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582 products in 73 categories |
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CaliforniaView MODIS Terra Truecolor
[CA-MODIS-Terra-123-True]
CaliforniaView: True color 250m MODIS image on May 3rd, 2022
CaliforniaView: True color 250m MODIS image on May 3rd, 2022
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Landsat-1 MSS 6, 5, 4
[landsat-1-madison-321]
Multispectral Scanner (MSS)
80-meter ground resolution in four spectralbands: Band 4 Visible green (0.5 to 0.6 µm) Band 5 Visible red (0.6 to 0.7 µm) Band 6 Near-Infrared (0.7 to 0.8 µm) Band 7 Near-Infrared (0.8 to 1.1...
Multispectral Scanner (MSS)
80-meter ground resolution in four spectral bands:
Band 4 Visible green (0.5 to 0.6 µm)
Band 5 Visible red (0.6 to 0.7 µm)
Band 6 Near-Infrared (0.7 to 0.8 µm)
Band 7 Near-Infrared (0.8 to 1.1 µm)
Six detectors for each spectral band provided six scan lines on each active scan
Ground Sampling Interval (pixel size): 57 x 79 m
Scene size: 170 km x 185 km (106 mi x 115 mi)
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OhioView-MODIS-FalseColor
[OhioView-MODIS-FalseColor]
OhioView-MODIS-FalseColor
OhioView-MODIS-FalseColor
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OhioView-MODIS-TrueColor
[OhioView-MODIS-TrueColor]
OhioView-MODIS-TrueColor
OhioView-MODIS-TrueColor
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NWS Watches and Warnings
[NWS-Alerts-Warnings]
Watches and warnings from NWS
Watches and warnings from NWS
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Landsat-1 MSS 6, 5, 4
[landsat-1-madison-321]
Multispectral Scanner (MSS)
80-meter ground resolution in four spectralbands: Band 4 Visible green (0.5 to 0.6 µm) Band 5 Visible red (0.6 to 0.7 µm) Band 6 Near-Infrared (0.7 to 0.8 µm) Band 7 Near-Infrared (0.8 to 1.1...
Multispectral Scanner (MSS)
80-meter ground resolution in four spectral bands:
Band 4 Visible green (0.5 to 0.6 µm)
Band 5 Visible red (0.6 to 0.7 µm)
Band 6 Near-Infrared (0.7 to 0.8 µm)
Band 7 Near-Infrared (0.8 to 1.1 µm)
Six detectors for each spectral band provided six scan lines on each active scan
Ground Sampling Interval (pixel size): 57 x 79 m
Scene size: 170 km x 185 km (106 mi x 115 mi)
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Australian Soil Moisture - Root Zone
[BOM-Root-Zone-Soil-Moisture]
Australian Bureau of Meteorology: Root Zone Soil Moisture is the sum ofwater in the AWRA-L Upper and Lower soil layers and represents the percentage of available water content in the top 1 m of the soil profile....
Australian Bureau of Meteorology: Root Zone Soil Moisture is the sum of water in the AWRA-L Upper and Lower soil layers and represents the percentage of available water content in the top 1 m of the soil profile. The maximum storage within the soil layer is calculated from the depth of the soil and the relative soil water storage capacity. More info at the link below.
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Cloud Top Cooling targets
[CIMSS-CTCtargets]
CIMSS-Cloud Top Cooling targets
CIMSS-Cloud Top Cooling targets
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Mountains Obscured Advisory
[AIRMET-MTN]
AIRMET-Mountain Obscured Advisory
AIRMET-Mountain Obscured Advisory
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Volcanic Ash Adv plumes
[VAA]
Volcanic Ash Advisories: Ash Clouds
Volcanic Ash Advisories: Ash Clouds
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True Color Clear View
[BRDF]
MODIS Clear View ConUS Composite. BRDF (Bidirectional ReluctanceDistribution Function) is a 16-day cloud-free composite.
MODIS Clear View ConUS Composite. BRDF (Bidirectional Reluctance Distribution Function) is a 16-day cloud-free composite.
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VIIRS Fire RGB - CIRA
[VIIRS-Fire-RGB-CIRA]
This RGB is created by assigning the VIIRS 3.74um channel to red, 0.87umchannel to green, and the 0.64um channel to blue. It is used to assess fire perimeters and burn scars. These data are produced by the Cooperative...
This RGB is created by assigning the VIIRS 3.74um channel to red, 0.87um channel to green, and the 0.64um channel to blue. It is used to assess fire perimeters and burn scars. These data are produced by the Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University.
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VIIRS Fire Temp RGB - CIRA
[VIIRS-Fire-Temp-RGB-CIRA]
This RGB is created by assigning the VIIRS 3.74um channel to red, 2.25umchannel to green, and the 1.61um channel to blue. It is used to assess fire intensity and size, with fires ranging from red (smallest/lowest intensity)...
This RGB is created by assigning the VIIRS 3.74um channel to red, 2.25um channel to green, and the 1.61um channel to blue. It is used to assess fire intensity and size, with fires ranging from red (smallest/lowest intensity) to yellow to white (hottest or most intense). These data are produced by the Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University.
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VIIRS Fire Temp RGB 375m CIRA
[VIIRS-Fire-Temp-RGB-375-CIRA]
This RGB is created by assigning the VIIRS 3.74um channel to red, 2.25umchannel to green, and the 1.61um channel to blue. It is used to assess fire intensity and size, with fires ranging from red (smallest/lowest intensity)...
This RGB is created by assigning the VIIRS 3.74um channel to red, 2.25um channel to green, and the 1.61um channel to blue. It is used to assess fire intensity and size, with fires ranging from red (smallest/lowest intensity) to yellow to white (hottest or most intense). These data are produced by the Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University.
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GOES CAPE
[cimssdpicapeli]
CIMSS-DPI Convective Available Potential Energy (Li et al. 2008)
CIMSS-DPI Convective Available Potential Energy (Li et al. 2008)
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GOES Lifted Index
[cimssdpilili]
GOES-DPI Lifted Index (Li et al. 2008)
GOES-DPI Lifted Index (Li et al. 2008)
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GOES Precipitable Water
[cimssdpipwli]
CIMSS-DPI Precipitable Water (mm)
CIMSS-DPI Precipitable Water (mm)
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Mean Snow Duration 1988-2017
[mean-snow-cover-1988-2017]
Global 4 km Multisensor Automated Snow and Ice Maps (GMASI) developed atthe NOAA/NESDIS Center for Satellite Applications and Research (STAR). The main function of the GMASI is to routinely generate global continuous maps...
Global 4 km Multisensor Automated Snow and Ice Maps (GMASI) developed at the NOAA/NESDIS Center for Satellite Applications and Research (STAR). The main function of the GMASI is to routinely generate global continuous maps of snow and ice cover distribution from combined observations in the visible/infrared and in the microwave spectral bands from operational meteorological polar orbiting and geostationary satellites.
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NOAA20 VIIRS Sea Ice Concentration Global
[j01-sic]
The Sea Ice Concentration products uses threshold reflectance(temperature) tests to detect possible ice cover for daytime (nighttime). Then uses a tie-point algorithm to determine fraction of grid cell at 1-km...
The Sea Ice Concentration products uses threshold reflectance (temperature) tests to detect possible ice cover for daytime (nighttime). Then uses a tie-point algorithm to determine fraction of grid cell at 1-km resolution covered by ice. The product is available over oceans, seas and lakes only under clear-sky conditions that is determined by VIIRS cloud mask.
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NOAA20 VIIRS Sea Ice Temperature Global
[j01-ist]
The Sea Ice Temperature product uses a split window algorithm that isdependent on bands M15 (~11 um) and M16 (~12 um) along with satellite scan angle to come up with an atmospheric correction term that adjusts clear...
The Sea Ice Temperature product uses a split window algorithm that is dependent on bands M15 (~11 um) and M16 (~12 um) along with satellite scan angle to come up with an atmospheric correction term that adjusts clear window Brightness Temperature to come up with a final IST value that is at 750 m resolution and has been shown to be within 1.5 K of validation measurements. The product is available over all water bodies, including rivers under clear-sky conditions that is determined by VIIRS cloud mask.
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NOAA20 VIIRS Sea Ice Thickness Global
[j01-ithk]
The Sea Ice Thickness product uses a one-dimensional thermodynamic icemodel (OTIM) The OTIM is based on the surface energy balance but does not directly use any channel data. Instead, it takes into account variables...
The Sea Ice Thickness product uses a one-dimensional thermodynamic ice model (OTIM) The OTIM is based on the surface energy balance but does not directly use any channel data. Instead, it takes into account variables such as VIIRS ice surface temperature and the VIIRS cloud mask to determine sea and lake ice thickness. The product is at 750 m resolution and available over all water bodies, including rivers under clear sky conditions that is determined by VIIRS cloud mask.
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SNPP VIIRS SEA Ice Concentration Global
[snpp-sic]
The Sea Ice Concentration products uses threshold reflectance(temperature) tests to detect possible ice cover for daytime (nighttime). Then uses a tie-point algorithm to determine fraction of grid cell at 1-km...
The Sea Ice Concentration products uses threshold reflectance (temperature) tests to detect possible ice cover for daytime (nighttime). Then uses a tie-point algorithm to determine fraction of grid cell at 1-km resolution covered by ice. The product is available over oceans, seas and lakes only under clear-sky conditions that is determined by VIIRS cloud mask.
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SNPP VIIRS Sea Ice Temperature Global
[snpp-ist]
The Sea Ice Temperature product uses a split window algorithm that isdependent on bands M15 (~11 um) and M16 (~12 um) along with satellite scan angle to come up with an atmospheric correction term that adjusts clear...
The Sea Ice Temperature product uses a split window algorithm that is dependent on bands M15 (~11 um) and M16 (~12 um) along with satellite scan angle to come up with an atmospheric correction term that adjusts clear window Brightness Temperature to come up with a final IST value that is at 750 m resolution and has been shown to be within 1.5 K of validation measurements. The product is available over all water bodies, including rivers under clear-sky conditions that is determined by VIIRS cloud mask.
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SNPP VIIRS Sea Ice Thickness Global
[snpp-ithk]
The Sea Ice Thickness product uses a one-dimensional thermodynamic icemodel (OTIM) The OTIM is based on the surface energy balance but does not directly use any channel data. Instead, it takes into account variables...
The Sea Ice Thickness product uses a one-dimensional thermodynamic ice model (OTIM) The OTIM is based on the surface energy balance but does not directly use any channel data. Instead, it takes into account variables such as VIIRS ice surface temperature and the VIIRS cloud mask to determine sea and lake ice thickness. The product is at 750 m resolution and available over all water bodies, including rivers under clear sky conditions that is determined by VIIRS cloud mask.
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VIIRS Fire Radiative Power I-band DB ConUS
[AFIMG-Points]
VIIRS 375m I-band high spatial resolution imagery provides a greaterresponse over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime...
VIIRS 375m I-band high spatial resolution imagery provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime performance. Consequently, these data are well suited for use in support of fire management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity. These data represent mean fire radiative power from SNPP and NOAA-20 Direct Broadcast imagery processed with CSPP software.
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FireWork Smoke Forecast - PM2.5 Column Diff
[RAQDPS-COL-Diff-25]
Canada’s Wildfire Smoke Prediction System (FireWork) produces daily smokeforecast maps. This map represents small particles (PM2.5), the whole atmosphere compressed (column), and the smoke-only after subtracting the...
Canada’s Wildfire Smoke Prediction System (FireWork) produces daily smoke forecast maps. This map represents small particles (PM2.5), the whole atmosphere compressed (column), and the smoke-only after subtracting the atmospheric background (diff). Smoke from wildfires in forests and grasslands can be a major source of air pollution for Canadians. The fine particles in the smoke can be a serious risk to health, particularly for children, seniors and those with heart or lung disease. Because smoke may be carried thousands of kilometers downwind, distant locations can be affected almost as severely as areas close to the fire. To help Canadians be better prepared, wildfire smoke forecast maps are available through the Government of Canada’s FireWork system. FireWork is an air quality prediction system that indicates how smoke from wildfires is expected to move across North America over the next 72 hours.
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HRRR CONUS/AK Near Surface Smoke
[HRRR-smoke-surface]
Operational model output from NECP. Developed at the NOAA Earth SystemResearch Laboratory High Resolution Rapid Refresh (HRRR) Surface Smoke forecast model, uses VIIRS inputs.
Operational model output from NECP. Developed at the NOAA Earth System Research Laboratory High Resolution Rapid Refresh (HRRR) Surface Smoke forecast model, uses VIIRS inputs.
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HRRR CONUS/AK Vertically Integrated Smoke
[HRRR-smoke-column]
Operational smoke model output from NCEP developed at the NOAA Earth SystemResearch Laboratory High Resolution Rapid Refresh (HRRR) Vertically Integrated Smoke forecast model, uses VIIRS inputs.
Operational smoke model output from NCEP developed at the NOAA Earth System Research Laboratory High Resolution Rapid Refresh (HRRR) Vertically Integrated Smoke forecast model, uses VIIRS inputs.
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RAP North America Near Surface Smoke
[RAP-smoke-surface]
The Rapid Refresh (RAP) is the continental-scale NOAA hourly-updatedassimilation/modeling system operational at NCEP. RAP covers North America and is comprised primarily of a numerical forecast model and an...
The Rapid Refresh (RAP) is the continental-scale NOAA hourly-updated assimilation/modeling system operational at NCEP. RAP covers North America and is comprised primarily of a numerical forecast model and an analysis/assimilation system to initialize that model. The RAP has a resolution of 13.5km and includes smoke forecast variables derived in part from VIIRS satellite inputs. RAP is complemented by the higher-resolution 3km High-Resolution Rapid Refresh (HRRR) model, which is also updated hourly and covering a smaller geographic domain.
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RAP North America Vertically Integrated Smoke
[RAP-smoke-column]
The Rapid Refresh (RAP) is the continental-scale NOAA hourly-updatedassimilation/modeling system operational at NCEP. RAP covers North America and is comprised primarily of a numerical forecast model and an...
The Rapid Refresh (RAP) is the continental-scale NOAA hourly-updated assimilation/modeling system operational at NCEP. RAP covers North America and is comprised primarily of a numerical forecast model and an analysis/assimilation system to initialize that model. The RAP has a resolution of 13.5km and includes smoke forecast variables derived in part from VIIRS satellite inputs. RAP is complemented by the higher-resolution 3km High-Resolution Rapid Refresh (HRRR) model, which is also updated hourly and covering a smaller geographic domain.
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Excessive Rainfall Outlook
[ERTA-NCEP]
Excessive Rainfall Outlook:
In the Excessive Rainfall Outlooks, theWeather Prediction Center (WPC) forecasts the probability that rainfall will exceed flash flood guidance at a point. Gridded FFG is provided by the...
Excessive Rainfall Outlook:
In the Excessive Rainfall Outlooks, the Weather Prediction Center (WPC) forecasts the probability that rainfall will exceed flash flood guidance at a point. Gridded FFG is provided by the twelve NWS River Forecast Centers (RFCs) whose service areas cover the lower 48 states. NCEP creates a national mosaic of FFG, whose 1, 3, and 6-hour values represent the amount of rainfall over those short durations which it is estimated would bring rivers and streams up to bankfull conditions. WPC estimates the likelihood that FFG will be exceeded by assessing environmental conditions (e.g. moisture content and steering winds), recognizing weather patterns commonly associated with heavy rainfall, and using a variety of deterministic and ensemble-based numerical model tools
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Flood Warnings Hydrological-VTEC (Issued)
[HVTEC]
For Flood Warnings (FLW) and follow up Flood Statements (FLS) at specificriver forecast points, the H-VTEC specifies the flood severity; immediate cause, timing of flood beginning, crest, and end; and how the flood...
For Flood Warnings (FLW) and follow up Flood Statements (FLS) at specific river forecast points, the H-VTEC specifies the flood severity; immediate cause,
timing of flood beginning, crest, and end; and how the flood compares to the flood of record.
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River Flood: ABI-daily
[River-Flood-ABI]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available 5-min CONUS imagery since sunrise on the given day. These products are expected to be most useful in mid- and low-latitude locations.
CONUS region
Quick guide
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River Flood: ABI-daily (tsp)
[River-Flood-ABItsp]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available 5-min CONUS imagery since sunrize through the given hour. These products are expected to be most useful in mid- and low-latitude locations.
CONUS region
Quick guide
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River Flood: ABI-hourly
[River-Flood-ABI-hourly]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available 5-min CONUS imagery since sunrize through the given hour. These products are expected to be most useful in mid- and low-latitude locations.
CONUS region
Quick guide
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River Flood: ABI-hourly (tsp)
[River-Flood-ABItsp-hourly]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available 5-min CONUS imagery since sunrize through the given hour. These products are expected to be most useful in mid- and low-latitude locations.
CONUS region
Quick guide
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River Flood: AHI
[RIVER-FLD-AHI]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available 10-min imagery since sunrise on the given day. These products are expected to be most useful in mid- and low-latitude locations.
For more information visit: Here
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River Flood: Joint ABI/VIIRS
[RIVER-FLD-joint-ABI]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available ABI-full disk imagery and VIIRS imagery since sunrise on the given day.
For more information visit: Here
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River Flood: Joint AHI/VIIRS
[RIVER-FLD-joint-AHI]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available AHI-full disk imagery and VIIRS imagery since sunrise on the given day.
For more information visit: Here
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River Flood: 1 day VIIRS composite
[RIVER-FLDglobal-composite1]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available VIIRS daylight imagery over the past 1 day.
For more information visit: Here
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River Flood: 5 day VIIRS composite
[RIVER-FLDglobal-composite]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available VIIRS daylight imagery over the past 5 days.
For more information visit: Here
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River Flood: Alaska
[RIVER-FLDall-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region
Quick guide
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River Flood: Alaska (transparent)
[RIVER-FLDtsp-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region(Transparent flood-free land)
Quick guide
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River Flood: Global
[RIVER-FLDglobal]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Global(CSPP product)
Quick guide
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River Flood: Missouri Basin
[RIVER-FLDall-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin
Quick guide
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River Flood: Missouri Basin (transparent)
[RIVER-FLDtsp-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin(Transparent flood-free land)
Quick guide
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River Flood: North Central Basin
[RIVER-FLDall-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin
Quick guide
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River Flood: North Central Basin (transparent)
[RIVER-FLDtsp-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin(Transparent flood-free land)
Quick guide
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River Flood: North East Basin
[RIVER-FLDall-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin
Quick guide
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River Flood: North East Basin (transparent)
[RIVER-FLDtsp-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin(Transparent flood-free land)
Quick guide
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River Flood: North West
[RIVER-FLDall-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region
Quick guide
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River Flood: North West (transparent)
[RIVER-FLDtsp-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region(Transparent flood-free land)
Quick guide
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River Flood: South East
[RIVER-FLDall-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region
Quick guide
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River Flood: South East (transparent)
[RIVER-FLDtsp-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region(Transparent flood-free land)
Quick guide
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River Flood: South West
[RIVER-FLDall-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region
Quick guide
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River Flood: South West (tsp)
[RIVER-FLDtsp-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region(Transparent flood-free land)
Quick guide
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River Flood: US
[RIVER-FLDall-US]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
US
Quick guide
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River Flood: West Gulf Basin
[RIVER-FLDall-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin
Quick guide
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River Flood: West Gulf Basin (transparent)
[RIVER-FLDtsp-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin(Transparent flood-free land)
Quick guide
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VIIRS Floodwater Depth
[VIIRS-3Dflood]
VIIRS downscaling software is designed to downscale the VIIRS 375-m floodproducts to 30-m flood products. The software uses Suomi-NPP
VIIRS downscaling software is designed to downscale the VIIRS 375-m flood products to 30-m flood products. The software uses Suomi-NPP
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Landsat 8 Look Natural Color (Swaths)
[lsat8-llook-fc]
View of lsat8-llook-fc-scenes
View of lsat8-llook-fc-scenes
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Landsat 8 Look Thermal IR (Swaths)
[lsat8-llook-tir]
View of lsat8-llook-tir-scenes
View of lsat8-llook-tir-scenes
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Landsat Footprints (WRS-2)
[wrs2-land]
The Worldwide Reference System (WRS) is a global notation used incataloging Landsat data. Landsat 8 and Landsat 7 follow the WRS-2, as did Landsat 5 and Landsat 4.
The Worldwide Reference System (WRS) is a global notation used in cataloging Landsat data. Landsat 8 and Landsat 7 follow the WRS-2, as did Landsat 5 and Landsat 4.
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Landsat 9 Look Natural Color (Swaths)
[lsat9-llook-fc]
View of lsat9-llook-fc-scenes
View of lsat9-llook-fc-scenes
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Landsat 9 Look Thermal IR (Swaths)
[lsat9-llook-tir]
View of lsat9-llook-tir-scenes
View of lsat9-llook-tir-scenes
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HRRR ConUS Latest Freezing MASK
[HRR-CONUS-FZRN-SFC]
HRRR ConUS Latest Freezing MASK
HRRR ConUS Latest Freezing MASK
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HRRR ConUS Latest Ice Mask
[HRR-CONUS-ICEP-SFC]
HRRR ConUS Latest Ice Mask
HRRR ConUS Latest Ice Mask
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HRRR ConUS Latest Precipitation Rate
[HRR-CONUS-PCP-LATEST]
View of HRR-CONUS-PCP-SFC
View of HRR-CONUS-PCP-SFC
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HRRR ConUS Latest Rain Mask
[HRR-CONUS-RAIN-SFC]
HRRR ConUS Latest Rain Mask
HRRR ConUS Latest Rain Mask
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HRRR ConUS Latest Simulated Radar
[HRR-CONUS-RADAR-LATEST]
View of HRR-CONUS-PCP-SFC
View of HRR-CONUS-PCP-SFC
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HRRR ConUS Latest Snow Mask
[HRR-CONUS-SNOW-SFC]
HRRR ConUS Latest Snow Mask
HRRR ConUS Latest Snow Mask
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RAP ConUS Latest Simulated Radar
[RAP-CONUS-PRAT-SFC-DBZ]
View of RAP-CONUS-PRAT-SFC
View of RAP-CONUS-PRAT-SFC
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VIIRS Fire Radiative Power I-band DB ConUS
[AFIMG-Points]
VIIRS 375m I-band high spatial resolution imagery provides a greaterresponse over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime...
