[CA-MODIS-Terra-123-True]

CaliforniaView: True color 250m MODIS image on May 3rd, 2022

[COView721]

COView721

[coview-721]

coview-721

[DelawareView-Landsat]

DelawareView-Landsat

[ksview-721-bands]

ksview-721-bands

[landsat-1-madison-321]

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)

[LandsatNY]

LandsatNY

[MI-721]

MI-721

[MICHIGAN]

MICHIGAN

[Montana]

Montana

[OhioView-MODIS-FalseColor]

OhioView-MODIS-FalseColor

[OhioView-MODIS-TrueColor]

OhioView-MODIS-TrueColor

[OhioView-TrueColor]

OhioView-TrueColor

[wvview-143-true-color]

wvview-143-true-color

[NWS-Alerts-All]

All NWS Alerts

[NWS-Alerts-Warnings]

Watches and warnings from NWS

[landsat-1-madison-321]

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)

[BOM-Root-Zone-Soil-Moisture]

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.

[CIMSS-CTCtargets]

CIMSS-Cloud Top Cooling targets

[AIRMET-ICE]

AIRMET Icing Advisory

[AIRMET-IFR]

AIRMET-IFR Advisory

[AIRMET-MTN]

AIRMET-Mountain Obscured Advisory

[TAF]

Terminal Aerodrome Forecast (TAF)

[AIRMET-TURB]

AIRMET-Turlulence Advisory

[VAA]

Volcanic Ash Advisories: Ash Clouds

[BRDF]

MODIS Clear View ConUS Composite. BRDF (Bidirectional Reluctance Distribution Function) is a 16-day cloud-free composite.

[VIIRS-Fire-RGB-CIRA]

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.

[VIIRS-Fire-Temp-RGB-CIRA]

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.

[VIIRS-Fire-Temp-RGB-375-CIRA]

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.

[cimssdpicapeli]

CIMSS-DPI Convective Available Potential Energy (Li et al. 2008)

[conusiravn]

GOES IR Aviation

[conusirbd]

GOES IR Dvorak

[conusirfunk]

GOES IR Funk Top

[conusirott]

GOES IR Overshooting Tops

[conusirnhc]

GOES IR Rainbow

[cimssdpilili]

GOES-DPI Lifted Index (Li et al. 2008)

[cimssdpiozli]

GOES-DPI Ozone (Li etal 2008)

[cimssdpipwli]

CIMSS-DPI Precipitable Water (mm)

[mean-snow-cover-1988-2017]

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.

[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 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.

[j01-ist]

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.

[j01-ithk]

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.

[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 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.

[snpp-ist]

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.

[snpp-ithk]

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.

[Eclipse]

Eclipse Path

[AFIMG-Points]

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.

[RAQDPS-COL-Diff-25]

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.

[HRRR-smoke-surface]

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.

[HRRR-smoke-column]

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.

[RAP-smoke-surface]

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.

[RAP-smoke-column]

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.

[ERTA-NCEP]

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

[WFLASH]

Flash Flood Hazards

[FOP]

WPC FLood Outlook Product

[FLOODWARN]

Flood Warning Polygons

[XFLOODWARN]

XFLOODWARN

[HVTEC]

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.

[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, 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

[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, 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

[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, 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

[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, 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

[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, 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

[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, 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

[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, 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

[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 represent a composite of all available VIIRS daylight imagery over the past 1 day. For more information visit: Here

[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 represent a composite of all available VIIRS daylight imagery over the past 5 days. For more information visit: Here

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[VIIRS-3Dflood]

VIIRS downscaling software is designed to downscale the VIIRS 375-m flood products to 30-m flood products. The software uses Suomi-NPP

[lsat8-llook-fc]

View of lsat8-llook-fc-scenes

[lsat8-llook-tir]

View of lsat8-llook-tir-scenes

[wrs2-land]

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.