VIIRS 375m I-band high spatial resolution imagery provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime performance. Consequently, these data are well suited for use in support of fire management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity. These data represent mean fire radiative power from SNPP and NOAA-20 Direct Broadcast imagery processed with CSPP software.
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GOES 15 Full Disk LWIR
[GOES-W-FD-LWIR]
GOES 15 Full Disk LWIR (Long Wave Infrared)
GOES 15 Full Disk LWIR (Long Wave Infrared)
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GOES 15 Full Disk NIR
[GOES-W-FD-NIR]
GOES 15 Full Disk NIR (Near Infrared)
GOES 15 Full Disk NIR (Near Infrared)
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GOES 15 Full Disk VIS
[GOES-W-FD-VIS]
GOES 15 Full Disk VIS (Visible)
GOES 15 Full Disk VIS (Visible)
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GOES 15 Full Disk WV
[GOES-W-FD-WV]
GOES 15 Full Disk WV (Water Vapor)
GOES 15 Full Disk WV (Water Vapor)
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GOES East ABI ConUS L2 "Sandwich"
[GOES-16SandwichCONUS]
A composite image of the 10.35 um IR brightness temperatures with the 0.64micron normalized visible brightness during the day. Transitions to an IR image at night.
A composite image of the 10.35 um IR brightness temperatures with the 0.64 micron normalized visible brightness during the day. Transitions to an IR image at night.
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GOES East Daily Fire Detections - CONUS
[NGFS-DAILY-CONUS-EAST]
This terrain-corrected product represents cumulative detections at the 2kmABI pixel level in a 24hr UTC day. For performance, serial repeat detections for the same pixel have been removed. The source data are CSV...
This terrain-corrected product represents cumulative detections at the 2km ABI pixel level in a 24hr UTC day. For performance, serial repeat detections for the same pixel have been removed. The source data are CSV files from the link below.
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GOES East Day Fire RGB - CONUS - CIRA
[goes-east-conus-day-fire-rgb]
This product is uploaded directly to RealEarth every 5-minutes by CIRA. More info to follow.
This product is uploaded directly to RealEarth every 5-minutes by CIRA. More info to follow.
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GOES East FDC
[goes-east-conus-FDCC]
The GOES-R Fire Detection and Characterization (FDC) data product uses bothvisible and infrared (IR) ABI spectral channels (or bands) to locate fires and retrieve fire characteristics. Fires produce a stronger signal in...
The GOES-R Fire Detection and Characterization (FDC) data product uses both visible and infrared (IR) ABI spectral channels (or bands) to locate fires and retrieve fire characteristics. Fires produce a stronger signal in mid-wave IR bands (around 4 µm) than they do in longwave IR bands (such as 11 µm). That differential response forms the basis for the GOES-R FDC product. The 3.9 µm ABI band is particularly useful for fire detection. Its shorter wavelength is sensitive to the hottest part of a fire pixel.
Right-click to "Probe" pixel value. 10-15 indicates first detection. 30-35 indicates multiple detections in the past 12 hours.
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GOES East Fire Temp RGB - CONUS - CIRA
[goes-east-conus-fire-temp-rgb]
This product is uploaded directly to RealEarth every 5-minutes by CIRA. TheFire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more...
This product is uploaded directly to RealEarth every 5-minutes by CIRA. The Fire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more intense fires emit more radiation at shorter wavelengths in the shortwave IR. Small or "cool" fires will only show up at 3.7 μm and appear red. Moderately intense or large fires will be detected at both 3.7 μm and 2.25 μm and will appear orange to yellow (yellow being more intense). Very intense fires will be detected by all three bands and appear white.
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GOES East Scene Fire Detections - CONUS
[NGFS-SCENE-CONUS-EAST]
Near real-time pixel-level thermal anomaly detections from the CONUS scanof ABI on GOES East. Pixel corner point locations are terrain corrected. These update every 5-minutes.
Near real-time pixel-level thermal anomaly detections from the CONUS scan of ABI on GOES East. Pixel corner point locations are terrain corrected. These update every 5-minutes.
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GOES East ABI ConUS B02 Hi-Res "Red" Visible
[G16-ABI-CONUS-BAND02]
The ‘Red’ Visible band – 0.64 µm – has the
finest spatialresolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air...
The ‘Red’ Visible band – 0.64 µm – has the
finest spatial resolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air boundaries, or overshooting tops or cumulus clouds. It has also been used to document daytime snow
and ice cover, diagnose low-level cloud-drift
winds, assist with detection of volcanic ash
and analysis of hurricanes and winter storms.
The ‘Red’ Visible band is also essential for
creation of “true color” imagery.
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GOES East ABI ConUS B03 "Veggie"
[G16-ABI-CONUS-BAND03]
The 0.86 μm band (a reflective band) detects daytime clouds, fog, andaerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86...
The 0.86 μm band (a reflective band) detects daytime clouds, fog, and aerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86 μm band can detect burn scars and thereby show land characteristics to determine fire and run-off potential. Vegetated land, in general, shows up brighter in this band than in visible bands. Landwater contrast is also large in this band.
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GOES East ABI ConUS B07 "Fire"
[G16-ABI-CONUS-BAND07]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES East ABI ConUS B07 "Fire" enhanced
[G16-ABI-CONUS-BAND07-FIRE]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES East ABI ConUS B09 Mid-level Water Vapor
[G16-ABI-CONUS-BAND09]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level moisture (for legacy vertical moisture profiles) and identifying regions where turbulence might
exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9µm by water vapor.
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GOES East ABI ConUS B09 Mid-level Water Vapor enhanced
[G16-ABI-CONUS-BAND09-VAPR]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level
moisture (for legacy vertical moisture profiles) and identifying regions where turbulence might exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9µm by water vapor.
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GOES East ABI ConUS B13 "Clean" Infrared
[G16-ABI-CONUS-BAND13]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES East ABI ConUS B13 "Clean" Infrared enhanced
[G16-ABI-CONUS-BAND13-GRAD]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES East ABI ConUS RGB True Color
[G16-ABI-CONUS-TC]
True Color Imagery gives an image that is
approximately as you would see itfrom Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product,...
True Color Imagery gives an image that is
approximately as you would see it from Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product, approximates the green by combining Blue (0.47 µm), Red (0.64 µm) and ‘Veggie’ (0.86 µm) bands. The use of the Veggie band is important because it mimics the enhanced reflectivity present in the Green Band.
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GOES East ABI FD FLS Cloud Thickness
[G16-ABI-FD-FLS-Thickness]
Cloud thickness: Estimate of the geometric thickness (cloud top - cloudbase) of a single layer liquid water stratus cloud.
Cloud thickness: Estimate of the geometric thickness (cloud top - cloud base) of a single layer liquid water stratus cloud.
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GOES East ABI FD FLS IFR Fog Probability
[G16-ABI-FD-FLS-IFR]
IFR probability: Probability that IFR (or lower) flight rule category ispresent for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
IFR probability: Probability that IFR (or lower) flight rule category is present for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
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GOES East ABI FD FLS LIFR Fog Probability
[G16-ABI-FD-FLS-LIFR]
LIFR probability: Probability that LIFR (or lower) flight rule category ispresent for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
LIFR probability: Probability that LIFR (or lower) flight rule category is present for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
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GOES East ABI FD FLS MVFR Fog Probability
[G16-ABI-FD-FLS-MVFR]
MVFR probability: Probability that MVFR (or lower) flight rule category ispresent for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
MVFR probability: Probability that MVFR (or lower) flight rule category is present for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
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GOES EAST ABI L2 South America Sandwich
[GOES-16-SA-Sandwich]
A composite image of the 10.35 um IR brightness temperatures with the 0.64micron normalized visible brightness temperatures during the day. Transitions to an IR image at night. Currently, this product only extends...
A composite image of the 10.35 um IR brightness temperatures with the 0.64 micron normalized visible brightness temperatures during the day. Transitions to an IR image at night. Currently, this product only extends to 35 South.
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GOES East GLM Full Disk Group Density
[glmgroupdensity]
The Geostationary Lightning Mapper, or GLM, on board GeostationaryOperational Environmental Satellite– R Series spacecraft, is the first operational lightning mapper flown on a geostationary satellite. GLM...
The Geostationary Lightning Mapper, or GLM, on board Geostationary Operational Environmental Satellite– R Series spacecraft, is the first operational lightning mapper flown on a geostationary satellite. GLM detects the light emitted by lightning at the tops of clouds day and night and collects information such as the frequency, location and extent of lightning discharges. The instrument measures total lightning, both in-cloud and cloud-to-ground, to aid in forecasting developing severe storms and a wide range of high-impact environmental phenomena including hailstorms, microburst winds, tornadoes, hurricanes, ash clouds, and snowstorms.
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GOES East GLM Full Disk Group Points
[glmgrouppoints]
The Geostationary Lightning Mapper, or GLM, on board GeostationaryOperational Environmental Satellite– R Series spacecraft, is the first operational lightning mapper flown on a geostationary satellite. GLM...
The Geostationary Lightning Mapper, or GLM, on board Geostationary Operational Environmental Satellite– R Series spacecraft, is the first operational lightning mapper flown on a geostationary satellite. GLM detects the light emitted by lightning at the tops of clouds day and night and collects information such as the frequency, location and extent of lightning discharges. The instrument measures total lightning, both in-cloud and cloud-to-ground, to aid in forecasting developing severe storms and a wide range of high-impact environmental phenomena including hailstorms, microburst winds, tornadoes, hurricanes, ash clouds, and snowstorms.
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GOES East ABI Full Disk B02 Hi-Res "Red" Visible
[G16-ABI-FD-BAND02]
The ‘Red’ Visible band – 0.64 µm – has the
finest spatialresolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air...
The ‘Red’ Visible band – 0.64 µm – has the
finest spatial resolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air boundaries, or overshooting tops or cumulus clouds. It has also been used to document daytime snow and ice cover, diagnose low-level cloud-drift winds, assist with detection of volcanic ash and analysis of hurricanes and winter storms. The ‘Red’ Visible band is also essential for creation of “true color imagery.
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GOES East ABI Full Disk B03 "Veggie"
[G16-ABI-FD-BAND03]
The 0.86 μm band (a reflective band) detects daytime clouds, fog, andaerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86...
The 0.86 μm band (a reflective band) detects daytime clouds, fog, and aerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86 μm band can detect burn scars and thereby show land characteristics to determine fire and run-off potential. Vegetated land, in general, shows up brighter in this band than in visible bands. Landwater contrast is also large in this band.
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GOES East ABI Full Disk B07 "Fire"
[G16-ABI-FD-BAND07]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES East ABI Full Disk B07 "Fire" enhanced
[G16-ABI-FD-BAND07-FIRE]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES East ABI Full Disk B09 Mid-level Water Vapor
[G16-ABI-FD-BAND09]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level
moisture (for legacy vertical moisture profiles) and identifying regions where turbulence might exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9µm by water vapor.
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GOES East ABI Full Disk B09 Mid-level Water Vapor enhanced
[G16-ABI-FD-BAND09-VAPR]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level moisture (for legacy vertical moisture profiles)
and identifying regions where turbulence might exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9µm by water vapor.
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GOES East ABI Full Disk B13 "Clean" Infrared
[G16-ABI-FD-BAND13]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES East ABI Full Disk B13 "Clean" Infrared enhanced
[G16-ABI-FD-BAND13-GRAD]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES East ABI Full Disk RGB True Color
[G16-ABI-FD-TC]
True Color Imagery gives an image that is
approximately as you would see itfrom Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product,...
True Color Imagery gives an image that is
approximately as you would see it from Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product, approximates the green by combining Blue (0.47 µm), Red (0.64 µm) and ‘Veggie’ (0.86µm) bands. The use of the Veggie band is important because it mimics the enhanced reflectivity present in the Green Band.
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GOES East ABI Meso1 L2 "Sandwich"
[GOES-16SandwichMESO1]
A composite image of the 10.35 um IR A composite image of the 10.35 um IRbrightness temperatures with the 0.64 micron normalized visible brightness during the day. Transitions to an IR image at night.
A composite image of the 10.35 um IR A composite image of the 10.35 um IR brightness temperatures with the 0.64 micron normalized visible brightness during the day. Transitions to an IR image at night.
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GOES East Day Fire RGB - Meso1 - CIRA
[goes-east-meso1-day-fire-rgb]
This product is uploaded directly to RealEarth every minute by CIRA. Moreinfo to follow.
This product is uploaded directly to RealEarth every minute by CIRA. More info to follow.
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GOES East Fire Temp RGB - Meso1 - CIRA
[goes-east-meso1-fire-temp-rgb]
This product is uploaded directly to RealEarth every minute by CIRA. TheFire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more...
This product is uploaded directly to RealEarth every minute by CIRA. The Fire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more intense fires emit more radiation at shorter wavelengths in the shortwave IR. Small or "cool" fires will only show up at 3.7 μm and appear red. Moderately intense or large fires will be detected at both 3.7 μm and 2.25 μm and will appear orange to yellow (yellow being more intense). Very intense fires will be detected by all three bands and appear white.
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GOES East Scene Fire Detections - Mesoscale1
[NGFS-SCENE-Mesoscale1-EAST]
Near real-time pixel-level thermal anomaly detections from the Mesoscale-1scan of ABI on GOES East. Pixel corner point locations are terrain corrected. These update every minute.
Near real-time pixel-level thermal anomaly detections from the Mesoscale-1 scan of ABI on GOES East. Pixel corner point locations are terrain corrected. These update every minute.
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GOES East ABI Meso1 B02 Hi-Res "Red" Visible
[G16-ABI-MESO1-BAND02]
The ‘Red’ Visible band – 0.64 µm – has the
finest spatialresolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air...
The ‘Red’ Visible band – 0.64 µm – has the
finest spatial resolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air boundaries, or overshooting tops or cumulus clouds. It has also been used to document daytime snow and ice cover, diagnose low-level cloud-drift winds, assist with detection of volcanic ash and analysis of hurricanes and winter storms. The ‘Red’ Visible band is also essential for creation of “true color” imagery.
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GOES East ABI Meso1 B03 "Veggie"
[G16-ABI-MESO1-BAND03]
The 0.86 μm band (a reflective band) detects daytime clouds, fog, andaerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86...
The 0.86 μm band (a reflective band) detects daytime clouds, fog, and aerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86 μm band can detect burn scars and thereby show land characteristics to determine fire and run-off potential. Vegetated land, in general, shows up brighter in this band than in visible bands. Landwater contrast is also large in this band.
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GOES East ABI Meso1 B07 "Fire"
[G16-ABI-MESO1-BAND07]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES East ABI Meso1 B07 "Fire" enhanced
[G16-ABI-MESO1-BAND07-FIRE]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES East ABI Meso1 B09 Mid-level Water Vapor
[G16-ABI-MESO1-BAND09]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level
moisture (for legacy vertical moisture profiles) and identifying regions where turbulence might exist. Surface features are usually not apparent in this band. Brightness Temperatures show
cooling because of absorption of energy at 6.9µm by water vapor.
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GOES East ABI Meso1 B09 Mid-level Water Vapor enhanced
[G16-ABI-MESO1-BAND09-VAPR]
The 6.9 µm “Mid-level water vapor” band is one
of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and...
The 6.9 µm “Mid-level water vapor” band is one
of three water vapor bands on the ABI, and is
used for tracking middle-tropospheric winds,
identifying jet streams, forecasting hurricane
track and mid-latitude storm motion, monitoring
severe weather potential, estimating mid-level
moisture (for legacy vertical moisture profiles)
and identifying regions where turbulence might
exist. Surface features are usually not apparent
in this band. Brightness Temperatures show
cooling because of absorption of energy at 6.9
µm by water vapor.
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GOES East ABI Meso1 B13 "Clean" Infrared
[G16-ABI-MESO1-BAND13]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES East ABI Meso1 B13 "Clean" Infrared enhanced
[G16-ABI-MESO1-BAND13-GRAD]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES East ABI Meso1 B13 "Clean" Infrared red
[G16-ABI-MESO1-BAND13-RED]
True Color Imagery gives an image that is approximately as you would see itfrom Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product,...
True Color Imagery gives an image that is approximately as you would see it from Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product, approximates the green by combining Blue (0.47 µm), Red (0.64 µm) and ‘Veggie’ (0.86 µm) bands. The use of the Veggie band is important because it mimics the enhanced reflectivity present in the Green Band.
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GOES East ABI Meso1 RGB True Color
[G16-ABI-MESO1-TC]
True Color Imagery gives an image that is approximately as you would see itfrom Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product,...
True Color Imagery gives an image that is approximately as you would see it from Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product, approximates the green by combining Blue (0.47 µm), Red (0.64 µm) and ‘Veggie’ (0.86 µm) bands. The use of the Veggie band is important because it mimics the enhanced reflectivity present in the Green Band.
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GOES East ABI Meso2 L2 "Sandwich"
[GOES-16SandwichMESO2]
NOTE: When MESO1 is in 30 second mode, MESO2 will not update.
A compositeimage of the 10.35 um IR A composite image of the 10.35 um IR brightness temperatures with the 0.64 micron normalized visible brightness during the...
NOTE: When MESO1 is in 30 second mode, MESO2 will not update.
A composite image of the 10.35 um IR A composite image of the 10.35 um IR brightness temperatures with the 0.64 micron normalized visible brightness during the day. Transitions to an IR image at night.
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GOES East Day Fire RGB - Meso2 - CIRA
[goes-east-meso2-day-fire-rgb]
This product is uploaded directly to RealEarth every minute by CIRA. Moreinfo to follow.
This product is uploaded directly to RealEarth every minute by CIRA. More info to follow.
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GOES East Fire Temp RGB - Meso2 - CIRA
[goes-east-meso2-fire-temp-rgb]
This product is uploaded directly to RealEarth every minute by CIRA. TheFire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more...
This product is uploaded directly to RealEarth every minute by CIRA. The Fire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more intense fires emit more radiation at shorter wavelengths in the shortwave IR. Small or "cool" fires will only show up at 3.7 μm and appear red. Moderately intense or large fires will be detected at both 3.7 μm and 2.25 μm and will appear orange to yellow (yellow being more intense). Very intense fires will be detected by all three bands and appear white.
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GOES East Scene Fire Detections - Mesoscale2
[NGFS-SCENE-Mesoscale2-EAST]
Near real-time pixel-level thermal anomaly detections from the Mesoscale-2scan of ABI on GOES East. Pixel corner point locations are terrain corrected. These update every minute.
Near real-time pixel-level thermal anomaly detections from the Mesoscale-2 scan of ABI on GOES East. Pixel corner point locations are terrain corrected. These update every minute.
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GOES East ABI Meso2 B02 Hi-Res "Red" Visible
[G16-ABI-MESO2-BAND02]
The ‘Red’ Visible band – 0.64 µm – has the
finest spatialresolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air...
The ‘Red’ Visible band – 0.64 µm – has the
finest spatial resolution (0.5 km at the subsatellite
point) of all ABI bands. Thus it is ideal
to identify small-scale features such as river
fogs and fog/clear air boundaries, or
overshooting tops or cumulus clouds. It has
also been used to document daytime snow
and ice cover, diagnose low-level cloud-drift
winds, assist with detection of volcanic ash
and analysis of hurricanes and winter storms.
The ‘Red’ Visible band is also essential for
creation of “true color” imagery.
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|
GOES East ABI Meso2 B03 "Veggie"
[G16-ABI-MESO2-BAND03]
The 0.86 μm band (a reflective band) detects daytime clouds, fog, andaerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86...
The 0.86 μm band (a reflective band) detects daytime clouds, fog, and aerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86 μm band can detect burn scars and thereby show land characteristics to determine fire and run-off potential. Vegetated land, in general, shows up brighter in this band than in visible bands. Landwater contrast is also large in this band.
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GOES East ABI Meso2 B07 "Fire"
[G16-ABI-MESO2-BAND07]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES East ABI Meso2 B07 "Fire" enhanced
[G16-ABI-MESO2-BAND07-FIRE]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES East ABI Meso2 B09 Mid-level Water Vapor
[G16-ABI-MESO2-BAND09]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level moisture (for legacy vertical moisture profiles)
and identifying regions where turbulence might exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9µm by water vapor.
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GOES East ABI Meso2 B09 Mid-level Water Vapor enhanced
[G16-ABI-MESO2-BAND09-VAPR]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level
moisture (for legacy vertical moisture profiles) and identifying regions where turbulence might exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9µm by water vapor.
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GOES East ABI Meso2 B13 "Clean" Infrared
[G16-ABI-MESO2-BAND13]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES East ABI Meso2 B13 "Clean" Infrared blue
[G16-ABI-MESO2-B13-CYAN]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES East ABI Meso2 B13 "Clean" Infrared enhanced
[G16-ABI-MESO2-BAND13-GRAD]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES East ABI Meso2 RGB True Color
[G16-ABI-MESO2-TC]
True Color Imagery gives an image that is approximately as you would see itfrom Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product,...
True Color Imagery gives an image that is approximately as you would see it from Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product, approximates the green by combining Blue (0.47 µm), Red (0.64 µm) and ‘Veggie’ (0.86 µm) bands. The use of the Veggie band is important because it mimics the enhanced reflectivity present in the Green Band.
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GOES-West 2020 June-Oct (20230809 tag)
[wscsTag20230809]
Case Study pixel-level thermal anomaly detections in a study region cutfrom FD scan of ABI on GOES-17. Pixel corner point locations are terrain corrected. These update every 10-minutes.
Case Study pixel-level thermal anomaly detections in a study region cut from FD scan of ABI on GOES-17. Pixel corner point locations are terrain corrected. These update every 10-minutes.
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GOES West Daily Fire Detections - CONUS
[NGFS-DAILY-CONUS-WEST]
This terrain-corrected product represents cumulative detections at the 2kmABI pixel level in a 24hr UTC day. For performance, serial repeat detections for the same pixel have been removed. The source data are CSV...
This terrain-corrected product represents cumulative detections at the 2km ABI pixel level in a 24hr UTC day. For performance, serial repeat detections for the same pixel have been removed. The source data are CSV files from the link below.
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GOES West Day Fire RGB - CONUS - CIRA
[goes-west-conus-day-fire-rgb]
This product is uploaded directly to RealEarth every 5-minutes by CIRA. More info to follow.
This product is uploaded directly to RealEarth every 5-minutes by CIRA. More info to follow.
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GOES West FDC
[goes-west-conus-FDCC]
The GOES-R Fire Detection and Characterization (FDC) data product uses bothvisible and infrared (IR) ABI spectral channels (or bands) to locate fires and retrieve fire characteristics. Fires produce a stronger signal in...
The GOES-R Fire Detection and Characterization (FDC) data product uses both visible and infrared (IR) ABI spectral channels (or bands) to locate fires and retrieve fire characteristics. Fires produce a stronger signal in mid-wave IR bands (around 4 µm) than they do in longwave IR bands (such as 11 µm). That differential response forms the basis for the GOES-R FDC product. The 3.9 µm ABI band is particularly useful for fire detection. Its shorter wavelength is sensitive to the hottest part of a fire pixel.
Right-click to "Probe" pixel value. 10-15 indicates first detection. 30-35 indicates multiple detections in the past 12 hours.
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GOES West Fire Temp RGB - CONUS - CIRA
[goes-west-conus-fire-temp-rgb]
This product is uploaded directly to RealEarth every 5-minutes by CIRA. TheFire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more...
This product is uploaded directly to RealEarth every 5-minutes by CIRA. The Fire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more intense fires emit more radiation at shorter wavelengths in the shortwave IR. Small or "cool" fires will only show up at 3.7 μm and appear red. Moderately intense or large fires will be detected at both 3.7 μm and 2.25 μm and will appear orange to yellow (yellow being more intense). Very intense fires will be detected by all three bands and appear white.
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GOES West Scene Fire Detections - CONUS
[NGFS-SCENE-CONUS-WEST]
Near real-time pixel-level thermal anomaly detections from the CONUS scanof ABI on GOES West. Pixel corner point locations are terrain corrected. These update every 5-minutes.
Near real-time pixel-level thermal anomaly detections from the CONUS scan of ABI on GOES West. Pixel corner point locations are terrain corrected. These update every 5-minutes.
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GOES West ABI ConUS B02 Hi-Res "Red" Visible
[G18-ABI-CONUS-BAND02]
he ‘Red’ Visible band – 0.64 µm – has the
finest spatialresolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air...
he ‘Red’ Visible band – 0.64 µm – has the
finest spatial resolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air boundaries, or overshooting tops or cumulus clouds. It has also been used to document daytime snow and ice cover, diagnose low-level cloud-drift winds, assist with detection of volcanic ash and analysis of hurricanes and winter storms. The ‘Red’ Visible band is also essential for creation of “true color” imagery.
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GOES West ABI ConUS B03 "Veggie"
[G18-ABI-CONUS-BAND03]
The 0.86 μm band (a reflective band) detects daytime clouds, fog, andaerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86...
The 0.86 μm band (a reflective band) detects daytime clouds, fog, and aerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86 μm band can detect burn scars and thereby show land characteristics to determine fire and run-off potential. Vegetated land, in general, shows up brighter in this band than in visible bands. Landwater contrast is also large in this band.
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GOES West ABI ConUS B07 "Fire"
[G18-ABI-CONUS-BAND07]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES West ABI ConUS B07 "Fire" enhanced
[G18-ABI-CONUS-BAND07-FIRE]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES West ABI ConUS B09 Mid-level Water Vapor
[G18-ABI-CONUS-BAND09]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level moisture (for legacy vertical moisture profiles)
and identifying regions where turbulence might exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9 µm by water vapor.
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GOES West ABI ConUS B09 Mid-level Water Vapor enhanced
[G18-ABI-CONUS-BAND09-VAPR]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level moisture (for legacy vertical moisture profiles)
and identifying regions where turbulence might exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9 µm by water vapor.
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GOES West ABI ConUS B13 "Clean" Infrared
[G18-ABI-CONUS-BAND13]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES West ABI ConUS B13 "Clean" Infrared enhanced
[G18-ABI-CONUS-BAND13-GRAD]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature
identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES West ABI FD Cloud Thickness
[G18-ABI-FD-FLS-Thickness]
Cloud thickness: Estimate of the geometric thickness (cloud top - cloudbase) of a single layer liquid water stratus cloud.
Cloud thickness: Estimate of the geometric thickness (cloud top - cloud base) of a single layer liquid water stratus cloud.
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GOES West ABI FD FLS IFR Fog Probability
[G18-ABI-FD-FLS-IFR]
IFR probability: Probability that IFR (or lower) flight rule category ispresent for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
IFR probability: Probability that IFR (or lower) flight rule category is present for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
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GOES West ABI FD FLS LIFR Fog Probability
[G18-ABI-FD-FLS-LIFR]
LIFR probability: Probability that LIFR (or lower) flight rule category ispresent for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
LIFR probability: Probability that LIFR (or lower) flight rule category is present for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
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GOES West ABI FD FLS MVFR Fog Probability
[G18-ABI-FD-FLS-MVFR]
MVFR probability: Probability that MVFR (or lower) flight rule category ispresent for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
MVFR probability: Probability that MVFR (or lower) flight rule category is present for a given GOES satellite pixel determined by fusing satellite and NWP model data using a naive Bayesian probabilistic model and classifier.
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GOES West ABI Full Disk B02 Hi-Res "Red" Visible
[G18-ABI-FD-BAND02]
he ‘Red’ Visible band – 0.64 µm – has the
finest spatialresolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air...
he ‘Red’ Visible band – 0.64 µm – has the
finest spatial resolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air boundaries, or overshooting tops or cumulus clouds. It has also been used to document daytime snow and ice cover, diagnose low-level cloud-drift winds, assist with detection of volcanic ash and analysis of hurricanes and winter storms. The ‘Red’ Visible band is also essential for creation of “true color” imagery.
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GOES West ABI Full Disk B03 "Veggie"
[G18-ABI-FD-BAND03]
The 0.86 μm band (a reflective band) detects daytime clouds, fog, andaerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86...
The 0.86 μm band (a reflective band) detects daytime clouds, fog, and aerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86 μm band can detect burn scars and thereby show land characteristics to determine fire and run-off potential. Vegetated land, in general, shows up brighter in this band than in visible bands. Landwater contrast is also large in this band.
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GOES West ABI Full Disk B07 "Fire"
[G18-ABI-FD-BAND07]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well assignificant reflected solar radiation during the day.
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GOES West ABI Full Disk B07 "Fire" enhanced
[G18-ABI-FD-BAND07-FIRE]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES West ABI Full Disk B09 Mid-level Water Vapor
[G18-ABI-FD-BAND09]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level
moisture (for legacy vertical moisture profiles) and identifying regions where turbulence might exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9 µm by water vapor.
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GOES West ABI Full Disk B09 Mid-level Water Vapor enhanced
[G18-ABI-FD-BAND09-VAPR]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level moisture (for legacy vertical moisture profiles) and identifying regions where turbulence might
exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9 µm by water vapor.
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GOES West ABI Full Disk B13 "Clean" Infrared
[G18-ABI-FD-BAND13]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES West ABI Full Disk B13 "Clean" Infrared enhanced
[G18-ABI-FD-BAND13-GRAD]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric ...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES West Day Fire RGB - Meso1 - CIRA
[goes-west-meso1-day-fire-rgb]
This product is uploaded directly to RealEarth every minute by CIRA. Moreinfo to follow.
This product is uploaded directly to RealEarth every minute by CIRA. More info to follow.
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GOES West Fire Temp RGB - Meso1 - CIRA
[goes-west-meso1-fire-temp-rgb]
This product is uploaded directly to RealEarth every minute by CIRA. TheFire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more...
This product is uploaded directly to RealEarth every minute by CIRA. The Fire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more intense fires emit more radiation at shorter wavelengths in the shortwave IR. Small or "cool" fires will only show up at 3.7 μm and appear red. Moderately intense or large fires will be detected at both 3.7 μm and 2.25 μm and will appear orange to yellow (yellow being more intense). Very intense fires will be detected by all three bands and appear white.
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GOES West Scene Fire Detections - Mesoscale1
[NGFS-SCENE-Mesoscale1-WEST]
Near real-time pixel-level thermal anomaly detections from the Mesoscale-1scan of ABI on GOES West. Pixel corner point locations are terrain corrected. These update every minute.
Near real-time pixel-level thermal anomaly detections from the Mesoscale-1 scan of ABI on GOES West. Pixel corner point locations are terrain corrected. These update every minute.
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GOES West ABI Meso1 B02 Hi-Res "Red" Visible
[G18-ABI-MESO1-BAND02]
he ‘Red’ Visible band – 0.64 µm – has the
finest spatialresolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air...
he ‘Red’ Visible band – 0.64 µm – has the
finest spatial resolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air boundaries, or overshooting tops or cumulus clouds. It has also been used to document daytime snow and ice cover, diagnose low-level cloud-drift winds, assist with detection of volcanic ash and analysis of hurricanes and winter storms. The ‘Red’ Visible band is also essential for creation of “true color” imagery.
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GOES West ABI Meso1 B03 "Veggie"
[G18-ABI-MESO1-BAND03]
The 0.86 μm band (a reflective band) detects daytime clouds, fog, andaerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86...
The 0.86 μm band (a reflective band) detects daytime clouds, fog, and aerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86 μm band can detect burn scars and thereby show land characteristics to determine fire and run-off potential. Vegetated land, in general, shows up brighter in this band than in visible bands. Landwater contrast is also large in this band.
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GOES West ABI Meso1 B07 "Fire"
[G18-ABI-MESO1-BAND07]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES West ABI Meso1 B07 "Fire" enhanced
[G18-ABI-MESO1-BAND07-FIRE]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES West ABI Meso1 B09 Mid-level Water Vapor
[G18-ABI-MESO1-BAND09]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level moisture (for legacy vertical moisture profiles)
and identifying regions where turbulence might exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9 µm by water vapor.
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GOES West ABI Meso1 B09 Mid-level Water Vapor enhanced
[G18-ABI-MESO1-BAND09-VAPR]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level moisture (for legacy vertical moisture profiles) and identifying regions where turbulence might
exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9 µm by water vapor.
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GOES West ABI Meso1 B13 "Clean" Infrared
[G18-ABI-MESO1-BAND13]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES West ABI Meso1 B13 "Clean" infrared enhanced
[G18-ABI-MESO1-BAND13-GRAD]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES West ABI Meso1 B13 "Clean" Infrared green
[G18-ABI-MESO1-BAND13-GREEN]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES West Day Fire RGB - Meso2 - CIRA
[goes-west-meso2-day-fire-rgb]
This product is uploaded directly to RealEarth every minute by CIRA. Moreinfo to follow.
This product is uploaded directly to RealEarth every minute by CIRA. More info to follow.
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GOES West Fire Temp RGB - Meso2 - CIRA
[goes-west-meso2-fire-temp-rgb]
This product is uploaded directly to RealEarth every minute by CIRA. TheFire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more...
This product is uploaded directly to RealEarth every minute by CIRA. The Fire Temp is useful for fire detection and provides a qualitative estimate of fire activity and intensity. It takes advantage of the fact that more intense fires emit more radiation at shorter wavelengths in the shortwave IR. Small or "cool" fires will only show up at 3.7 μm and appear red. Moderately intense or large fires will be detected at both 3.7 μm and 2.25 μm and will appear orange to yellow (yellow being more intense). Very intense fires will be detected by all three bands and appear white.
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GOES West Scene Fire Detections - Mesoscale2
[NGFS-SCENE-Mesoscale2-WEST]
Near real-time pixel-level thermal anomaly detections from the Mesoscale-2scan of ABI on GOES West. Pixel corner point locations are terrain corrected. These update every minute.
Near real-time pixel-level thermal anomaly detections from the Mesoscale-2 scan of ABI on GOES West. Pixel corner point locations are terrain corrected. These update every minute.
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GOES West ABI Meso2 B02 Hi-Res "Red" Visible
[G18-ABI-MESO2-BAND02]
he ‘Red’ Visible band – 0.64 µm – has the
finest spatialresolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air...
he ‘Red’ Visible band – 0.64 µm – has the
finest spatial resolution (0.5 km at the subsatellite point) of all ABI bands. Thus it is ideal to identify small-scale features such as river fogs and fog/clear air boundaries, or overshooting tops or cumulus clouds. It has also been used to document daytime snow and ice cover, diagnose low-level cloud-drift winds, assist with detection of volcanic ash and analysis of hurricanes and winter storms. The ‘Red’ Visible band is also essential for creation of “true color” imagery.
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GOES West ABI Meso2 B03 "Veggie"
[G18-ABI-MESO2-BAND03]
The 0.86 μm band (a reflective band) detects daytime clouds, fog, andaerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86...
The 0.86 μm band (a reflective band) detects daytime clouds, fog, and aerosols and is used to compute the normalized difference vegetation index (NDVI). Its nickname is the “veggie” or “vegetation” band. The 0.86 μm band can detect burn scars and thereby show land characteristics to determine fire and run-off potential. Vegetated land, in general, shows up brighter in this band than in visible bands. Landwater contrast is also large in this band.
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GOES West ABI Meso2 B07 "Fire"
[G18-ABI-MESO2-BAND07]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES West ABI Meso2 B07 "Fire" enhanced
[G18-ABI-MESO2-BAND07-FIRE]
The 3.9 μm band can be used to identify fog and low clouds at night,identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day....
The 3.9 μm band can be used to identify fog and low clouds at night, identify fire hot spots, detect volcanic ash, estimate sea-surface temperatures, and discriminate between ice crystal sizes during the day. Low-level atmospheric vector winds can be estimated with this band, and the band can be used to study urban heat islands. The 3.9 μm is unique among ABI bands because it senses both emitted terrestrial radiation as well as significant reflected solar radiation during the day.
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GOES West ABI Meso2 B09 Mid-level Water Vapor
[G18-ABI-MESO2-BAND09]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level moisture (for legacy vertical moisture profiles) and identifying regions where turbulence might
exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9 µm by water vapor.
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GOES West ABI Meso2 B09 Mid-level Water Vapor enhanced
[G18-ABI-MESO2-BAND09-VAPR]
The 6.9 µm “Mid-level water vapor” band is one of three water vaporbands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm...
The 6.9 µm “Mid-level water vapor” band is one of three water vapor bands on the ABI, and is used for tracking middle-tropospheric winds, identifying jet streams, forecasting hurricane track and mid-latitude storm motion, monitoring severe weather potential, estimating mid-level moisture (for legacy vertical moisture profiles)
and identifying regions where turbulence might exist. Surface features are usually not apparent in this band. Brightness Temperatures show cooling because of absorption of energy at 6.9 µm by water vapor.
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GOES West ABI Meso2 B13 "Clean" Infrared
[G18-ABI-MESO2-BAND13]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES West ABI Meso2 B13 "Clean" Infrared enhanced
[G18-ABI-MESO2-BAND13-GRAD]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES West ABI Meso2 B13 "Clean" Infrared yellow
[G18-ABI-MESO2-BAND13-YELLOW]
The 10.3 μm “clean” infrared window band is less sensitive than otherinfrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric...
The 10.3 μm “clean” infrared window band is less sensitive than other infrared window bands to water vapor absorption, and therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification, estimation of cloudtop brightness temperature and cloud particle size, and surface property characterization in derived products.
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GOES CAPE
[cimssdpicapeli]
CIMSS-DPI Convective Available Potential Energy (Li et al. 2008)
CIMSS-DPI Convective Available Potential Energy (Li et al. 2008)
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GOES Lifted Index
[cimssdpilili]
GOES-DPI Lifted Index (Li et al. 2008)
GOES-DPI Lifted Index (Li et al. 2008)
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GOES Precipitable Water
[cimssdpipwli]
CIMSS-DPI Precipitable Water (mm)
CIMSS-DPI Precipitable Water (mm)
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Hydro Estimator Rainfall
[NESDIS-GHE-HourlyRainfall]
The HE algorithm uses infrared (IR) brightness temperatures to identifyregions of rainfall and retrieve rainfall rate, while using National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS)...
The HE algorithm uses infrared (IR) brightness temperatures to identify regions of rainfall and retrieve rainfall rate, while using National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model fields to account for the effects of moisture availability, evaporation, orographic modulation, and thermodynamic profile effects. Estimates of rainfall from satellites can provide critical rainfall information in regions where data from gauges or radar are unavailable or unreliable, such as over oceans or sparsely populated regions.
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IR Winds 250-100mb
[AMV-ULhigh]
AMV: Upper Level IR/WV (100-250mb)
AMV: Upper Level IR/WV (100-250mb)
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IR Winds 350-251mb
[AMV-ULmid]
AMV: Upper Level IR/WV (251-350mb)
AMV: Upper Level IR/WV (251-350mb)
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IR Winds 500-351mb
[AMV-ULlow]
AMV: Upper Level IR/WV (351-500mb)
AMV: Upper Level IR/WV (351-500mb)
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Vis Winds 800-700mb
[AMV-VISmid]
AMV: Middle Level Visible (700-800mb)
AMV: Middle Level Visible (700-800mb)
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Vis Winds 925-801mb
[AMV-VISlow]
AMV: Lower Level Visible (801-925mb)
AMV: Lower Level Visible (801-925mb)
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Hydro Estimator Rainfall
[NESDIS-GHE-HourlyRainfall]
The HE algorithm uses infrared (IR) brightness temperatures to identifyregions of rainfall and retrieve rainfall rate, while using National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS)...
The HE algorithm uses infrared (IR) brightness temperatures to identify regions of rainfall and retrieve rainfall rate, while using National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model fields to account for the effects of moisture availability, evaporation, orographic modulation, and thermodynamic profile effects. Estimates of rainfall from satellites can provide critical rainfall information in regions where data from gauges or radar are unavailable or unreliable, such as over oceans or sparsely populated regions.
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IR Winds 250-100mb
[AMV-ULhigh]
AMV: Upper Level IR/WV (100-250mb)
AMV: Upper Level IR/WV (100-250mb)
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IR Winds 350-251mb
[AMV-ULmid]
AMV: Upper Level IR/WV (251-350mb)
AMV: Upper Level IR/WV (251-350mb)
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IR Winds 500-351mb
[AMV-ULlow]
AMV: Upper Level IR/WV (351-500mb)
AMV: Upper Level IR/WV (351-500mb)
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Sea Surface Temperature
[NESDIS-SST]
NESDIS: Hi-Res Sea Surface Temperature
NESDIS: Hi-Res Sea Surface Temperature
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Vis Winds 800-700mb
[AMV-VISmid]
AMV: Middle Level Visible (700-800mb)
AMV: Middle Level Visible (700-800mb)
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Vis Winds 925-801mb
[AMV-VISlow]
AMV: Lower Level Visible (801-925mb)
AMV: Lower Level Visible (801-925mb)
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Global Infrared
[globalir]
This product is a global composite of imagery from multiple satellites. Itis completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most...
This product is a global composite of imagery from multiple satellites. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most current imagery, shifting occurs along composite seams.
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Global Infrared - Aviation
[globalir-avn]
This product is an enhanced view of the global infrared composite product.It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most...
This product is an enhanced view of the global infrared composite product. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most current imagery, shifting occurs along composite seams.
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Global Infrared - Dvorak
[globalir-bd]
This product is an enhanced view of the global infrared composite product.It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most...
This product is an enhanced view of the global infrared composite product. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most current imagery, shifting occurs along composite seams.
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Global Infrared - Funk Top
[globalir-funk]
This product is an enhanced view of the global infrared composite product.It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most...
This product is an enhanced view of the global infrared composite product. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most current imagery, shifting occurs along composite seams.
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Global Infrared - Rainbow
[globalir-nhc]
This product is an enhanced view of the global infrared composite product.It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most...
This product is an enhanced view of the global infrared composite product. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most current imagery, shifting occurs along composite seams.
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Global Infrared - Rain Rate
[globalir-rr]
This product is based on a statistical relationship between cloud toptemperature and observed rain rate. It is derived every hour (at about 35-minutes after the hour UTC) using the global IR composite produced by...
This product is based on a statistical relationship between cloud top temperature and observed rain rate. It is derived every hour (at about 35-minutes after the hour UTC) using the global IR composite produced by the SSEC Data Center. While it shows the most current imagery, shifting occurs along composite seams.
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Global Infrared - Tops
[globalir-ott]
This product is an enhanced view of the global infrared composite product.It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most...
This product is an enhanced view of the global infrared composite product. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most current imagery, shifting occurs along composite seams.