[lsat9-llook-fc]

View of lsat9-llook-fc-scenes

[lsat9-llook-tir]

View of lsat9-llook-tir-scenes

[HRR-CONUS-FZRN-SFC]

HRRR ConUS Latest Freezing MASK

[HRR-CONUS-ICEP-SFC]

HRRR ConUS Latest Ice Mask

[HRR-CONUS-PCP-LATEST]

View of HRR-CONUS-PCP-SFC

[HRR-CONUS-RAIN-SFC]

HRRR ConUS Latest Rain Mask

[HRR-CONUS-PCP-SFC]

HRR-CONUS-PCP-SFC

[HRR-CONUS-RADAR-LATEST]

View of HRR-CONUS-PCP-SFC

[HRR-CONUS-SNOW-SFC]

HRRR ConUS Latest Snow Mask

[RAP-CONUS-PRAT-SFC-DBZ]

View of RAP-CONUS-PRAT-SFC

[TAF]

Terminal Aerodrome Forecast (TAF)

[nppdnb]

NPP Day/Night Band - Dynamic

[AFIMG-Points]

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.

[GOES-W-CONUS-IR]

GOES 15 ConUS IR

[GOES-W-CONUS-LWIR]

GOES 15 ConUS LWIR

[GOES-W-CONUS-NIR]

GOES 15 ConUS NIR

[GOES-W-CONUS-VIS]

GOES 15 ConUS VIS

[GOES-W-CONUS-WV]

GOES 15 ConUS WV

[GOES-W-FD-IR]

GOES 15 Full Disk IR (Infrared)

[GOES-W-FD-LWIR]

GOES 15 Full Disk LWIR (Long Wave Infrared)

[GOES-W-FD-NIR]

GOES 15 Full Disk NIR (Near Infrared)

[GOES-W-FD-VIS]

GOES 15 Full Disk VIS (Visible)

[GOES-W-FD-WV]

GOES 15 Full Disk WV (Water Vapor)

[GOES-16SandwichCONUS]

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.

[goes-east-conus-band-2-cira]

[goes-east-conus-band-7-cira]

[goes-east-conus-band-13-cira]

[NGFS-DAILY-CONUS-EAST]

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.

[goes-east-conus-day-fire-rgb]

This product is uploaded directly to RealEarth every 5-minutes by CIRA. More info to follow.

[goes-east-conus-day-microphy-rgb-cira]

[goes-east-conus-FDCC]

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.

[NGFS-EVENTS-CONUS-EAST]

[goes-east-conus-fire-temp-rgb]

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.

[goes-east-conus-GeoColor-cira]

[NGFS-SCENE-CONUS-EAST]

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.

[G16-ABI-CONUS-BAND02]

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.

[G16-ABI-CONUS-BAND03]

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.

[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. 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.

[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. 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.

[G16-ABI-CONUS-BAND09]

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.

[G16-ABI-CONUS-BAND09-VAPR]

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.

[G16-ABI-CONUS-BAND13]

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.

[G16-ABI-CONUS-BAND13-GRAD]

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.

[G16-ABI-CONUS-TC]

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.

[G16-ABI-FD-FLS-Thickness]

Cloud thickness: Estimate of the geometric thickness (cloud top - cloud base) of a single layer liquid water stratus cloud.

[G16-ABI-FD-FLS-IFR]

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.

[G16-ABI-FD-FLS-LIFR]

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.

[G16-ABI-FD-FLS-MVFR]

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.

[GOES-16-SA-Sandwich]

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.

[glmgroupdensity]

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.

[glmgrouppoints]

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.

[G16-ABI-FD-BAND02]

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.

[G16-ABI-FD-BAND03]

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.

[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. 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.

[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. 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.

[G16-ABI-FD-BAND09]

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.

[G16-ABI-FD-BAND09-VAPR]

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.

[G16-ABI-FD-BAND13]

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.

[G16-ABI-FD-BAND13-GRAD]

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.

[G16-ABI-FD-TC]

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.

[GOES-16SandwichMESO1]

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.

[goes-east-meso1-band-2-cira]

[goes-east-meso1-band-7-cira]

[goes-east-meso1-band-13-cira]

[goes-east-meso1-day-fire-rgb]

This product is uploaded directly to RealEarth every minute by CIRA. More info to follow.

[goes-east-meso1-day-microphy-rgb-cira]

[goes-east-meso1-fire-temp-rgb]

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.

[goes-east-meso1-GeoColor-cira]

[NGFS-SCENE-Mesoscale1-EAST]

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.

[G16-ABI-MESO1-BAND02]

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.

[G16-ABI-MESO1-BAND03]

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.