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Global Visible
[globalvis]
This product is a global composite of imagery from multiple satellites. Itis completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most...
This product is a global composite of imagery from multiple satellites. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most current imagery, shifting occurs along composite seams.
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Global Visible (transparent Night)
[globalvis-tsp]
This view is based on the global Visible composite product in which nighttime regions are rendered transparent. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best...
This view is based on the global Visible composite product in which night time regions are rendered transparent. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most current imagery, shifting occurs along composite seams.
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Global Visible - fill
[global1kmvis]
This product is a 15-minute snapshot of a global composite of imagery frommultiple satellites. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery....
This product is a 15-minute snapshot of a global composite of imagery from multiple satellites. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most current imagery, shifting occurs along composite seams.
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Global Water Vapor
[globalwv]
This product is a global composite of imagery from multiple satellites. Itis completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most...
This product is a global composite of imagery from multiple satellites. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most current imagery, shifting occurs along composite seams.
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Global Water Vapor - Gradient
[globalwv-grad]
This product is an enhanced view of the global Water Vapor compositeproduct. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it...
This product is an enhanced view of the global Water Vapor composite product. It is completed every hour (at about 35-minutes after the hour UTC) by the SSEC Data Center with the best available imagery. While it shows the most current imagery, shifting occurs along composite seams.
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Cladophora Classification
[clad]
Estimate of 2005 algae extent along coastal Lake Michigan.
Estimate of 2005 algae extent along coastal Lake Michigan.
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Great Lakes Ice Type Classification (ICECON)
[GLERL-ICE]
Ice formations can be an obstacle for U.S. Coast Guard, commercial, andfishing boats. In order to understand ice formations and types of ice in the Great Lakes, Synthetic Aperture Radar (SAR) data from the NOAA...
Ice formations can be an obstacle for U.S. Coast Guard, commercial, and fishing boats. In order to understand ice formations and types of ice in the Great Lakes, Synthetic Aperture Radar (SAR) data from the NOAA CoastWatch Great Lakes Node is used to monitor six different types of ice, ice thickness, and ice cover. This risk assessment tool is known as the Ice Condition Index (ICECON).
The categories are as follows:
0 - Blue - Calm Water
1 - Green - New Lake Ice
2 - Yellow - Pancake Ice
3-4 - Orange - Consolidated Flows - Snow/SnowIce/LakeIce
5 - Red - Brash
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Great Lakes Surface Environmental Analysis
[GLERL-GLSEAimage]
Great Lakes Surface Environmental Analysis (GLSEA) from GLERL. For moreinfo see: http://coastwatch.glerl.noaa.gov/glsea/doc
Great Lakes Surface Environmental Analysis (GLSEA) from GLERL. For more info see:
http://coastwatch.glerl.noaa.gov/glsea/doc
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WI Coastal Imagery
[WICoast]
WI Coastal Imagery displays aerial photographs of the Lake Michigan coastof Wisconsin from 2007. The images are being used to monitor cladophora algae growth.
WI Coastal Imagery displays aerial photographs of the Lake Michigan coast of Wisconsin from 2007. The images are being used to monitor cladophora algae growth.
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WI Coastal Shaded Relief
[WIcoastalshdrlf]
WI coastal shaded relief map generated from LiDAR data.
WI coastal shaded relief map generated from LiDAR data.
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Earthquake Magnitude
[Earthquake-mag]
Earthquake Magnitude (Past 24hr)
Earthquake Magnitude (Past 24hr)
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Fire Hazards (Valid)
[XREDFLAG]
The National Weather Service issues a variety of Weather warnings, watchesand advisories. The event type is indicated on the map by different colors. This product contains Wildland Fire Weather Hazards VALID for a 48hr Window...
The National Weather Service issues a variety of Weather warnings, watches and advisories. The event type is indicated on the map by different colors. This product contains Wildland Fire Weather Hazards VALID for a 48hr Window spanning from the previous 24hrs to 24hrs in the future at 1hr increments
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Flood Warnings Hydrological-VTEC (Issued)
[HVTEC]
For Flood Warnings (FLW) and follow up Flood Statements (FLS) at specificriver forecast points, the H-VTEC specifies the flood severity; immediate cause, timing of flood beginning, crest, and end; and how the flood...
For Flood Warnings (FLW) and follow up Flood Statements (FLS) at specific river forecast points, the H-VTEC specifies the flood severity; immediate cause,
timing of flood beginning, crest, and end; and how the flood compares to the flood of record.
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Severe Weather Warnings
[Severe]
Tornado, Thunderstorm, Flash Flood and Marine Warning polygons.
Tornado, Thunderstorm, Flash Flood and Marine Warning polygons.
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Severe Weather Watch Box
[SAW]
Severe Weather Watch Box - Aviation
Severe Weather Watch Box - Aviation
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Tropical Storm & Hurricane Forecast
[TSFCST]
National Hurricane Center Tropical Storm & Hurricane Forecast
National Hurricane Center Tropical Storm & Hurricane Forecast
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Volcanic Ash Adv plumes
[VAA]
Volcanic Ash Advisories: Ash Clouds
Volcanic Ash Advisories: Ash Clouds
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Wind Hazards
[WWIND]
Wind Hazards is a collection of alerts associated with all types of Windrelated events. These Hazards are issued by the NWS WSFOs as Advisories, Watches and Warnings. WindEvents include Wind, LakeWind and HighWind...
Wind Hazards is a collection of alerts associated with all types of Wind related events. These Hazards are issued by the NWS WSFOs as Advisories, Watches and Warnings. WindEvents include Wind, LakeWind and HighWind categories. Click on objects to get a detailed description of the specific hazard.
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Winter Weather Hazards (Issued)
[WWINTER]
Winter Weather is a collection of Hazards associated with all types ofWinter precip and conditions. Hazards are issued by the NWS WSFOs as Advisories, Watches and Warnings. SnowEvents include SnowStorm,...
Winter Weather is a collection of Hazards associated with all types of Winter precip and conditions. Hazards are issued by the NWS WSFOs as Advisories, Watches and Warnings. SnowEvents include SnowStorm, WinterStorm, Snow, HeavySnow, LakeEffectSnow and BlowingSnow. IceEvents include Sleet, HeavySleet, FreezingRain, IceStorm and FreezingFog. Click on objects to get a detailed description of the specific hazard.
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Winter Weather Hazards (Valid)
[XWINTER]
The National Weather Service issues a variety of Winter Weather warnings,watches and advisories. The event type is indicated on the map by different colors. This product contains Winter Weather Hazards VALID for a 48hr...
The National Weather Service issues a variety of Winter Weather warnings, watches and advisories. The event type is indicated on the map by different colors. This product contains Winter Weather Hazards VALID for a 48hr Window spanning from the previous 24hrs to 24hrs in the future at 1hr increments.
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RIVER-ICE-CONCENTRATION: Missouri Basin
[RVER-ICEC-MB]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice...
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice concentration. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Missouri Basin (product off-line in summer)
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River-ICE-CONCENTRATION: North Central Basin
[RVER-ICEC-NC]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice...
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice concentration. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, North Central Basin (product off-line in summer)
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River-ICE-CONCENTRATION: North East Basin
[RVER-ICEC-NE]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice...
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice concentration. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, North East Basin (product off-line in summer)
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River Flood: 1 day VIIRS composite
[RIVER-FLDglobal-composite1]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available VIIRS daylight imagery over the past 1 day.
For more information visit: Here
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River Flood: 5 day VIIRS composite
[RIVER-FLDglobal-composite]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available VIIRS daylight imagery over the past 5 days.
For more information visit: Here
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River Flood: Alaska
[RIVER-FLDall-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region
Quick guide
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River Flood: Alaska (transparent)
[RIVER-FLDtsp-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region(Transparent flood-free land)
Quick guide
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River Flood: Global
[RIVER-FLDglobal]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Global(CSPP product)
Quick guide
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River Flood: Joint ABI/VIIRS
[RIVER-FLD-joint-ABI]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available ABI-full disk imagery and VIIRS imagery since sunrise on the given day.
For more information visit: Here
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River Flood: Missouri Basin
[RIVER-FLDall-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin
Quick guide
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River Flood: Missouri Basin (transparent)
[RIVER-FLDtsp-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin(Transparent flood-free land)
Quick guide
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River Flood: North Central Basin
[RIVER-FLDall-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin
Quick guide
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River Flood: North Central Basin (transparent)
[RIVER-FLDtsp-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin(Transparent flood-free land)
Quick guide
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River Flood: North East Basin
[RIVER-FLDall-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin
Quick guide
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River Flood: North East Basin (transparent)
[RIVER-FLDtsp-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin(Transparent flood-free land)
Quick guide
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River Flood: North West
[RIVER-FLDall-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region
Quick guide
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River Flood: North West (transparent)
[RIVER-FLDtsp-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region(Transparent flood-free land)
Quick guide
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River Flood: South East
[RIVER-FLDall-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region
Quick guide
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River Flood: South East (transparent)
[RIVER-FLDtsp-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region(Transparent flood-free land)
Quick guide
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River Flood: South West
[RIVER-FLDall-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region
Quick guide
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River Flood: South West (tsp)
[RIVER-FLDtsp-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region(Transparent flood-free land)
Quick guide
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River Flood: US
[RIVER-FLDall-US]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
US
Quick guide
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River Flood: US (transparent)
[RIVER-FLDtsp-US]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
US(Transparent flood-free land)
Quick guide
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River Flood: West Gulf Basin
[RIVER-FLDall-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin
Quick guide
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River Flood: West Gulf Basin (transparent)
[RIVER-FLDtsp-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin(Transparent flood-free land)
Quick guide
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River Ice: Alaska
[RIVER-ICE-AP]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Alaska
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River Ice: Missouri Basin
[RIVER-ICE-MB]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Missouri Basin (product off-line in summer)
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River Ice: North Central Basin
[RIVER-ICE-NC]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, North Central Basin (product off-line in summer)
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River Ice: North East Basin
[RIVER-ICE-NE]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Northeast Basin (product off-line in summer)
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Infrared 6 inch Imagery of Madison
[madisonir]
Infrared 6 inch Imagery of Madison
Infrared 6 inch Imagery of Madison
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NAIP WI
[NAIPWI]
National Agricultural Imagery Program aerial photography from the WisconsinFarm Service Agency (WI-FSA) of the USDA.
National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA.
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NAIP WI Color Infrared
[NAIPWICIR]
National Agricultural Imagery Program aerial photography from the WisconsinFarm Service Agency (WI-FSA) of the USDA (Color Infrared)
National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA (Color Infrared)
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WI Coastal Shaded Relief
[WIcoastalshdrlf]
WI coastal shaded relief map generated from LiDAR data.
WI coastal shaded relief map generated from LiDAR data.
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Wisconsin LIDAR Hillshade
[wi-hillshade]
WisconsinView is a remote sensing consortium and member of AmericaView.org.These Wisconsin lidar data sets were collected by aircraft and processed by state and county agencies. These data are hosted by WisconsinView and...
WisconsinView is a remote sensing consortium and member of AmericaView.org. These Wisconsin lidar data sets were collected by aircraft and processed by state and county agencies. These data are hosted by WisconsinView and visualized here with coordination and funding from the WI State Dept. of Administration, Geographic Information Office and NOAA"s coastal management program.
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WI USGS Landsat Poster
[wilandsat]
This is a georeferenced poster from the USGS. The original source is:http://eros.usgs.gov/imagegallery/landsat-state-mosaics unfortunately the original poster imagery without graphics burned-in is not available.
This is a georeferenced poster from the USGS. The original source is: http://eros.usgs.gov/imagegallery/landsat-state-mosaics unfortunately the original poster imagery without graphics burned-in is not available.
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Himawari AHI Full Disk B03 Hi-Res "Red" Visible
[HIMAWARI-B03]
Himawari AHI Full Disk B03 Hi-Res "Red" Visible
Himawari AHI Full Disk B03 Hi-Res "Red" Visible
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Himawari AHI Full Disk B04 "Veggie"
[HIMAWARI-B04]
Himawari AHI Full Disk B04 "Veggie"
Himawari AHI Full Disk B04 "Veggie"
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Himawari AHI Full Disk B07 "Fire"
[HIMAWARI-B07]
Himawari AHI Full Disk B07 "Fire"
Himawari AHI Full Disk B07 "Fire"
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Himawari AHI Full Disk B07 "Fire" enhanced
[HIMAWARI-B07-FIRE]
View of HIMAWARI-B07
View of HIMAWARI-B07
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Himawari AHI Full Disk B09 Mid-level Water Vapor
[HIMAWARI-B09]
Himawari AHI Full Disk B09 Mid-level Water Vapor
Himawari AHI Full Disk B09 Mid-level Water Vapor
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Himawari AHI Full Disk B09 Mid-level Water Vapor enhanced
[HIMAWARI-B09-VAPR]
View of HIMAWARI-09
View of HIMAWARI-09
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Himawari AHI Full Disk B13 "Clean" Infrared
[HIMAWARI-B13]
Himawari AHI Full Disk B13 "Clean" Infrared
Himawari AHI Full Disk B13 "Clean" Infrared
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Himawari AHI Full Disk B13 "Clean" Infrared enhanced
[HIMAWARI-B13-GRAD]
View of HIMAWARI-B13
View of HIMAWARI-B13
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Himawari AHI Full Disk Day Convective Storm (ave)
[H-DayConvectiveStorm-cve]
Himawari AHI Full Disk Day Convective Storm (ave)
Himawari AHI Full Disk Day Convective Storm (ave)
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Himawari AHI Full Disk Day Microphysics (dms)
[H-DayMicrophysics-dms]
Himawari AHI Full Disk Day Microphysics (dms)
Himawari AHI Full Disk Day Microphysics (dms)
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Himawari AHI Full Disk Dust (dst)
[H-Dust-dst]
Himawari AHI Full Disk Dust (dst)
Himawari AHI Full Disk Dust (dst)
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Himawari AHI Full Disk Natural Color (dnc)
[H-NaturalColor-dnc]
Himawari AHI Full Disk Natural Color (dnc)
Himawari AHI Full Disk Natural Color (dnc)
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Himawari AHI Full Disk Night Microphysics (nms)
[H-NightMicrophysics-ngt]
Himawari AHI Full Disk Night Microphysics (nms)
Himawari AHI Full Disk Night Microphysics (nms)
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Himawari AHI Full Disk RGB Air Mass (arm)
[H-24hrAirMass-arm]
The Air Mass RGB is used to diagnose the environment
surrounding synopticsystems by enhancing temperature and moisture characteristics of air masses. Cyclogenesis can be inferred by the identification of warm, dry,...
The Air Mass RGB is used to diagnose the environment
surrounding synoptic systems by enhancing temperature and moisture characteristics of air masses.
Cyclogenesis can be inferred by the identification of
warm, dry, ozone-rich descending stratospheric air
associated with jet streams and potential vorticity (PV)
anomalies. The RGB can be used to validate the location of PV anomalies in model data. Additionally,
this RGB can distinguish between polar and tropical
air masses, especially along frontal boundaries and
identify high-, mid-, and low- level clouds.
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Himawari AHI Full Disk Snow and Fog (dsl)
[H-SnowFog-dsl]
Himawari AHI Full Disk Snow and Fog (dsl)
Himawari AHI Full Disk Snow and Fog (dsl)
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Himawari AHI Full Disk True Color (wgt)
[H-TrueColor-wgt]
Himawari AHI Full Disk True Color (wgt)
Himawari AHI Full Disk True Color (wgt)
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Himawari AHI Japan B03 Hi-Res "Red" Visible
[HIMAWARI-JP-B03]
Himawari AHI Japan B03 Hi-Res "Red" Visible
Himawari AHI Japan B03 Hi-Res "Red" Visible
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Himawari AHI Japan B07 "Fire"
[HIMAWARI-JP-B07]
Himawari AHI Japan Bo7 "Fire"
Himawari AHI Japan Bo7 "Fire"
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Himawari AHI Japan B07 "Fire" enhanced
[HIMAWARI-JP-B07-FIRE]
View of HIMAWARI-JP-B07
View of HIMAWARI-JP-B07
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Himawari AHI Japan B09 Mid-level Water Vapor
[HIMAWARI-JP-B09]
Himawari AHI Japan B09 Mid-level Water Vapor
Himawari AHI Japan B09 Mid-level Water Vapor
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Himawari AHI Japan B09 Mid-level Water Vapor enhanced
[HIMAWARI-JP-B09-VAPR]
View of HIMAWARI-JP-B09
View of HIMAWARI-JP-B09
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Himawari AHI Japan B14 Infrared
[HIMAWARI-JP-B14]
Himawari AHI Japan B14 Infrared
Himawari AHI Japan B14 Infrared
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Himawari AHI Japan B14 Infrared enhanced
[HIMAWARI-JP-B14-GRAD]
View of HIMAWARI-JP-B14
View of HIMAWARI-JP-B14
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Himawari AHI Target B03 Hi-Res "Red" Visible
[HIMAWARI-T1-B03]
Himawrai AHI Target B03 Hi-Res "Red" Visible
Himawrai AHI Target B03 Hi-Res "Red" Visible
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Himawari AHI Target B07 "Fire"
[HIMAWARI-T1-B07]
Himawari AHI Target B07 "Fire"
Himawari AHI Target B07 "Fire"
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Himawari AHI Target B07 enhanced
[HIMAWARI-T1-B07-FIRE]
View of HIMAWARI-T1-B07
View of HIMAWARI-T1-B07
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Himawari AHI Target B14 Infrared
[HIMAWARI-T1-B14]
Himawari AHI Target B14 Infrared
Himawari AHI Target B14 Infrared
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Himawari AHI Target B14 Infrared enhanced
[HIMAWARI-T1-B14-GRAD]
Himawari AHI Target B14 Infrared enhanced
Himawari AHI Target B14 Infrared enhanced
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Himawari AHI Target Mid-level Water Vapor
[HIMAWARI-T1-B09]
Himawari AHI Target Mid-level Water Vapor
Himawari AHI Target Mid-level Water Vapor
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Himawari AHI Target Mid-level Water Vapor enhanced
[HIMAWARI-T1-B09-VAPR]
Himawari AHI Target Mid-level Water Vapor enhanced
Himawari AHI Target Mid-level Water Vapor enhanced
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River Flood: Global
[RIVER-FLDglobal]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Global(CSPP product)
Quick guide
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VIIRS Floodwater Depth
[VIIRS-3Dflood]
VIIRS downscaling software is designed to downscale the VIIRS 375-m floodproducts to 30-m flood products. The software uses Suomi-NPP
VIIRS downscaling software is designed to downscale the VIIRS 375-m flood products to 30-m flood products. The software uses Suomi-NPP
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RIVER-ICE-CONCENTRATION: Missouri Basin
[RVER-ICEC-MB]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice...
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice concentration. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Missouri Basin (product off-line in summer)
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River-ICE-CONCENTRATION: North Central Basin
[RVER-ICEC-NC]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice...
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice concentration. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, North Central Basin (product off-line in summer)
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River-ICE-CONCENTRATION: North East Basin
[RVER-ICEC-NE]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice...
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice concentration. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, North East Basin (product off-line in summer)
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River Flood: 1 day VIIRS composite
[RIVER-FLDglobal-composite1]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available VIIRS daylight imagery over the past 1 day.
For more information visit: Here
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River Flood: 5 day VIIRS composite
[RIVER-FLDglobal-composite]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available VIIRS daylight imagery over the past 5 days.
For more information visit: Here
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River Flood: ABI-daily
[River-Flood-ABI]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available 5-min CONUS imagery since sunrise on the given day. These products are expected to be most useful in mid- and low-latitude locations.
CONUS region
Quick guide
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River Flood: ABI-daily (tsp)
[River-Flood-ABItsp]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available 5-min CONUS imagery since sunrize through the given hour. These products are expected to be most useful in mid- and low-latitude locations.
CONUS region
Quick guide
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River Flood: ABI-hourly
[River-Flood-ABI-hourly]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available 5-min CONUS imagery since sunrize through the given hour. These products are expected to be most useful in mid- and low-latitude locations.
CONUS region
Quick guide
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River Flood: ABI-hourly (tsp)
[River-Flood-ABItsp-hourly]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available 5-min CONUS imagery since sunrize through the given hour. These products are expected to be most useful in mid- and low-latitude locations.
CONUS region
Quick guide
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River Flood: AHI
[RIVER-FLD-AHI]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available 10-min imagery since sunrise on the given day. These products are expected to be most useful in mid- and low-latitude locations.
For more information visit: Here
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River Flood: Alaska
[RIVER-FLDall-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region
Quick guide
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River Flood: Alaska (transparent)
[RIVER-FLDtsp-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region(Transparent flood-free land)
Quick guide
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River Flood: Joint ABI/VIIRS
[RIVER-FLD-joint-ABI]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available ABI-full disk imagery and VIIRS imagery since sunrise on the given day.
For more information visit: Here
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River Flood: Joint AHI/VIIRS
[RIVER-FLD-joint-AHI]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud,...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS, adapted to the GOES-ABI and Himawari -AHI. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. These products represent a composite of all available AHI-full disk imagery and VIIRS imagery since sunrise on the given day.
For more information visit: Here
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River Flood: Missouri Basin
[RIVER-FLDall-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin
Quick guide
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River Flood: Missouri Basin (transparent)
[RIVER-FLDtsp-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin(Transparent flood-free land)
Quick guide
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River Flood: North Central Basin
[RIVER-FLDall-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin
Quick guide
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River Flood: North Central Basin (transparent)
[RIVER-FLDtsp-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin(Transparent flood-free land)
Quick guide
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River Flood: North East Basin
[RIVER-FLDall-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin
Quick guide
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River Flood: North East Basin (transparent)
[RIVER-FLDtsp-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin(Transparent flood-free land)
Quick guide
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River Flood: North West
[RIVER-FLDall-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region
Quick guide
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River Flood: North West (transparent)
[RIVER-FLDtsp-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region(Transparent flood-free land)
Quick guide
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River Flood: South East
[RIVER-FLDall-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region
Quick guide
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River Flood: South East (transparent)
[RIVER-FLDtsp-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region(Transparent flood-free land)
Quick guide
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River Flood: South West
[RIVER-FLDall-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region
Quick guide
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River Flood: South West (tsp)
[RIVER-FLDtsp-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region(Transparent flood-free land)
Quick guide
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River Flood: US
[RIVER-FLDall-US]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
US
Quick guide
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River Flood: US (transparent)
[RIVER-FLDtsp-US]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
US(Transparent flood-free land)
Quick guide
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River Flood: West Gulf Basin
[RIVER-FLDall-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin
Quick guide
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River Flood: West Gulf Basin (transparent)
[RIVER-FLDtsp-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin(Transparent flood-free land)
Quick guide
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River Ice: Alaska
[RIVER-ICE-AP]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Alaska
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River Ice: Missouri Basin
[RIVER-ICE-MB]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Missouri Basin (product off-line in summer)
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River Ice: North Central Basin
[RIVER-ICE-NC]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, North Central Basin (product off-line in summer)
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River Ice: North East Basin
[RIVER-ICE-NE]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Northeast Basin (product off-line in summer)
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MADIS Surface DewPoint
[MADIS-dewt]
The MADIS Surface Dewpoint uses a 2-dimensional boxcar spatial convolutionto smooth hourly average surface observations from the NCEP Meteorological Assimilation Data Ingest System (MADIS) to a grid resolution of 0.7 degree...
The MADIS Surface Dewpoint uses a 2-dimensional boxcar spatial convolution to smooth hourly average surface observations from the NCEP Meteorological Assimilation Data Ingest System (MADIS) to a grid resolution of 0.7 degree latitude/longitude. The source data is obtained in near-real time from https://madis.ncep.noaa.gov/.
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MIRS 90Ghz Brightness Temperature
[MIRS-BT90]
MIRS 90Ghz Brightness Temperature
MIRS 90Ghz Brightness Temperature
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MIRS Rain Rate
[MIRS-RainRate]
With inputs from the ATMS (Advanced Technology Microwave Sounder) sensoraboard JPSS satellites, the rainfall rate product from the Microwave Integrated Retrieval System (MIRS) identifies the intensity of rain at the...
With inputs from the ATMS (Advanced Technology Microwave Sounder) sensor aboard JPSS satellites, the rainfall rate product from the Microwave Integrated Retrieval System (MIRS) identifies the intensity of rain at the instant the satellite is passing over the area. It is derived from three vertically integrated MIRS products: Cloud Liquid Water (CLW), Rain Water Path (RWP), and Ice Water Path (IWP), taking advantage of the physical relationship found between atmospheric hydrometeor amounts and surface rain rate.
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SNPP Day/Night AM Composite - Adaptive
[nppadpam]
NPP Day/Night AM Composite - Adaptive
NPP Day/Night AM Composite - Adaptive
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SNPP Day/Night Band (DNB) - Honolulu DB
[nppdnbdyn-hnl]
NPP Day/Night Band (DNB) - Honolulu DB
NPP Day/Night Band (DNB) - Honolulu DB
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Aqua Aerosol Optical Depth
[AQUA-AER]
MODIS: AQUA Aerosol Optical Depth (ta)
MODIS: AQUA Aerosol Optical Depth (ta)
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Aqua False Color
[aquafalsecolor]
CIMSS-MODIS Satellite False Color (Aqua)
CIMSS-MODIS Satellite False Color (Aqua)
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Global Black Marble
[VIIRS-MASK-54000x27000]
VIIRS Night Global Black Marble by NASA
VIIRS Night Global Black Marble by NASA
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Global Night Lights
[NightLightsColored]
Global Night Lights (enhanced)
Global Night Lights (enhanced)
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Terra Aerosol Optical Depth
[TERRA-AER]
MODIS: TERRA Aerosol Optical Depth (ta)
MODIS: TERRA Aerosol Optical Depth (ta)
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Terra False Color
[terrafalsecolor]
CIMSS-MODIS Satellite False Color (Terra)
CIMSS-MODIS Satellite False Color (Terra)
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Terra True Color
[terratruecolor]
CIMSS-MODIS Satellite True Color (Terra)
CIMSS-MODIS Satellite True Color (Terra)
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Total Column Sulphur Dioxide
[AURA-SO2]
AURA - OMI Total Column Sulphur Dioxide (SO2)
AURA - OMI Total Column Sulphur Dioxide (SO2)
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True Color Clear View
[BRDF]
MODIS Clear View ConUS Composite. BRDF (Bidirectional ReluctanceDistribution Function) is a 16-day cloud-free composite.
MODIS Clear View ConUS Composite. BRDF (Bidirectional Reluctance Distribution Function) is a 16-day cloud-free composite.
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RIVER-ICE-CONCENTRATION: Missouri Basin
[RVER-ICEC-MB]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice...
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice concentration. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Missouri Basin (product off-line in summer)
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River-ICE-CONCENTRATION: North Central Basin
[RVER-ICEC-NC]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice...
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice concentration. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, North Central Basin (product off-line in summer)
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River-ICE-CONCENTRATION: North East Basin
[RVER-ICEC-NE]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice...
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice concentration. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, North East Basin (product off-line in summer)
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River Flood: Alaska
[RIVER-FLDall-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region
Quick guide
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River Flood: Alaska (transparent)
[RIVER-FLDtsp-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region(Transparent flood-free land)
Quick guide
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River Flood: Missouri Basin
[RIVER-FLDall-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin
Quick guide
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River Flood: Missouri Basin (transparent)
[RIVER-FLDtsp-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin(Transparent flood-free land)
Quick guide
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River Flood: North Central Basin
[RIVER-FLDall-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin
Quick guide
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River Flood: North Central Basin (transparent)
[RIVER-FLDtsp-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin(Transparent flood-free land)
Quick guide
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River Flood: North East Basin
[RIVER-FLDall-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin
Quick guide
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River Flood: North East Basin (transparent)
[RIVER-FLDtsp-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin(Transparent flood-free land)
Quick guide
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River Flood: North West
[RIVER-FLDall-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region
Quick guide
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River Flood: North West (transparent)
[RIVER-FLDtsp-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region(Transparent flood-free land)
Quick guide
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River Flood: South East
[RIVER-FLDall-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region
Quick guide
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River Flood: South East (transparent)
[RIVER-FLDtsp-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region(Transparent flood-free land)
Quick guide
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River Flood: South West
[RIVER-FLDall-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region
Quick guide
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River Flood: South West (tsp)
[RIVER-FLDtsp-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region(Transparent flood-free land)
Quick guide
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River Flood: US
[RIVER-FLDall-US]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
US
Quick guide
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River Flood: US (transparent)
[RIVER-FLDtsp-US]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
US(Transparent flood-free land)
Quick guide
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River Flood: West Gulf Basin
[RIVER-FLDall-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin
Quick guide
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River Flood: West Gulf Basin (transparent)
[RIVER-FLDtsp-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin(Transparent flood-free land)
Quick guide
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River Ice: Alaska
[RIVER-ICE-AP]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Alaska
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River Ice: Missouri Basin
[RIVER-ICE-MB]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Missouri Basin (product off-line in summer)
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River Ice: North Central Basin
[RIVER-ICE-NC]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, North Central Basin (product off-line in summer)
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River Ice: North East Basin
[RIVER-ICE-NE]
CIMSS hosts a flood product developed at a river ice product developed atCity College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent....
CIMSS hosts a flood product developed at a river ice product developed at City College of New York (CCNY) derived from VIIRS. The CCNY algorithm produces an enhanced river ice mapping product with river ice extent. Products are generated with direct broadcast VIIRS data in near real-time. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Algorithm Version5.1, Northeast Basin (product off-line in summer)
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WI USGS Landsat Poster
[wilandsat]
This is a georeferenced poster from the USGS. The original source is:http://eros.usgs.gov/imagegallery/landsat-state-mosaics unfortunately the original poster imagery without graphics burned-in is not available.
This is a georeferenced poster from the USGS. The original source is: http://eros.usgs.gov/imagegallery/landsat-state-mosaics unfortunately the original poster imagery without graphics burned-in is not available.
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Landsat 8 Look Natural Color (Swaths)
[lsat8-llook-fc]
View of lsat8-llook-fc-scenes
View of lsat8-llook-fc-scenes
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|
Landsat 8 Look Thermal IR (Swaths)
[lsat8-llook-tir]
View of lsat8-llook-tir-scenes
View of lsat8-llook-tir-scenes
|
|
Landsat 9 Look Natural Color (Swaths)
[lsat9-llook-fc]
View of lsat9-llook-fc-scenes
View of lsat9-llook-fc-scenes
|
|
Landsat 9 Look Thermal IR (Swaths)
[lsat9-llook-tir]
View of lsat9-llook-tir-scenes
View of lsat9-llook-tir-scenes
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Landsat Footprints (WRS-2)
[wrs2-land]
The Worldwide Reference System (WRS) is a global notation used incataloging Landsat data. Landsat 8 and Landsat 7 follow the WRS-2, as did Landsat 5 and Landsat 4.
The Worldwide Reference System (WRS) is a global notation used in cataloging Landsat data. Landsat 8 and Landsat 7 follow the WRS-2, as did Landsat 5 and Landsat 4.
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GOES East GLM Full Disk Group Density
[glmgroupdensity]
The Geostationary Lightning Mapper, or GLM, on board GeostationaryOperational Environmental Satellite– R Series spacecraft, is the first operational lightning mapper flown on a geostationary satellite. GLM...
The Geostationary Lightning Mapper, or GLM, on board Geostationary Operational Environmental Satellite– R Series spacecraft, is the first operational lightning mapper flown on a geostationary satellite. GLM detects the light emitted by lightning at the tops of clouds day and night and collects information such as the frequency, location and extent of lightning discharges. The instrument measures total lightning, both in-cloud and cloud-to-ground, to aid in forecasting developing severe storms and a wide range of high-impact environmental phenomena including hailstorms, microburst winds, tornadoes, hurricanes, ash clouds, and snowstorms.
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GOES East GLM Full Disk Group Points
[glmgrouppoints]
The Geostationary Lightning Mapper, or GLM, on board GeostationaryOperational Environmental Satellite– R Series spacecraft, is the first operational lightning mapper flown on a geostationary satellite. GLM...
The Geostationary Lightning Mapper, or GLM, on board Geostationary Operational Environmental Satellite– R Series spacecraft, is the first operational lightning mapper flown on a geostationary satellite. GLM detects the light emitted by lightning at the tops of clouds day and night and collects information such as the frequency, location and extent of lightning discharges. The instrument measures total lightning, both in-cloud and cloud-to-ground, to aid in forecasting developing severe storms and a wide range of high-impact environmental phenomena including hailstorms, microburst winds, tornadoes, hurricanes, ash clouds, and snowstorms.
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MIRS 90Ghz Brightness Temperature
[MIRS-BT90]
MIRS 90Ghz Brightness Temperature
MIRS 90Ghz Brightness Temperature
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MIRS Rain Rate
[MIRS-RainRate]
With inputs from the ATMS (Advanced Technology Microwave Sounder) sensoraboard JPSS satellites, the rainfall rate product from the Microwave Integrated Retrieval System (MIRS) identifies the intensity of rain at the...
With inputs from the ATMS (Advanced Technology Microwave Sounder) sensor aboard JPSS satellites, the rainfall rate product from the Microwave Integrated Retrieval System (MIRS) identifies the intensity of rain at the instant the satellite is passing over the area. It is derived from three vertically integrated MIRS products: Cloud Liquid Water (CLW), Rain Water Path (RWP), and Ice Water Path (IWP), taking advantage of the physical relationship found between atmospheric hydrometeor amounts and surface rain rate.
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MIRS RainRate - Alaska (GINA)
[MIRS-RainRate-AK]
With inputs from the ATMS (Advanced Technology Microwave Sounder) sensoraboard JPSS satellites, the rainfall rate product from the Microwave Integrated Retrieval System (MIRS) identifies the intensity of rain at the...
With inputs from the ATMS (Advanced Technology Microwave Sounder) sensor aboard JPSS satellites, the rainfall rate product from the Microwave Integrated Retrieval System (MIRS) identifies the intensity of rain at the instant the satellite is passing over the area. It is derived from three vertically integrated MIRS products: Cloud Liquid Water (CLW), Rain Water Path (RWP), and Ice Water Path (IWP), taking advantage of the physical relationship found between atmospheric hydrometeor amounts and surface rain rate.
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Aqua Aerosol Optical Depth
[AQUA-AER]
MODIS: AQUA Aerosol Optical Depth (ta)
MODIS: AQUA Aerosol Optical Depth (ta)
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Aqua False Color
[aquafalsecolor]
CIMSS-MODIS Satellite False Color (Aqua)
CIMSS-MODIS Satellite False Color (Aqua)
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Terra Aerosol Optical Depth
[TERRA-AER]
MODIS: TERRA Aerosol Optical Depth (ta)
MODIS: TERRA Aerosol Optical Depth (ta)
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Terra False Color
[terrafalsecolor]
CIMSS-MODIS Satellite False Color (Terra)
CIMSS-MODIS Satellite False Color (Terra)
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Terra True Color
[terratruecolor]
CIMSS-MODIS Satellite True Color (Terra)
CIMSS-MODIS Satellite True Color (Terra)
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True Color Clear View
[BRDF]
MODIS Clear View ConUS Composite. BRDF (Bidirectional ReluctanceDistribution Function) is a 16-day cloud-free composite.
MODIS Clear View ConUS Composite. BRDF (Bidirectional Reluctance Distribution Function) is a 16-day cloud-free composite.
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Meteosat 8 SEVIRI Full Disk B01 Vis (0.6um)
[Met8-SEVIRI-FD-BAND01]
VIS0.6: Known from the Advanced Very High Resolution Radiometer (AVHRR) ofthe polar-orbiting NOAA satellites. It is essential for cloud detection, cloud tracking, scene identification, aerosol, and land surface and veg...
VIS0.6: Known from the Advanced Very High Resolution Radiometer (AVHRR) of the polar-orbiting NOAA satellites. It is essential for cloud detection, cloud tracking, scene identification, aerosol, and land surface and veg etation monitoring.
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Meteosat 8 SEVIRI Full Disk B04 IR Fire (3.9um)
[Met8-SEVIRI-FD-BAND04]
IR3.9: Known from AVHRR. Primarily for low cloud and fog detection (Eyre etal. 1984; Lee et al. 1997). Also supports measurement of land and sea surface temperature at night and increases the low- level wind coverage...
IR3.9: Known from AVHRR. Primarily for low cloud and fog detection (Eyre et al. 1984; Lee et al. 1997). Also supports measurement of land and sea surface temperature at night and increases the low- level wind coverage from cloud tracking (Velden et al. 2001). For MSG, the spectral band has been broadened to longer wavelengths to improve
signal-to-noise ratio.
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Meteosat 8 SEVIRI Full Disk B05 WV High (6.2um)
[Met8-SEVIRI-FD-BAND05]
WV6.2: Continues mission of
Meteosat broadband water vapor channel forobserving water vapor and winds. Enhanced to two channels peaking at different levels in the tropo sphere. Also supports height allocation of...
WV6.2: Continues mission of
Meteosat broadband water vapor channel for observing water vapor and winds. Enhanced to two channels peaking at different levels in the tropo sphere. Also supports height allocation of semitransparent clouds (Nieman et al. 1993; Schmetz et al. 1993).
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Meteosat 8 SEVIRI Full Disk B09 IR Clean (10.8um)
[Met8-SEVIRI-FD-BAND09]
IR10.8: Well-known split window channel (e.g., AVHRR). Essential formeasur ing sea and land surface and cloud-top temperatures; also for the detection of cirrus cloud (e.g., Inoue 1987) and volcanic ash clouds (Prata...
IR10.8: Well-known split window channel (e.g., AVHRR). Essential for measur ing sea and land surface and cloud-top temperatures; also for the detection of cirrus cloud (e.g., Inoue 1987) and
volcanic ash clouds (Prata 1989).
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Meteosat 8 SEVIRI Full Disk B09 IR Clean (10.8um) enhanced
[Met8-SEVIRI-FD-BAND09-enh]
IR10.8: Well-known split window channel (e.g., AVHRR). Essential formeasur ing sea and land surface and cloud-top temperatures; also for the detection of cirrus cloud (e.g., Inoue 1987) and volcanic ash clouds (Prata...
IR10.8: Well-known split window channel (e.g., AVHRR). Essential for measur ing sea and land surface and cloud-top temperatures; also for the detection of cirrus cloud (e.g., Inoue 1987) and
volcanic ash clouds (Prata 1989).
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Meteosat 8 SEVIRI Full Disk B12 Vis HRV (0.7um)
[Met8-SEVIRI-HRV-BAND12]
The high-resolution visible (HRV) channel covers half of the full disk inthe east–west direction and a full disk in the north–south direction (see Fig. 3). The high-resolution visible channel has a spatial resolution...
The high-resolution visible (HRV) channel covers half of the full disk in the east–west direction and a full disk in the north–south direction (see Fig. 3). The high-resolution visible channel has a spatial resolution of 1.67 km, as the oversampling factor is 1.67 the sampling distance is 1 km at nadir.
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Meteosat 11 SEVIRI Full Disk B01 Vis (0.6um)
[Met11-SEVIRI-FD-BAND01]
VIS0.6: Known from the Advanced Very High Resolution Radiometer (AVHRR) ofthe polar-orbiting NOAA satellites. It is essential for cloud detection, cloud tracking, scene identification, aerosol, and land surface and veg...
VIS0.6: Known from the Advanced Very High Resolution Radiometer (AVHRR) of the polar-orbiting NOAA satellites. It is essential for cloud detection, cloud tracking, scene identification, aerosol, and land surface and veg etation monitoring.
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Meteosat 11 SEVIRI Full Disk B04 IR Fire (3.9um)
[Met11-SEVIRI-FD-BAND04]
IR3.9: Known from AVHRR. Primarily for low cloud and fog detection (Eyre etal. 1984; Lee et al. 1997). Also supports measurement of land and sea surface temperature at night and increases the low- level wind coverage...
IR3.9: Known from AVHRR. Primarily for low cloud and fog detection (Eyre et al. 1984; Lee et al. 1997). Also supports measurement of land and sea surface temperature at night and increases the low- level wind coverage from cloud tracking (Velden et al. 2001). For MSG, the spectral band has been broadened to longer wavelengths to improve
signal-to-noise ratio.
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Meteosat 11 SEVIRI Full Disk B05 WV High (6.2um)
[Met11-SEVIRI-FD-BAND05]
WV6.2: Continues mission of
Meteosat broadband water vapor channel forobserving water vapor and winds. Enhanced to two channels peaking at different levels in the tropo sphere. Also supports height allocation of...
WV6.2: Continues mission of
Meteosat broadband water vapor channel for observing water vapor and winds. Enhanced to two channels peaking at different levels in the tropo sphere. Also supports height allocation of semitransparent clouds (Nieman et al. 1993; Schmetz et al. 1993).
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Meteosat 11 SEVIRI Full Disk B09 IR Clean (10.8um)
[Met11-SEVIRI-FD-BAND09]
IR10.8: Well-known split window channel (e.g., AVHRR). Essential formeasur ing sea and land surface and cloud-top temperatures; also for the detection of cirrus cloud (e.g., Inoue 1987) and volcanic ash clouds (Prata...
IR10.8: Well-known split window channel (e.g., AVHRR). Essential for measur ing sea and land surface and cloud-top temperatures; also for the detection of cirrus cloud (e.g., Inoue 1987) and
volcanic ash clouds (Prata 1989).
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Meteosat 11 SEVIRI Full Disk B09 IR Clean (10.8um) enhanced
[Met11-SEVIRI-FD-BAND09-enh]
IR10.8: Well-known split window channel (e.g., AVHRR). Essential formeasur ing sea and land surface and cloud-top temperatures; also for the detection of cirrus cloud (e.g., Inoue 1987) and volcanic ash clouds (Prata...
IR10.8: Well-known split window channel (e.g., AVHRR). Essential for measur ing sea and land surface and cloud-top temperatures; also for the detection of cirrus cloud (e.g., Inoue 1987) and
volcanic ash clouds (Prata 1989).
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Meteosat 11 SEVIRI Full Disk B12 Vis HRV (0.7um)
[Met11-SEVIRI-HRV-BAND12]
The high-resolution visible (HRV) channel covers half of the full disk inthe east–west direction and a full disk in the north–south direction (see Fig. 3). The high-resolution visible channel has a spatial resolution...
The high-resolution visible (HRV) channel covers half of the full disk in the east–west direction and a full disk in the north–south direction (see Fig. 3). The high-resolution visible channel has a spatial resolution of 1.67 km, as the oversampling factor is 1.67 the sampling distance is 1 km at nadir.
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NAIP WI
[NAIPWI]
National Agricultural Imagery Program aerial photography from the WisconsinFarm Service Agency (WI-FSA) of the USDA.
National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA.