[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. 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.

[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. 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.

[G16-ABI-MESO1-BAND09]

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.

[G16-ABI-MESO1-BAND09-VAPR]

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.

[G16-ABI-MESO1-BAND13]

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.

[G16-ABI-MESO1-BAND13-GRAD]

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.

[G16-ABI-MESO1-BAND13-RED]

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.

[G16-ABI-MESO1-TC]

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.

[GOES-16SandwichMESO2]

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.

[goes-east-meso2-band-2-cira]

[goes-east-meso2-band-7-cira]

[goes-east-meso2-band-13-cira]

[goes-east-meso2-day-fire-rgb]

This product is uploaded directly to RealEarth every minute by CIRA. More info to follow.

[goes-east-meso2-day-microphy-rgb-cira]

[goes-east-meso2-fire-temp-rgb]

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.

[goes-east-meso2-GeoColor-cira]

[NGFS-SCENE-Mesoscale2-EAST]

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.

[G16-ABI-MESO2-BAND02]

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.

[G16-ABI-MESO2-BAND03]

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.

[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. 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.

[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. 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.

[G16-ABI-MESO2-BAND09]

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.

[G16-ABI-MESO2-BAND09-VAPR]

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.

[G16-ABI-MESO2-BAND13]

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.

[G16-ABI-MESO2-B13-CYAN]

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.

[G16-ABI-MESO2-BAND13-GRAD]

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.

[G16-ABI-MESO2-TC]

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.

[wscsTag20230809]

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.

[goes-west-conus-band-2-cira]

[goes-west-conus-band-7-cira]

[goes-west-conus-band-13-cira]

[NGFS-DAILY-CONUS-WEST]

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.

[goes-west-conus-day-fire-rgb]

This product is uploaded directly to RealEarth every 5-minutes by CIRA. More info to follow.

[goes-west-conus-day-microphy-rgb-cira]

[goes-west-conus-FDCC]

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.

[NGFS-EVENTS-CONUS-WEST]

[goes-west-conus-fire-temp-rgb]

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.

[goes-west-conus-GeoColor-cira]

[NGFS-SCENE-CONUS-WEST]

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.

[G18-ABI-CONUS-BAND02]

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.

[G18-ABI-CONUS-BAND03]

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.

[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. 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.

[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. 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.

[G18-ABI-CONUS-BAND09]

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.

[G18-ABI-CONUS-BAND09-VAPR]

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.

[G18-ABI-CONUS-BAND13]

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.

[G18-ABI-CONUS-BAND13-GRAD]

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.

[G18-ABI-FD-FLS-Thickness]

Cloud thickness: Estimate of the geometric thickness (cloud top - cloud base) of a single layer liquid water stratus cloud.

[G18-ABI-FD-FLS-IFR]

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.

[G18-ABI-FD-FLS-LIFR]

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.

[G18-ABI-FD-FLS-MVFR]

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.

[G18-ABI-FD-BAND02]

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.

[G18-ABI-FD-BAND03]

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.

[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. 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.

[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. 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.

[G18-ABI-FD-BAND09]

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.

[G18-ABI-FD-BAND09-VAPR]

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.

[G18-ABI-FD-BAND13]

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.

[G18-ABI-FD-BAND13-GRAD]

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.

[goes-west-meso1-band-2-cira]

[goes-west-meso1-band-7-cira]

[goes-west-meso1-band-13-cira]

[goes-west-meso1-day-fire-rgb]

This product is uploaded directly to RealEarth every minute by CIRA. More info to follow.

[goes-west-meso1-day-microphy-rgb-cira]

[goes-west-meso1-fire-temp-rgb]

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.

[goes-west-meso1-GeoColor-cira]

[NGFS-SCENE-Mesoscale1-WEST]

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.

[G18-ABI-MESO1-BAND02]

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.

[G18-ABI-MESO1-BAND03]

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.

[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. 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.

[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. 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.

[G18-ABI-MESO1-BAND09]

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.

[G18-ABI-MESO1-BAND09-VAPR]

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.

[G18-ABI-MESO1-BAND13]

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.

[G18-ABI-MESO1-BAND13-GRAD]

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.

[G18-ABI-MESO1-BAND13-GREEN]

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.