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NAIP WI Color Infrared
[NAIPWICIR]
National Agricultural Imagery Program aerial photography from the WisconsinFarm Service Agency (WI-FSA) of the USDA (Color Infrared)
National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA (Color Infrared)
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Storm Cell ID and Tracking - Filter 1
[SCIT-ALL]
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALLCells 2| Moderate Threat level Cells 3| Severe Threat level Cells
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALL Cells
2| Moderate Threat level Cells
3| Severe Threat level Cells
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Storm Cell ID and Tracking - Filter 2
[SCIT-MOD]
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALLCells 2| Moderate Threat level Cells 3| Severe Threat level Cells
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALL Cells
2| Moderate Threat level Cells
3| Severe Threat level Cells
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Storm Cell ID and Tracking - Filter 3
[SCIT-SEV]
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALLCells 2| Moderate Threat level Cells 3| Severe Threat level Cells
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALL Cells
2| Moderate Threat level Cells
3| Severe Threat level Cells
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Storm Cell ID and Tracking - Forecast 2
[SCIT-MOD-FCST]
Storm Cell Identification and Tracking (SCIT)
Filter2 - 15min ForecastTrajectories 1| ALL Cells 2| Moderate Threat level Cells 3| Severe Threat level Cells
Storm Cell Identification and Tracking (SCIT)
Filter2 - 15min Forecast Trajectories
1| ALL Cells
2| Moderate Threat level Cells
3| Severe Threat level Cells
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National Reflectivity MRMS Composite mask
[nexrrain]
The Multi-Radar Multi-Sensor (MRMS) system is now operational at theNational Centers for Environmental Prediction (NCEP). The MRMS system consists of the Warning Decision Support System–Integrated Information...
The Multi-Radar Multi-Sensor (MRMS) system is now operational at the National Centers for Environmental Prediction (NCEP). The MRMS system consists of the Warning Decision Support System–Integrated Information suite of severe weather and aviation products and the quantitative precipitation estimation (QPE) products created by the National Mosaic and Multi-Sensor QPE system. The MRMS system provides operational guidance for severe convective weather, QPE, and aviation hazards on a seamless three-dimensional grid that is created at a spatial resolution of 0.01° latitude × 0.01° longitude, with 33 vertical levels, every 2 min over the conterminous United States (CONUS) and southern Canada.
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NEXRAD ConUS Hybrid Reflectivity mask
[nexrhres]
Values are actual reflectivity values instead of categories, data extendsto further range, and additional elevations are available. Products from elevation angles at or below 3.5 degrees are available, and select sites...
Values are actual reflectivity values instead of categories, data extends to further range, and additional elevations are available. Products from elevation angles at or below 3.5 degrees are available, and select sites may also scan at an additional low elevation angle, as low as -0.2 degrees. Specific elevation angles depend on the site and scanning mode of the Radar.
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NEXRAD ConUS Storm Total Precipitation
[nexrstorm]
Storm Total Precipitation (NTP/80)
This product uses the PPS algorithm tocreate a continuously updated estimate of a storm’s accumulated precipitation. Accumulation is tracked on a 1.1 nm x 1 degree grid....
Storm Total Precipitation (NTP/80)
This product uses the PPS algorithm to create a continuously updated estimate of a storm’s accumulated precipitation. Accumulation is tracked on a 1.1 nm x 1 degree grid. Scientists use this product to locate flood potential over urban or rural areas, estimate total basin runoff, and provide rainfall data 24 hours a day.
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NEXRAD Alaska Base Reflectivity
[NEXRAD-Alaska]
WSR 88D NEXRAD Radar Mosiac Base Reflectivity Tilt 1 for Alaska Region.Bethel (KABC) Sitka (KACG) Nome (KAEC) Anchorage (KANG) Middleton Island (KAIH) King Salmon (KAKC) Fairbanks (KAPD)
WSR 88D NEXRAD Radar Mosiac Base Reflectivity Tilt 1 for Alaska Region.
Bethel (KABC)
Sitka (KACG)
Nome (KAEC)
Anchorage (KANG)
Middleton Island (KAIH)
King Salmon (KAKC)
Fairbanks (KAPD)
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NEXRAD Guam Base Reflectivity
[NEXRAD-Guam]
NEXRAD Guam Base Reflectivity
NEXRAD Guam Base Reflectivity
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NEXRAD Hawaii Base Reflectivity
[NEXRAD-Hawaii]
NEXRAD Hawaii Base Reflectivity
NEXRAD Hawaii Base Reflectivity
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NEXRAD Puerto Rico Base Reflectivity
[NEXRAD-PuertoRico]
WSR 88D NEXRAD Radar Base Reflectivity Tilt 1 for San Juan, Puerto Rico
WSR 88D NEXRAD Radar Base Reflectivity Tilt 1 for San Juan, Puerto Rico
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CMORPH2 1-Day Precip Accumulation
[c2accum1dy]
This satellite-derived precipitation product represents global 1-dayaccumulation. The second generation CMORPH (CMORPH2) has started test real-time production of 30-minute precipitation estimates on a 0.05-degree...
This satellite-derived precipitation product represents global 1-day accumulation. The second generation CMORPH (CMORPH2) has started test real-time production of 30-minute precipitation estimates on a 0.05-degree lat/lon grid over the entire globe, from pole-to-pole. The CMORPH2 is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include various rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available polar or "low earth" (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) and LEO platforms, and model precipitation forecast from the NCEP operational global forecast system (GFS).
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CMORPH2 1-Hour Precip Accumulation
[c2accum1hr]
This satellite-derived precipitation product represents global 1-houraccumulation. The second generation CMORPH (CMORPH2) has started test real-time production of 30-minute precipitation estimates on a 0.05-degree...
This satellite-derived precipitation product represents global 1-hour accumulation. The second generation CMORPH (CMORPH2) has started test real-time production of 30-minute precipitation estimates on a 0.05-degree lat/lon grid over the entire globe, from pole-to-pole. The CMORPH2 is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include various rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available polar or "low earth" (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) and LEO platforms, and model precipitation forecast from the NCEP operational global forecast system (GFS).
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CMORPH2 7-Day Precip Accumulation
[c2accum7dy]
This satellite-derived precipitation product represents global 7-dayaccumulation. The second generation CMORPH (CMORPH2) has started test real-time production of 30-minute precipitation estimates on a 0.05-degree...
This satellite-derived precipitation product represents global 7-day accumulation. The second generation CMORPH (CMORPH2) has started test real-time production of 30-minute precipitation estimates on a 0.05-degree lat/lon grid over the entire globe, from pole-to-pole. The CMORPH2 is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include various rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available polar or "low earth" (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) and LEO platforms, and model precipitation forecast from the NCEP operational global forecast system (GFS).
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Fronts and Troughs
[Fronts]
NCEP Frontal Analysis: fronts and troughs
NCEP Frontal Analysis: fronts and troughs
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Low/High Pressure
[HighLow]
NCEP Frontal Analysis: Highs and Lows
NCEP Frontal Analysis: Highs and Lows
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Snow Depth (SNODAS)
[SNODAS-Thickness]
SNODAS (SNOw Data Assimilation System) is a modeling and data assimilationsystem developed by NOAA National Weather Service"s NOHRSC (National Operational Hydrologic Remote Sensing Center) to provide the best possible...
SNODAS (SNOw Data Assimilation System) is a modeling and data assimilation system developed by NOAA National Weather Service"s NOHRSC (National Operational Hydrologic Remote Sensing Center) to provide the best possible estimates of snow cover and associated parameters to support hydrologic modeling and analysis. The aim of SNODAS is to provide a physically consistent framework to integrate snow data from satellite, airborne platforms, and ground stations with model estimates of snow cover. The 24hr Snow Thickness is a daily snapshot of snow thickness at 0600hr UTC.
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Snowfall Total - 24hr (SNODAS)
[SNODAS-Accumulate]
SNODAS (SNOw Data Assimilation System) is a modeling and data assimilationsystem developed by NOAA National Weather Service"s NOHRSC (National Operational Hydrologic Remote Sensing Center) to provide the best possible...
SNODAS (SNOw Data Assimilation System) is a modeling and data assimilation system developed by NOAA National Weather Service"s NOHRSC (National Operational Hydrologic Remote Sensing Center) to provide the best possible estimates of snow cover and associated parameters to support hydrologic modeling and analysis. The aim of SNODAS is to provide a physically consistent framework to integrate snow data from satellite, airborne platforms, and ground stations with model estimates of snow cover. 24hr Snow Fall Total is calculated every 24 hours at 0600hr UTC and posted shortly thereafter.
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Australian Soil Moisture - Root Zone
[BOM-Root-Zone-Soil-Moisture]
Australian Bureau of Meteorology: Root Zone Soil Moisture is the sum ofwater in the AWRA-L Upper and Lower soil layers and represents the percentage of available water content in the top 1 m of the soil profile....
Australian Bureau of Meteorology: Root Zone Soil Moisture is the sum of water in the AWRA-L Upper and Lower soil layers and represents the percentage of available water content in the top 1 m of the soil profile. The maximum storage within the soil layer is calculated from the depth of the soil and the relative soil water storage capacity. More info at the link below.
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Convective Outlook - Categorical
[SPC-ConvOutlook-CATG]
SPC Convective Outlook - Categorical
SPC Convective Outlook - Categorical
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Convective Outlook - Categorical (color map)
[SPC-ConvOutlook-CATG-cmap]
View of SPC-ConvOutlook-CATG
View of SPC-ConvOutlook-CATG
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Insolation East
[InsolationEast]
This product displays daily-integrated solar radiation estimates (MJ-m-2)for the previous calendar day derived using half-hourly imagery data from GOES-EAST and GOES-WEST geostationary satellites and a simple radiative...
This product displays daily-integrated solar radiation estimates (MJ-m-2) for the previous calendar day derived using half-hourly imagery data from GOES-EAST and GOES-WEST geostationary satellites and a simple radiative transfer model of the atmosphere. GOES-EAST data are used for the eastern half of the U.S., GOES-WEST for the western half and both these results are displayed upon initial invocation of this insolation page. Raw data values scaled by 100. Right-click on a pixel and select "probe" to view values.
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Insolation West
[Insolation]
This product displays daily-integrated solar radiation estimates (MJ-m-2)for the previous calendar day derived using half-hourly imagery data from GOES-EAST and GOES-WEST geostationary satellites and a simple radiative...
This product displays daily-integrated solar radiation estimates (MJ-m-2) for the previous calendar day derived using half-hourly imagery data from GOES-EAST and GOES-WEST geostationary satellites and a simple radiative transfer model of the atmosphere. GOES-EAST data are used for the eastern half of the U.S., GOES-WEST for the western half and both these results are displayed upon initial invocation of this insolation page. Raw data values scaled by 100. Right-click on a pixel and select "probe" to view values.
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US Landsat Analysis Ready Data (ARD) Grids
[usgs-ard-grid]
This product shows the Analysis Ready Data (ARD) grids for Landsatsatellite data. It includes all three grids for the contiguous United States (CONUS), Alaska, and Hawaii. Landsat data have been produced,...
This product shows the Analysis Ready Data (ARD) grids for Landsat satellite data. It includes all three grids for the contiguous United States (CONUS), Alaska, and Hawaii. Landsat data have been produced, archived, and distributed by the U.S. Geological Survey (USGS) since 1972. Users rely upon these data for conducting historical studies of land surface change, but they have shouldered the burden of post-production processing to create application-ready datasets. To alleviate this burden on the user, the USGS has initiated an effort to produce a collection of Landsat Science Products to support land surface change studies. The effort involves re-gridding Landsat imagery in regular 150km x 150km squares using an Albers Equal Area projection.
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Current Fire Incidents: lightning dashboards
[CURRENTNIFC]
LightningCast and GLM meteograms for current fire incidents.
LightningCast and GLM meteograms for current fire incidents.
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GOES-East GLM FED CONUS
[GOESEastGLMFEDRadC]
GOES-East flash-extent density, a 5-min accumulation of flashes at eachpoint.
GOES-East flash-extent density, a 5-min accumulation of flashes at each point.
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GOES-East GLM MFA CONUS
[GOESEastGLMMFARadC]
GOES-East minimum flash density
GOES-East minimum flash density
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GOES-East GLM TOE CONUS
[GOESEastGLMTOERadC]
GOES-East total optical energy, in femto Joules (fJ).
GOES-East total optical energy, in femto Joules (fJ).
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GOES-West GLM FED CONUS
[GOESWestGLMFEDRadC]
GOES-West flash-extent density, a 5-min accumulation of flashes at eachpoint.
GOES-West flash-extent density, a 5-min accumulation of flashes at each point.
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LightningCast GOES-East CONUS
[PLTGGOESEastRadC]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-East FD (OCONUS)
[PLTGGOESEastRadF]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-East MESO1
[PLTGGOESEastRadM1]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-East MESO2
[PLTGGOESEastRadM2]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-East RadC Alabama
[PLTGGOESEastRadCAL]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-East RadM2 Gridded
[PLTGGOESEastRadM2Gridded]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-West Alaska/Western Canada
[PLTGGOESWestRadFAKCAN]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-West American Samoa
[PLTGGOESWestRadFUSSAMOA]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-West CONUS
[PLTGGOESWestRadC]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-West MESO1
[PLTGGOESWestRadM1]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast GOES-West MESO2
[PLTGGOESWestRadM2]
An AI model that predicts the probability of lightning in the next 60minutes using GOES-R ABI data.
An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.
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LightningCast Himawari Guam
[PLTGAHIJAPANFLDKGUAM]
An AI model that predicts the probability of lightning in the next 60minutes using Himawari AHI data.
An AI model that predicts the probability of lightning in the next 60 minutes using Himawari AHI data.
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Vermont Flooding 2023 - Color Infrared
[vt-floods-2023-CIR]
Sentinel 2a captured this image of flooding in Vermont on July 11, 2023 at11:38am local time. This image represents bands 8, 4, and 3 as RGB showing vegetation in red and water in black or gray. Source: Copernicus Open...
Sentinel 2a captured this image of flooding in Vermont on July 11, 2023 at 11:38am local time. This image represents bands 8, 4, and 3 as RGB showing vegetation in red and water in black or gray. Source: Copernicus Open Access Hub.
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Vermont Flooding 2023 - Natural Color
[vt-floods-2023]
Sentinel 2a captured this image of flooding in Vermont on July 11, 2023 at11:38am local time. This image represents bands 4, 3, and 2 as RGB to approximate true color. Source: Copernicus Open Access Hub.
Sentinel 2a captured this image of flooding in Vermont on July 11, 2023 at 11:38am local time. This image represents bands 4, 3, and 2 as RGB to approximate true color. Source: Copernicus Open Access Hub.
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Vermont Flooding 2023 - Normalized Difference
[vt-floods-2023-nbr]
These images were produced from Sentinel 2a imagery with Google EarthEngine and represent normalized differences between the 10-meter green band (B3) and 20-meter SWIR2 band (B12). Clouds have been masked. The "before"...
These images were produced from Sentinel 2a imagery with Google Earth Engine and represent normalized differences between the 10-meter green band (B3) and 20-meter SWIR2 band (B12). Clouds have been masked. The "before" image is a composite marked as June 11, 2023 00:00UTC. The "after" image was captured July 11, 2023 11:38am EDT. Switching between the two time steps highlights new water in dark blue. Credit: Danielle Losos - SSEC/CIMSS University of Wisconsin-Madison
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Historic Fire Scars (MTBS)
[historic-fire-scars-conus]
These data come from the interagency MTBS (Monitoring Trends in BurnSeverity) program through their direct download service.
These data come from the interagency MTBS (Monitoring Trends in Burn Severity) program through their direct download service.
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Hydro Estimator Rainfall
[NESDIS-GHE-HourlyRainfall]
The HE algorithm uses infrared (IR) brightness temperatures to identifyregions of rainfall and retrieve rainfall rate, while using National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS)...
The HE algorithm uses infrared (IR) brightness temperatures to identify regions of rainfall and retrieve rainfall rate, while using National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model fields to account for the effects of moisture availability, evaporation, orographic modulation, and thermodynamic profile effects. Estimates of rainfall from satellites can provide critical rainfall information in regions where data from gauges or radar are unavailable or unreliable, such as over oceans or sparsely populated regions.
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Snow Fall Rate
[NESDIS-SnowFallRate]
AMSU Snow Fall Rate Global by NOAA-NESDIS
AMSU Snow Fall Rate Global by NOAA-NESDIS
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HRRR ConUS Latest Simulated Radar
[HRR-CONUS-RADAR-LATEST]
View of HRR-CONUS-PCP-SFC
View of HRR-CONUS-PCP-SFC
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RAP ConUS Latest Simulated Radar
[RAP-CONUS-PRAT-SFC-DBZ]
View of RAP-CONUS-PRAT-SFC
View of RAP-CONUS-PRAT-SFC
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Storm Cell ID and Tracking - Filter 1
[SCIT-ALL]
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALLCells 2| Moderate Threat level Cells 3| Severe Threat level Cells
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALL Cells
2| Moderate Threat level Cells
3| Severe Threat level Cells
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Storm Cell ID and Tracking - Filter 2
[SCIT-MOD]
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALLCells 2| Moderate Threat level Cells 3| Severe Threat level Cells
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALL Cells
2| Moderate Threat level Cells
3| Severe Threat level Cells
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Storm Cell ID and Tracking - Filter 3
[SCIT-SEV]
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALLCells 2| Moderate Threat level Cells 3| Severe Threat level Cells
Storm Cell Identification and Tracking (SCIT)
Filters
1| ALL Cells
2| Moderate Threat level Cells
3| Severe Threat level Cells
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Storm Cell ID and Tracking - Forecast 2
[SCIT-MOD-FCST]
Storm Cell Identification and Tracking (SCIT)
Filter2 - 15min ForecastTrajectories 1| ALL Cells 2| Moderate Threat level Cells 3| Severe Threat level Cells
Storm Cell Identification and Tracking (SCIT)
Filter2 - 15min Forecast Trajectories
1| ALL Cells
2| Moderate Threat level Cells
3| Severe Threat level Cells
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MRMS MergedReflectivity
[MERGEDREF]
Multi-Radar/Multi-Sensor MergedReflectivityQCComposite
Multi-Radar/Multi-Sensor MergedReflectivityQCComposite
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ProbSevere (version 3)
[PROBSEVEREV3]
PSv3 models use a machine-learning model called gradient-boosted decisiontrees.
PSv3 models use a machine-learning model called gradient-boosted decision trees.
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National Reflectivity MRMS Composite mask
[nexrrain]
The Multi-Radar Multi-Sensor (MRMS) system is now operational at theNational Centers for Environmental Prediction (NCEP). The MRMS system consists of the Warning Decision Support System–Integrated Information...
The Multi-Radar Multi-Sensor (MRMS) system is now operational at the National Centers for Environmental Prediction (NCEP). The MRMS system consists of the Warning Decision Support System–Integrated Information suite of severe weather and aviation products and the quantitative precipitation estimation (QPE) products created by the National Mosaic and Multi-Sensor QPE system. The MRMS system provides operational guidance for severe convective weather, QPE, and aviation hazards on a seamless three-dimensional grid that is created at a spatial resolution of 0.01° latitude × 0.01° longitude, with 33 vertical levels, every 2 min over the conterminous United States (CONUS) and southern Canada.
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NEXRAD Alaska Base Reflectivity
[NEXRAD-Alaska]
WSR 88D NEXRAD Radar Mosiac Base Reflectivity Tilt 1 for Alaska Region.Bethel (KABC) Sitka (KACG) Nome (KAEC) Anchorage (KANG) Middleton Island (KAIH) King Salmon (KAKC) Fairbanks (KAPD)
WSR 88D NEXRAD Radar Mosiac Base Reflectivity Tilt 1 for Alaska Region.
Bethel (KABC)
Sitka (KACG)
Nome (KAEC)
Anchorage (KANG)
Middleton Island (KAIH)
King Salmon (KAKC)
Fairbanks (KAPD)
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NEXRAD ConUS Hybrid Reflectivity mask
[nexrhres]
Values are actual reflectivity values instead of categories, data extendsto further range, and additional elevations are available. Products from elevation angles at or below 3.5 degrees are available, and select sites...
Values are actual reflectivity values instead of categories, data extends to further range, and additional elevations are available. Products from elevation angles at or below 3.5 degrees are available, and select sites may also scan at an additional low elevation angle, as low as -0.2 degrees. Specific elevation angles depend on the site and scanning mode of the Radar.
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NEXRAD ConUS Storm Total Precipitation
[nexrstorm]
Storm Total Precipitation (NTP/80)
This product uses the PPS algorithm tocreate a continuously updated estimate of a storm’s accumulated precipitation. Accumulation is tracked on a 1.1 nm x 1 degree grid....
Storm Total Precipitation (NTP/80)
This product uses the PPS algorithm to create a continuously updated estimate of a storm’s accumulated precipitation. Accumulation is tracked on a 1.1 nm x 1 degree grid. Scientists use this product to locate flood potential over urban or rural areas, estimate total basin runoff, and provide rainfall data 24 hours a day.
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NEXRAD Guam Base Reflectivity
[NEXRAD-Guam]
NEXRAD Guam Base Reflectivity
NEXRAD Guam Base Reflectivity
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NEXRAD Hawaii Base Reflectivity
[NEXRAD-Hawaii]
NEXRAD Hawaii Base Reflectivity
NEXRAD Hawaii Base Reflectivity
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NEXRAD Puerto Rico Base Reflectivity
[NEXRAD-PuertoRico]
WSR 88D NEXRAD Radar Base Reflectivity Tilt 1 for San Juan, Puerto Rico
WSR 88D NEXRAD Radar Base Reflectivity Tilt 1 for San Juan, Puerto Rico
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River Flood: Alaska
[RIVER-FLDall-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region
Quick guide
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River Flood: Alaska (transparent)
[RIVER-FLDtsp-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region(Transparent flood-free land)
Quick guide
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River Flood: Missouri Basin
[RIVER-FLDall-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin
Quick guide
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River Flood: Missouri Basin (transparent)
[RIVER-FLDtsp-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin(Transparent flood-free land)
Quick guide
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River Flood: North Central Basin
[RIVER-FLDall-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin
Quick guide
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River Flood: North Central Basin (transparent)
[RIVER-FLDtsp-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin(Transparent flood-free land)
Quick guide
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River Flood: North East Basin
[RIVER-FLDall-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin
Quick guide
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River Flood: North East Basin (transparent)
[RIVER-FLDtsp-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin(Transparent flood-free land)
Quick guide
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River Flood: North West
[RIVER-FLDall-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region
Quick guide
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River Flood: North West (transparent)
[RIVER-FLDtsp-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region(Transparent flood-free land)
Quick guide
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River Flood: South East
[RIVER-FLDall-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region
Quick guide
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River Flood: South East (transparent)
[RIVER-FLDtsp-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region(Transparent flood-free land)
Quick guide
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River Flood: South West
[RIVER-FLDall-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region
Quick guide
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River Flood: South West (tsp)
[RIVER-FLDtsp-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region(Transparent flood-free land)
Quick guide
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River Flood: US
[RIVER-FLDall-US]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
US
Quick guide
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River Flood: US (transparent)
[RIVER-FLDtsp-US]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
US(Transparent flood-free land)
Quick guide
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River Flood: West Gulf Basin
[RIVER-FLDall-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin
Quick guide
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River Flood: West Gulf Basin (transparent)
[RIVER-FLDtsp-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin(Transparent flood-free land)
Quick guide
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River Flood: Alaska
[RIVER-FLDall-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region
Quick guide
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River Flood: Alaska (transparent)
[RIVER-FLDtsp-AP]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Alaska region(Transparent flood-free land)
Quick guide
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River Flood: Missouri Basin
[RIVER-FLDall-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin
Quick guide
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River Flood: Missouri Basin (transparent)
[RIVER-FLDtsp-MB]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Missouri Basin(Transparent flood-free land)
Quick guide
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River Flood: North Central Basin
[RIVER-FLDall-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin
Quick guide
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River Flood: North Central Basin (transparent)
[RIVER-FLDtsp-NC]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North Central Basin(Transparent flood-free land)
Quick guide
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River Flood: North East Basin
[RIVER-FLDall-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin
Quick guide
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River Flood: North East Basin (transparent)
[RIVER-FLDtsp-NE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
North East Basin(Transparent flood-free land)
Quick guide
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River Flood: North West
[RIVER-FLDall-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region
Quick guide
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River Flood: North West (transparent)
[RIVER-FLDtsp-NW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Northwest Region(Transparent flood-free land)
Quick guide
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River Flood: South East
[RIVER-FLDall-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region
Quick guide
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River Flood: South East (transparent)
[RIVER-FLDtsp-SE]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southeast Region(Transparent flood-free land)
Quick guide
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River Flood: South West
[RIVER-FLDall-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region
Quick guide
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River Flood: South West (tsp)
[RIVER-FLDtsp-SW]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
Southwest Region(Transparent flood-free land)
Quick guide
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River Flood: US
[RIVER-FLDall-US]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
US
Quick guide
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River Flood: US (transparent)
[RIVER-FLDtsp-US]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
US(Transparent flood-free land)
Quick guide
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River Flood: West Gulf Basin
[RIVER-FLDall-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin
Quick guide
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River Flood: West Gulf Basin (transparent)
[RIVER-FLDtsp-WG]
CIMSS hosts a flood product developed at George Mason University (GMU)derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are...
CIMSS hosts a flood product developed at George Mason University (GMU) derived from VIIRS. The product provides an estimate of flooding water fractions, regions of ice, cloud, snow cover, and shadows. Products are generated with direct broadcast VIIRS data in near real-time. The success of the product has sparked interest from several river forecast centers (APRFC, NERFC, MBRFC, and WGRFC) as well as FEMA. These products could be useful to other institutions that monitor river ice and flooding conditions, especially in mid- and high-latitude locations.
West Gulf Basin(Transparent flood-free land)
Quick guide
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Cloud Top Cooling targets
[CIMSS-CTCtargets]
CIMSS-Cloud Top Cooling targets
CIMSS-Cloud Top Cooling targets
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Convective Outlook Day1
[SPCcoday1]
Convective Outlook Day1 (Category)
id=SPCcoday1
Convective Outlook Day1 (Category)
id=SPCcoday1
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Convective Outlook Day2
[SPCcoday2]
Convective Outlook Day2 (Category)
Convective Outlook Day2 (Category)
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Convective Outlook Day3
[SPCcoday3]
Convective Outlook Day3 (Categorical)
Convective Outlook Day3 (Categorical)
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Fire Weather Outlook Day1
[SPCfwday1]
Fire Weather Outlook Day1 (Category)
Fire Weather Outlook Day1 (Category)
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Fire Weather Outlook Day2
[SPCfwday2]
Fire Weather Outlook Day2 (Category)
Fire Weather Outlook Day2 (Category)
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Overshooting Tops targets
[CIMSS-OTtargets]
Cloud OverShooting Tops targets
Cloud OverShooting Tops targets
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Severe Weather Warning Outlines
[SevereOutl]
Tornado, Thunderstorm, Flash Flood and Marine Warnings (outlines only, nofill)
Tornado, Thunderstorm, Flash Flood and Marine Warnings (outlines only, no fill)
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Severe Weather Warnings
[Severe]
Tornado, Thunderstorm, Flash Flood and Marine Warning polygons.
Tornado, Thunderstorm, Flash Flood and Marine Warning polygons.
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Severe Weather Warning Vectors
[SevereVect]
Tornado and Thunderstorm Warning Vectors
Tornado and Thunderstorm Warning Vectors
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Severe Weather Watch Box
[SAW]
Severe Weather Watch Box - Aviation
Severe Weather Watch Box - Aviation
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Thunderstorm Watches/Warnings
[WWSEVTRW]
Thunderstorm Watches and Warnings
Thunderstorm Watches and Warnings
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IntenseStormNet -- GOES-East CONUS
[ICP]
Deep learning model that predicts where "intense" convection" is present,based on features that humans associate with intense convection.
Deep learning model that predicts where "intense" convection" is present, based on features that humans associate with intense convection.
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IntenseStormNet -- GOES-East MESO1
[ICPRadM1]
IntenseStormNet -- GOES East Mesoscale 1
IntenseStormNet -- GOES East Mesoscale 1
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IntenseStormNet -- GOES-East MESO2
[ICPRadM2]
IntenseStormNet -- GOES East Mesoscale 2
IntenseStormNet -- GOES East Mesoscale 2
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MRMS MergedReflectivity
[MERGEDREF]
Multi-Radar/Multi-Sensor MergedReflectivityQCComposite
Multi-Radar/Multi-Sensor MergedReflectivityQCComposite
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NWSWARNS12Z12Z
[NWSWARNS12Z12Z]
NWSWARNS12Z12Z (Severe and Tornado. No SVSs)
NWSWARNS12Z12Z (Severe and Tornado. No SVSs)
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ProbSevere (version2)
[PROBSEVERE]
The probability of any severe is the max(ProbHail,ProbWind,ProbTor).
The probability of any severe is the max(ProbHail,ProbWind,ProbTor).
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ProbSevere Accumulation 20% to 49%
[PROBSEVACCUMLOW]
ProbSevere Accumulation 20% to 49%
ProbSevere Accumulation 20% to 49%
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GOES CAPE
[cimssdpicapeli]
CIMSS-DPI Convective Available Potential Energy (Li et al. 2008)
CIMSS-DPI Convective Available Potential Energy (Li et al. 2008)
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GOES Lifted Index
[cimssdpilili]
GOES-DPI Lifted Index (Li et al. 2008)
GOES-DPI Lifted Index (Li et al. 2008)
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Sea Surface Temperature
[NESDIS-SST]
NESDIS: Hi-Res Sea Surface Temperature
NESDIS: Hi-Res Sea Surface Temperature
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Cloud Top Cooling targets
[CIMSS-CTCtargets]
CIMSS-Cloud Top Cooling targets
CIMSS-Cloud Top Cooling targets
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Earthquake Magnitude
[Earthquake-mag]
Earthquake Magnitude (Past 24hr)
Earthquake Magnitude (Past 24hr)
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Overshooting Tops targets
[CIMSS-OTtargets]
Cloud OverShooting Tops targets
Cloud OverShooting Tops targets
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Volcanic Ash Adv plumes
[VAA]
Volcanic Ash Advisories: Ash Clouds
Volcanic Ash Advisories: Ash Clouds
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Tropical Storm & Hurricane Forecast
[TSFCST]
National Hurricane Center Tropical Storm & Hurricane Forecast
National Hurricane Center Tropical Storm & Hurricane Forecast
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GOES East ABI ConUS RGB True Color
[G16-ABI-CONUS-TC]
True Color Imagery gives an image that is
approximately as you would see itfrom Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product,...
True Color Imagery gives an image that is
approximately as you would see it from Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product, approximates the green by combining Blue (0.47 µm), Red (0.64 µm) and ‘Veggie’ (0.86 µm) bands. The use of the Veggie band is important because it mimics the enhanced reflectivity present in the Green Band.
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GOES East ABI Full Disk RGB True Color
[G16-ABI-FD-TC]
True Color Imagery gives an image that is
approximately as you would see itfrom Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product,...
True Color Imagery gives an image that is
approximately as you would see it from Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product, approximates the green by combining Blue (0.47 µm), Red (0.64 µm) and ‘Veggie’ (0.86µm) bands. The use of the Veggie band is important because it mimics the enhanced reflectivity present in the Green Band.
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GOES East ABI Meso1 RGB True Color
[G16-ABI-MESO1-TC]
True Color Imagery gives an image that is approximately as you would see itfrom Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product,...
True Color Imagery gives an image that is approximately as you would see it from Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product, approximates the green by combining Blue (0.47 µm), Red (0.64 µm) and ‘Veggie’ (0.86 µm) bands. The use of the Veggie band is important because it mimics the enhanced reflectivity present in the Green Band.
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GOES East ABI Meso2 RGB True Color
[G16-ABI-MESO2-TC]
True Color Imagery gives an image that is approximately as you would see itfrom Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product,...
True Color Imagery gives an image that is approximately as you would see it from Outer Space. With ABI, the challenge of creating True Color arises from the the lack of a Green Band. The CIMSS Natural True Color product, approximates the green by combining Blue (0.47 µm), Red (0.64 µm) and ‘Veggie’ (0.86 µm) bands. The use of the Veggie band is important because it mimics the enhanced reflectivity present in the Green Band.
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NOAA20 VIIRS DNB (Swaths) Global
[j01-viirs-dnb-swath]
View of j01-viirs-bands-night-swath
View of j01-viirs-bands-night-swath
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NOAA20 VIIRS False Color (Daily) Global
[j01-viirs-false-color-daily]
View of j01-viirs-false-color-swath
View of j01-viirs-false-color-swath
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NOAA20 VIIRS False Color (Swaths) Global
[j01-viirs-false-color-swath]
View of j01-viirs-false-color
View of j01-viirs-false-color
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NOAA20 VIIRS M-Band Fire RGB (Swaths) Global
[j01-viirs-swath-fire-color]
This image is made by on-the-fly combining VIIRS bands M11 (2.25um) as red,M7 (8.66um) as green, and M4 (5.55) as blue. Because the M11 shortwave infrared band is sensitive to bright fires, it highlights active especially...
This image is made by on-the-fly combining VIIRS bands M11 (2.25um) as red, M7 (8.66um) as green, and M4 (5.55) as blue. Because the M11 shortwave infrared band is sensitive to bright fires, it highlights active especially hot fires in red while preserving a natural color appearance in the rest of the image.
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NOAA20 VIIRS M-Band Fire Temp (Swaths) Global
[j01-viirs-swath-fire-temp]
On-the-fly combination of bands 11, 10, 12.
On-the-fly combination of bands 11, 10, 12.
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NOAA20 VIIRS True Color (Daily) Global
[j01-viirs-true-color-daily]
View of j01-viirs-true-color-swath
View of j01-viirs-true-color-swath
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NOAA20 VIIRS True Color (Swaths) Global
[j01-viirs-true-color-swath]
View of j01-viirs-true-color
View of j01-viirs-true-color
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SNPP Day/Night AM Composite - Adaptive
[nppadpam]
NPP Day/Night AM Composite - Adaptive
NPP Day/Night AM Composite - Adaptive
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SNPP Day/Night Band (DNB) - Honolulu DB
[nppdnbdyn-hnl]
NPP Day/Night Band (DNB) - Honolulu DB
NPP Day/Night Band (DNB) - Honolulu DB
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SNPP VIIRS True Color DB Hawaii
[npptc-hnl]
NPP True Color (TC) - Honolulu DB
NPP True Color (TC) - Honolulu DB
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SNPP VIIRS True Color DB Puerto Rico
[npptc-upr]
NPP True Color (TC) - Puerto Rico DB
NPP True Color (TC) - Puerto Rico DB
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VIIRS NDVI 16-day Composite DB ConUS
[NDVI-16day-before]
This CONUS NDVI product is clipped from the global VIIRS composite productVNP13A1-001 using AppEEARS at the NASA LPDAAC. The spatial resolution is 500m. It is made with in alternating 8-day cycles from best available...
This CONUS NDVI product is clipped from the global VIIRS composite product VNP13A1-001 using AppEEARS at the NASA LPDAAC. The spatial resolution is 500m. It is made with in alternating 8-day cycles from best available pixels. See link below for more information.
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Global Black Marble
[VIIRS-MASK-54000x27000]
VIIRS Night Global Black Marble by NASA
VIIRS Night Global Black Marble by NASA
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Global Night Lights
[NightLightsColored]
Global Night Lights (enhanced)
Global Night Lights (enhanced)
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NOAA20 VIIRS Sea Ice Concentration Global
[j01-sic]
The Sea Ice Concentration products uses threshold reflectance(temperature) tests to detect possible ice cover for daytime (nighttime). Then uses a tie-point algorithm to determine fraction of grid cell at 1-km...
The Sea Ice Concentration products uses threshold reflectance (temperature) tests to detect possible ice cover for daytime (nighttime). Then uses a tie-point algorithm to determine fraction of grid cell at 1-km resolution covered by ice. The product is available over oceans, seas and lakes only under clear-sky conditions that is determined by VIIRS cloud mask.
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SNPP VIIRS SEA Ice Concentration Global
[snpp-sic]
The Sea Ice Concentration products uses threshold reflectance(temperature) tests to detect possible ice cover for daytime (nighttime). Then uses a tie-point algorithm to determine fraction of grid cell at 1-km...
The Sea Ice Concentration products uses threshold reflectance (temperature) tests to detect possible ice cover for daytime (nighttime). Then uses a tie-point algorithm to determine fraction of grid cell at 1-km resolution covered by ice. The product is available over oceans, seas and lakes only under clear-sky conditions that is determined by VIIRS cloud mask.
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SNPP VIIRS DNB Adaptive DB ConUS
[npp-viirs-adaptive-dnb-msn]
npp-viirs-adaptive-dnb-msn
npp-viirs-adaptive-dnb-msn
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SNPP VIIRS False Color (Daily) Global
[npp-viirs-false-color-daily]
View of npp-viirs-false-color-swath
View of npp-viirs-false-color-swath
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SNPP VIIRS False Color (Swaths) Global
[npp-viirs-false-color-swath]
View of npp-viirs-false-color
View of npp-viirs-false-color
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SNPP VIIRS Fire RGB (Swaths) Global
[npp-viirs-swath-fire-color]
View of npp-viirs-bands-day-swath
View of npp-viirs-bands-day-swath
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SNPP VIIRS Fire Temp (Swaths) Global
[npp-viirs-swath-fire-temp]
View of npp-viirs-bands-day-swath
View of npp-viirs-bands-day-swath
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SNPP VIIRS True Color (Daily) Global
[npp-viirs-true-color-daily]
View of npp-viirs-true-color-swath
View of npp-viirs-true-color-swath
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SNPP VIIRS True Color (Swaths) Global
[npp-viirs-true-color-swath]
View of npp-viirs-true-color
View of npp-viirs-true-color
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NOAA20 VIIRS DNB (Swaths) Global
[j01-viirs-dnb-swath]
View of j01-viirs-bands-night-swath
View of j01-viirs-bands-night-swath
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NOAA20 VIIRS False Color (Daily) Global
[j01-viirs-false-color-daily]
View of j01-viirs-false-color-swath
View of j01-viirs-false-color-swath
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NOAA20 VIIRS False Color (Swaths) Global
[j01-viirs-false-color-swath]
View of j01-viirs-false-color
View of j01-viirs-false-color
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NOAA20 VIIRS M-Band Fire RGB (Swaths) Global
[j01-viirs-swath-fire-color]
This image is made by on-the-fly combining VIIRS bands M11 (2.25um) as red,M7 (8.66um) as green, and M4 (5.55) as blue. Because the M11 shortwave infrared band is sensitive to bright fires, it highlights active especially...
This image is made by on-the-fly combining VIIRS bands M11 (2.25um) as red, M7 (8.66um) as green, and M4 (5.55) as blue. Because the M11 shortwave infrared band is sensitive to bright fires, it highlights active especially hot fires in red while preserving a natural color appearance in the rest of the image.
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NOAA20 VIIRS M-Band Fire Temp (Swaths) Global
[j01-viirs-swath-fire-temp]
On-the-fly combination of bands 11, 10, 12.
On-the-fly combination of bands 11, 10, 12.
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NOAA20 VIIRS True Color (Daily) Global
[j01-viirs-true-color-daily]
View of j01-viirs-true-color-swath
View of j01-viirs-true-color-swath
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NOAA20 VIIRS True Color (Swaths) Global
[j01-viirs-true-color-swath]
View of j01-viirs-true-color
View of j01-viirs-true-color
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Fire Radiative Power VIIRS I-band - GINA
[AFIMG-Points-GINA]
VIIRS 375m I-band high spatial resolution imagery provides a greaterresponse over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime...
VIIRS 375m I-band high spatial resolution imagery provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime performance. Consequently, these data are well suited for use in support of fire management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity. These data represent mean fire radiative power from SNPP and NOAA-20 Direct Broadcast imagery processed with CSPP software at GINA.
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MIRS RainRate - Alaska (GINA)
[MIRS-RainRate-AK]
With inputs from the ATMS (Advanced Technology Microwave Sounder) sensoraboard JPSS satellites, the rainfall rate product from the Microwave Integrated Retrieval System (MIRS) identifies the intensity of rain at the...
With inputs from the ATMS (Advanced Technology Microwave Sounder) sensor aboard JPSS satellites, the rainfall rate product from the Microwave Integrated Retrieval System (MIRS) identifies the intensity of rain at the instant the satellite is passing over the area. It is derived from three vertically integrated MIRS products: Cloud Liquid Water (CLW), Rain Water Path (RWP), and Ice Water Path (IWP), taking advantage of the physical relationship found between atmospheric hydrometeor amounts and surface rain rate.
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VIIRS Aerosol Optical Depth (GINA) DB Alaska
[AOD-RGB-GINA]
Aerosol optical depth is a measure of the extinction of the solar beam bydust and haze. In other words, particles in the atmosphere (dust, smoke, pollution) can block sunlight by absorbing or by scattering light. AOD...
Aerosol optical depth is a measure of the extinction of the solar beam by dust and haze. In other words, particles in the atmosphere (dust, smoke, pollution) can block sunlight by absorbing or by scattering light. AOD tells us how much direct sunlight is prevented from reaching the ground by these aerosol particles. It is a dimensionless number that is related to the amount of aerosol in the vertical column of atmosphere over the observation location. A value of 0.01 corresponds to an extremely clean atmosphere, and a value of 0.4 would correspond to a very hazy condition. An average aerosol optical depth for the U.S. is 0.1 to 0.15.
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VIIRS Fire Radiative Power I-band DB ConUS
[AFIMG-Points]
VIIRS 375m I-band high spatial resolution imagery provides a greaterresponse over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime...
VIIRS 375m I-band high spatial resolution imagery provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375m data also has improved nighttime performance. Consequently, these data are well suited for use in support of fire management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity. These data represent mean fire radiative power from SNPP and NOAA-20 Direct Broadcast imagery processed with CSPP software.
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VIIRS Fire RGB (GINA) DB Alaska
[DayLandCloudFire-RGB-GINA]
This RGB is created by assigning the VIIRS 3.74um channel to red, 0.87umchannel to green, and the 0.64um channel to blue. It is used to assess fire perimeters and burn scars. These data are produced by the Geographic...
This RGB is created by assigning the VIIRS 3.74um channel to red, 0.87um channel to green, and the 0.64um channel to blue. It is used to assess fire perimeters and burn scars. These data are produced by the Geographic Information Network of Alaska (GINA).
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VIIRS Fire Temp RGB (GINA) DB Alaska
[FireTemperature-RGB-GINA]
This RGB is created by assigning the VIIRS 3.74um channel to red, 2.25umchannel to green, and the 1.61um channel to blue. It is used to assess fire intensity and size, with fires ranging from red (lowest) to yellow to white...
This RGB is created by assigning the VIIRS 3.74um channel to red, 2.25um channel to green, and the 1.61um channel to blue. It is used to assess fire intensity and size, with fires ranging from red (lowest) to yellow to white (hottest or biggest). These data are produced by the Geographic Information Network of Alaska (GINA).
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VIIRS i04 (GINA) DB Alaska
[VIIRS-i04-GINA]
This is the VIIRS 3.74um single channel i-band with 376 m resolution. It isan IR channel that is very sensitive to fires and hot spots and is available day or night. A special colormap is used to enhance the warm-hot...
This is the VIIRS 3.74um single channel i-band with 376 m resolution. It is an IR channel that is very sensitive to fires and hot spots and is available day or night. A special colormap is used to enhance the warm-hot pixels. The sensors can become saturated by very intense fires and daytime radiance values can affected by reflected sunlight. These data are produced by the Geographic Information Network of Alaska (GINA).
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VIIRS Snowmelt (GINA) DB Alaska
[VIIRS-Snowmelt-GINA]
This RGB is created by assigning the VIIRS 1.61um channel to red, 1.24umchannel to green, and the 0.64um channel to blue. The blue shades identify snow cover characteristics. Darker blue shows wetter or older snow and...
This RGB is created by assigning the VIIRS 1.61um channel to red, 1.24um channel to green, and the 0.64um channel to blue. The blue shades identify snow cover characteristics. Darker blue shows wetter or older snow and lighter blues show drier or newer snow. These data are produced by the Geographic Information Network of Alaska (GINA).
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VIIRS True Color RGB (GINA) DB Alaska
[TrueColor-RGB-GINA]
This RGB is made from the red (0.64um), green (0.56um) and blue (0.49um)visible VIIRS channels. It produces a product that is close to what the human eye would see from space.
This RGB is made from the red (0.64um), green (0.56um) and blue (0.49um) visible VIIRS channels. It produces a product that is close to what the human eye would see from space.
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VIIRS NDVI 16-day Composite DB ConUS
[NDVI-16day-before]
This CONUS NDVI product is clipped from the global VIIRS composite productVNP13A1-001 using AppEEARS at the NASA LPDAAC. The spatial resolution is 500m. It is made with in alternating 8-day cycles from best available...
This CONUS NDVI product is clipped from the global VIIRS composite product VNP13A1-001 using AppEEARS at the NASA LPDAAC. The spatial resolution is 500m. It is made with in alternating 8-day cycles from best available pixels. See link below for more information.
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SNPP VIIRS True Color DB Hawaii
[npptc-hnl]
NPP True Color (TC) - Honolulu DB
NPP True Color (TC) - Honolulu DB
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SNPP VIIRS True Color DB Puerto Rico
[npptc-upr]
NPP True Color (TC) - Puerto Rico DB
NPP True Color (TC) - Puerto Rico DB
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Freezing Rain Probability >= .25" Final Forecast
[WPC-picezgt25]
The Probability of Freezing Rain Accumulating ≥ .25" Days 1-3
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The Probability of Freezing Rain Accumulating ≥ .25" Days 1-3
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
The product depicts the probability of freezing rain reaching or exceeding 0.25 inch for Days 1-3.
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Freezing Rain Probability >= 0.01"/24h
[WPC-picez24gep01]
The 24-Hour Probability of Freezing Rain Accumulating ≥ .01"
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The 24-Hour Probability of Freezing Rain Accumulating ≥ .01"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Freezing Rain Probability >= 0.10"/24h
[WPC-picez24gep10]
The 24-Hour Probability of Freezing Rain Accumulating ≥ .10"
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The 24-Hour Probability of Freezing Rain Accumulating ≥ .10"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Freezing Rain Probability >= 0.25"/24h
[WPC-picez24gep25]
The 24-Hour Probability of Freezing Rain Accumulating ≥ .25"
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The 24-Hour Probability of Freezing Rain Accumulating ≥ .25"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Freezing Rain Probability >=0.50"/24h
[WPC-picez24gep50]
The 24-Hour Probability of Freezing Rain Accumulating ≥ .50"
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The 24-Hour Probability of Freezing Rain Accumulating ≥ .50"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Freezing Rain Probability >=1.00"/24h
[WPC-picez24ge1]
The 24-Hour Probability of Freezing Rain Accumulating ≥ 1.00"
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The 24-Hour Probability of Freezing Rain Accumulating ≥ 1.00"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 0.1"/24h
[WPC-psnow24gep1]
24Hour Probability of Snow Accumulating ≥.1"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥.1"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 1.0"/24h
[WPC-psnow24ge1]
24Hour Probability of Snow Accumulating ≥1"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥1"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 2.0"/24h
[WPC-psnow24ge2]
24Hour Probability of Snow Accumulating ≥2"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥2"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 4.0"/24h
[WPC-psnow24ge4]
24Hour Probability of Snow Accumulating ≥4"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥4"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 6.0"/24h
[WPC-psnow24ge6]
24Hour Probability of Snow Accumulating ≥6"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥6"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 8.0"/24h
[WPC-psnow24ge8]
24Hour Probability of Snow Accumulating ≥8"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥8"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 12.0"/24h
[WPC-psnow24ge12p0]
24Hour Probability of Snow Accumulating ≥12"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥12"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 18.0"/24h
[WPC-psnow24ge18p0]
24Hour Probability of Snow Accumulating ≥18"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥18"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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WSSI Blowing Snow
[WPC-WSSI-BlowingSnow]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Blowing Snow Index Indicates the potential disruption due to blowing and drifting snow. This index accounts for land use type. For example, more densely forested areas will show less blowing snow than open grassland areas.
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WSSI Flash Freeze
[WPC-WSSI-FlashFreeze]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Flash Freeze Index Indicates the potential impacts of flash freezing (temperatures starting above freezing and quickly dropping below freezing) during or after precipitation events
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WSSI Ground Blizzard
[WPC-WSSI-Blizzard]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Ground Blizzard indicates the potential travel-related impacts of strong winds interacting with
pre-existing snow cover. This is the only sub-component that does not require snow to be forecast in order for calculations to be made. The NOHRSC snow cover data along with forecast winds are used to model the ground blizzard.
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WSSI Ice Accumulation
[WPC-WSSI-IceAccum]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Ice Accumulation indicates potential infrastructure impacts (e.g. roads/bridges) due to combined effects and severity of ice and wind. Designated urban areas are also weighted a little more than non-urban areas. Please note that not all NWS offices provide ice accumulation information into the NDFD. In those areas, the ice accumulation is not calculated.
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WSSI Overall Impact
[WPC-WSSI]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
The Overall WSSI Impact value is the maximum value from all the sub-components. The specific sub-components are:
● Snow Load Index
● Snow Amount Index
● Ice Accumulation
● Blowing Snow Index
● Flash Freeze Index
● Ground Blizzard
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WSSI Snow Amount
[WPC-WSSI-SnowAmount]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Snow Amount indicates potential impacts due to the total amount of snow or the snow accumulation rate. This index also normalizes for climatology, such that regions of the country that experience, on average, less snowfall will show a higher level of severity for the same amount of snow that is forecast across a region that experiences more snowfall on average.
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WSSI Snow Load
[WPC-WSSI-SnowLoad]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Snow Load indicates potential infrastructure impacts due to the weight of the snow. This index accounts for the land cover type. For example, more forested and urban areas will show increased severity versus the same snow conditions in grasslands.
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IR Winds 250-100mb
[AMV-ULhigh]
AMV: Upper Level IR/WV (100-250mb)
AMV: Upper Level IR/WV (100-250mb)
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IR Winds 350-251mb
[AMV-ULmid]
AMV: Upper Level IR/WV (251-350mb)
AMV: Upper Level IR/WV (251-350mb)
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IR Winds 500-351mb
[AMV-ULlow]
AMV: Upper Level IR/WV (351-500mb)
AMV: Upper Level IR/WV (351-500mb)
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Vis Winds 800-700mb
[AMV-VISmid]
AMV: Middle Level Visible (700-800mb)
AMV: Middle Level Visible (700-800mb)
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Vis Winds 925-801mb
[AMV-VISlow]
AMV: Lower Level Visible (801-925mb)
AMV: Lower Level Visible (801-925mb)
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Snow Depth (SNODAS)
[SNODAS-Thickness]
SNODAS (SNOw Data Assimilation System) is a modeling and data assimilationsystem developed by NOAA National Weather Service"s NOHRSC (National Operational Hydrologic Remote Sensing Center) to provide the best possible...
SNODAS (SNOw Data Assimilation System) is a modeling and data assimilation system developed by NOAA National Weather Service"s NOHRSC (National Operational Hydrologic Remote Sensing Center) to provide the best possible estimates of snow cover and associated parameters to support hydrologic modeling and analysis. The aim of SNODAS is to provide a physically consistent framework to integrate snow data from satellite, airborne platforms, and ground stations with model estimates of snow cover. The 24hr Snow Thickness is a daily snapshot of snow thickness at 0600hr UTC.
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Snowfall Total - 24hr (SNODAS)
[SNODAS-Accumulate]
SNODAS (SNOw Data Assimilation System) is a modeling and data assimilationsystem developed by NOAA National Weather Service"s NOHRSC (National Operational Hydrologic Remote Sensing Center) to provide the best possible...
SNODAS (SNOw Data Assimilation System) is a modeling and data assimilation system developed by NOAA National Weather Service"s NOHRSC (National Operational Hydrologic Remote Sensing Center) to provide the best possible estimates of snow cover and associated parameters to support hydrologic modeling and analysis. The aim of SNODAS is to provide a physically consistent framework to integrate snow data from satellite, airborne platforms, and ground stations with model estimates of snow cover. 24hr Snow Fall Total is calculated every 24 hours at 0600hr UTC and posted shortly thereafter.
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Winter Weather Hazards (Issued)
[WWINTER]
Winter Weather is a collection of Hazards associated with all types ofWinter precip and conditions. Hazards are issued by the NWS WSFOs as Advisories, Watches and Warnings. SnowEvents include SnowStorm,...
Winter Weather is a collection of Hazards associated with all types of Winter precip and conditions. Hazards are issued by the NWS WSFOs as Advisories, Watches and Warnings. SnowEvents include SnowStorm, WinterStorm, Snow, HeavySnow, LakeEffectSnow and BlowingSnow. IceEvents include Sleet, HeavySleet, FreezingRain, IceStorm and FreezingFog. Click on objects to get a detailed description of the specific hazard.
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Winter Weather Hazards (Valid)
[XWINTER]
The National Weather Service issues a variety of Winter Weather warnings,watches and advisories. The event type is indicated on the map by different colors. This product contains Winter Weather Hazards VALID for a 48hr...
The National Weather Service issues a variety of Winter Weather warnings, watches and advisories. The event type is indicated on the map by different colors. This product contains Winter Weather Hazards VALID for a 48hr Window spanning from the previous 24hrs to 24hrs in the future at 1hr increments.
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Snow Fall Rate
[NESDIS-SnowFallRate]
AMSU Snow Fall Rate Global by NOAA-NESDIS
AMSU Snow Fall Rate Global by NOAA-NESDIS
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Freezing Rain Probability >= .25" Final Forecast
[WPC-picezgt25]
The Probability of Freezing Rain Accumulating ≥ .25" Days 1-3
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The Probability of Freezing Rain Accumulating ≥ .25" Days 1-3
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
The product depicts the probability of freezing rain reaching or exceeding 0.25 inch for Days 1-3.
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Freezing Rain Probability >= 0.01"/24h
[WPC-picez24gep01]
The 24-Hour Probability of Freezing Rain Accumulating ≥ .01"
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The 24-Hour Probability of Freezing Rain Accumulating ≥ .01"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Freezing Rain Probability >= 0.10"/24h
[WPC-picez24gep10]
The 24-Hour Probability of Freezing Rain Accumulating ≥ .10"
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The 24-Hour Probability of Freezing Rain Accumulating ≥ .10"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Freezing Rain Probability >= 0.25"/24h
[WPC-picez24gep25]
The 24-Hour Probability of Freezing Rain Accumulating ≥ .25"
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The 24-Hour Probability of Freezing Rain Accumulating ≥ .25"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Freezing Rain Probability >=0.50"/24h
[WPC-picez24gep50]
The 24-Hour Probability of Freezing Rain Accumulating ≥ .50"
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The 24-Hour Probability of Freezing Rain Accumulating ≥ .50"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Freezing Rain Probability >=1.00"/24h
[WPC-picez24ge1]
The 24-Hour Probability of Freezing Rain Accumulating ≥ 1.00"
Theoperational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h...
The 24-Hour Probability of Freezing Rain Accumulating ≥ 1.00"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Midwest Winter Road Conditions
[ROADS-IADOT]
Conditions are updated every 10 minutes during the winter season (October15 to April 15) and on an as-needed basis during the non-winter months. Layer and service is maintained by the Iowa DOT GIS team on behalf of the...
Conditions are updated every 10 minutes during the winter season (October 15 to April 15) and on an as-needed basis during the non-winter months. Layer and service is maintained by the Iowa DOT GIS team on behalf of the Office of Traffic Operations. This data is provided as is through this value added REST service. All conditions have been remapped to the best of our ability to meet the condition reporting criteria as defined by the Iowa DOT. Some discrepancies may appear. This data service should only be used for reference only. For the most accurate information, please utilize the authoritative state 511 sites below.
State 511 Sites 511 Vendor Disclaimers
North Dakota Iteris The data is provided as is and without liability from the North Dakota Department of Transportation (NDDOT). The NDDOT does not guarantee this data to be free from errors, or inaccuracies, and disclaims any responsibility or liability for interpretations or decisions based on this data.
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Snowfall Reports - 6hr
[lsr-snow]
NWS reported 6hr Snowfall Totals (inches).
NWS reported 6hr Snowfall Totals (inches).
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Snow Probability >= 0.1"/24h
[WPC-psnow24gep1]
24Hour Probability of Snow Accumulating ≥.1"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥.1"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 1.0"/24h
[WPC-psnow24ge1]
24Hour Probability of Snow Accumulating ≥1"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥1"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 2.0"/24h
[WPC-psnow24ge2]
24Hour Probability of Snow Accumulating ≥2"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥2"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 4.0"/24h
[WPC-psnow24ge4]
24Hour Probability of Snow Accumulating ≥4"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥4"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 6.0"/24h
[WPC-psnow24ge6]
24Hour Probability of Snow Accumulating ≥6"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥6"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 8.0"/24h
[WPC-psnow24ge8]
24Hour Probability of Snow Accumulating ≥8"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥8"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 12.0"/24h
[WPC-psnow24ge12p0]
24Hour Probability of Snow Accumulating ≥12"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥12"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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Snow Probability >= 18.0"/24h
[WPC-psnow24ge18p0]
24Hour Probability of Snow Accumulating ≥18"
The operational WPC WinterWeather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending...
24Hour Probability of Snow Accumulating ≥18"
The operational WPC Winter Weather Desk (WWD) creates 24-h forecasts of snowfall and freezing rain accumulations for each of three consecutive 24-h periods (days) extending 72 hours into the future. These products are shared with the NWS Weather Forecast Offices (WFO) in a collaborative process resulting in refinement of the accumulation forecasts. After the 24-h snowfall and freezing rain accumulation forecasts are finalized, the WWD issues its public products: a limited suite of probabilistic winter weather forecasts. These probabilistic forecasts are computed based on the deterministic accumulation forecasts combined with ensemble information.
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WSSI Blowing Snow
[WPC-WSSI-BlowingSnow]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Blowing Snow Index Indicates the potential disruption due to blowing and drifting snow. This index accounts for land use type. For example, more densely forested areas will show less blowing snow than open grassland areas.
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WSSI Flash Freeze
[WPC-WSSI-FlashFreeze]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Flash Freeze Index Indicates the potential impacts of flash freezing (temperatures starting above freezing and quickly dropping below freezing) during or after precipitation events
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WSSI Ground Blizzard
[WPC-WSSI-Blizzard]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Ground Blizzard indicates the potential travel-related impacts of strong winds interacting with
pre-existing snow cover. This is the only sub-component that does not require snow to be forecast in order for calculations to be made. The NOHRSC snow cover data along with forecast winds are used to model the ground blizzard.
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WSSI Ice Accumulation
[WPC-WSSI-IceAccum]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Ice Accumulation indicates potential infrastructure impacts (e.g. roads/bridges) due to combined effects and severity of ice and wind. Designated urban areas are also weighted a little more than non-urban areas. Please note that not all NWS offices provide ice accumulation information into the NDFD. In those areas, the ice accumulation is not calculated.
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WSSI Overall Impact
[WPC-WSSI]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
The Overall WSSI Impact value is the maximum value from all the sub-components. The specific sub-components are:
● Snow Load Index
● Snow Amount Index
● Ice Accumulation
● Blowing Snow Index
● Flash Freeze Index
● Ground Blizzard
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WSSI Snow Amount
[WPC-WSSI-SnowAmount]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Snow Amount indicates potential impacts due to the total amount of snow or the snow accumulation rate. This index also normalizes for climatology, such that regions of the country that experience, on average, less snowfall will show a higher level of severity for the same amount of snow that is forecast across a region that experiences more snowfall on average.
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WSSI Snow Load
[WPC-WSSI-SnowLoad]
The WSSI is created by screening the official National Weather Servicegridded forecasts from the National Digital Forecast Database (NDFD) for winter weather elements and combining those data with non-meteorological or...
The WSSI is created by screening the official National Weather Service gridded forecasts from
the National Digital Forecast Database (NDFD) for winter weather elements and combining
those data with non-meteorological or static information datasets (e.g., climatology, land-use,
urban areas). This process creates a graphical depiction of anticipated overall impacts to
society due to winter weather. NWS has implemented the WSSI to provide the public with a tool that attempts to convey the complexities and hazards associated with winter storms as they relate to potential societal impacts.
Snow Load indicates potential infrastructure impacts due to the weight of the snow. This index accounts for the land cover type. For example, more forested and urban areas will show increased severity versus the same snow conditions in grasslands.
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2015 WI NAIP Counties
[wi-counties]
This layer displays Wisconsin county outlines. Right-click-probe allowsdownloads of source imagery for the 2015 Wisconsin NAIP aerial photography county mosaics.
This layer displays Wisconsin county outlines. Right-click-probe allows downloads of source imagery for the 2015 Wisconsin NAIP aerial photography county mosaics.
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2015 WI NAIP DOQQs
[NAIPWI2015fp]
This layer displays the coverage footprints for the 2015 Wisconsin NAIPaerial photography. Right-click probe allows downloads of source imagery.
This layer displays the coverage footprints for the 2015 Wisconsin NAIP aerial photography. Right-click probe allows downloads of source imagery.
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Infrared 6 inch Imagery of Madison
[madisonir]
Infrared 6 inch Imagery of Madison
Infrared 6 inch Imagery of Madison
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NAIP WI
[NAIPWI]
National Agricultural Imagery Program aerial photography from the WisconsinFarm Service Agency (WI-FSA) of the USDA.
National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA.
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NAIP WI Color Infrared
[NAIPWICIR]
National Agricultural Imagery Program aerial photography from the WisconsinFarm Service Agency (WI-FSA) of the USDA (Color Infrared)
National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA (Color Infrared)
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WI Coastal Imagery
[WICoast]
WI Coastal Imagery displays aerial photographs of the Lake Michigan coastof Wisconsin from 2007. The images are being used to monitor cladophora algae growth.
WI Coastal Imagery displays aerial photographs of the Lake Michigan coast of Wisconsin from 2007. The images are being used to monitor cladophora algae growth.
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WI Coastal Shaded Relief
[WIcoastalshdrlf]
WI coastal shaded relief map generated from LiDAR data.
WI coastal shaded relief map generated from LiDAR data.
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WI Lake Clarity
[LakesTSI]
These data represent the estimated clarity, or transparency, of the 8,000largest of those lakes as measured by satellite remote sensing (Landsat).
These data represent the estimated clarity, or transparency, of the 8,000 largest of those lakes as measured by satellite remote sensing (Landsat).
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WISCLAND 1993
[wiscland]
In 1993 a team of researchers from University of Wisconsin-Madison (ERSC)and the Wisconsin DNR developed WISCLAND, the first satellite-derived land cover map of Wisconsin. The UW-Madison (SCO) and the DNR partnered on a...
In 1993 a team of researchers from University of Wisconsin-Madison (ERSC) and the Wisconsin DNR developed WISCLAND, the first satellite-derived land cover map of Wisconsin. The UW-Madison (SCO) and the DNR partnered on a project to produce an updated land cover map of Wisconsin. The resulting dataset, known as Wiscland 2.0, was completed in August 2016.
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Wisconsin in 3D (SRTM)
[wisc-3d]
The Space Shuttle Endeavour collected data to produce a digital elevationmodel of the Earth during the Shuttle Radar Topography Mission (SRTM), flown from February 11-22, 2000. Researchers clipped Wisconsin from this...
The Space Shuttle Endeavour collected data to produce a digital elevation model of the Earth during the Shuttle Radar Topography Mission (SRTM), flown from February 11-22, 2000. Researchers clipped Wisconsin from this data to produce this 3D anaglyph. To see the 3D effect, use Red-Blue 3D glasses (red over left eye).
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Wisconsin LIDAR Hillshade
[wi-hillshade]
WisconsinView is a remote sensing consortium and member of AmericaView.org.These Wisconsin lidar data sets were collected by aircraft and processed by state and county agencies. These data are hosted by WisconsinView and...
WisconsinView is a remote sensing consortium and member of AmericaView.org. These Wisconsin lidar data sets were collected by aircraft and processed by state and county agencies. These data are hosted by WisconsinView and visualized here with coordination and funding from the WI State Dept. of Administration, Geographic Information Office and NOAA"s coastal management program.
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WI USGS Landsat Poster
[wilandsat]
This is a georeferenced poster from the USGS. The original source is:http://eros.usgs.gov/imagegallery/landsat-state-mosaics unfortunately the original poster imagery without graphics burned-in is not available.
This is a georeferenced poster from the USGS. The original source is: http://eros.usgs.gov/imagegallery/landsat-state-mosaics unfortunately the original poster imagery without graphics burned-in is not available.
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