[goes-west-meso2-band-2-cira]

[goes-west-meso2-band-7-cira]

[goes-west-meso2-band-13-cira]

[goes-west-meso2-day-fire-rgb]

This product is uploaded directly to RealEarth every minute by CIRA. More info to follow.

[goes-west-meso2-day-microphy-rgb-cira]

[goes-west-meso2-fire-temp-rgb]

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.

[goes-west-meso2-GeoColor-cira]

[NGFS-SCENE-Mesoscale2-WEST]

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.

[G18-ABI-MESO2-BAND02]

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.

[G18-ABI-MESO2-BAND03]

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.

[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. 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.

[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. 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.

[G18-ABI-MESO2-BAND09]

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.

[G18-ABI-MESO2-BAND09-VAPR]

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.

[G18-ABI-MESO2-BAND13]

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.

[G18-ABI-MESO2-BAND13-GRAD]

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.

[G18-ABI-MESO2-BAND13-YELLOW]

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.

[cimssdpicapeli]

CIMSS-DPI Convective Available Potential Energy (Li et al. 2008)

[conusiravn]

GOES IR Aviation

[conusirbd]

GOES IR Dvorak

[conusirfunk]

GOES IR Funk Top

[conusirott]

GOES IR Overshooting Tops

[conusirnhc]

GOES IR Rainbow

[cimssdpilili]

GOES-DPI Lifted Index (Li et al. 2008)

[cimssdpiozli]

GOES-DPI Ozone (Li etal 2008)

[cimssdpipwli]

CIMSS-DPI Precipitable Water (mm)

[NESDIS-GHE-HourlyRainfall]

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.

[AMV-ULhigh]

AMV: Upper Level IR/WV (100-250mb)

[AMV-ULmid]

AMV: Upper Level IR/WV (251-350mb)

[AMV-ULlow]

AMV: Upper Level IR/WV (351-500mb)

[AMV-LLhigh]

AMV: 400-599mb Low Level IR winds

[AMV-LLmid]

AMV: Lower Level IR (600-799mb)

[AMV-LLlow]

AMV: Lower Level IR (800-950mb)

[AMV-VISmid]

AMV: Middle Level Visible (700-800mb)

[AMV-VISlow]

AMV: Lower Level Visible (801-925mb)

[NESDIS-GHE-HourlyRainfall]

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.

[AMV-ULhigh]

AMV: Upper Level IR/WV (100-250mb)

[AMV-ULmid]

AMV: Upper Level IR/WV (251-350mb)

[AMV-ULlow]

AMV: Upper Level IR/WV (351-500mb)

[AMV-LLhigh]

AMV: 400-599mb Low Level IR winds

[AMV-LLmid]

AMV: Lower Level IR (600-799mb)

[AMV-LLlow]

AMV: Lower Level IR (800-950mb)

[NESDIS-SST]

NESDIS: Hi-Res Sea Surface Temperature

[AMV-VISmid]

AMV: Middle Level Visible (700-800mb)

[AMV-VISlow]

AMV: Lower Level Visible (801-925mb)

[globalir]

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.

[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 current imagery, shifting occurs along composite seams.

[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 current imagery, shifting occurs along composite seams.

[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 current imagery, shifting occurs along composite seams.

[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 current imagery, shifting occurs along composite seams.

[globalir-rr]

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.

[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 current imagery, shifting occurs along composite seams.

[globalvis]

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.

[globalvis-tsp]

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.

[global1kmvis]

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.

[global1kmvisfull]

[globalwv]

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.

[globalwv-grad]

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.

[clad]

Estimate of 2005 algae extent along coastal Lake Michigan.

[GLERL-ICE]

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

[GLERL-GLSEAimage]

Great Lakes Surface Environmental Analysis (GLSEA) from GLERL. For more info see: http://coastwatch.glerl.noaa.gov/glsea/doc

[WICoast]

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.

[WIcoastalshdrlf]

WI coastal shaded relief map generated from LiDAR data.

[Earthquake-mag]

Earthquake Magnitude (Past 24hr)

[XREDFLAG]

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

[WFLASH]

Flash Flood Hazards

[FOP]

WPC FLood Outlook Product

[FLOODWARN]

Flood Warning Polygons

[XFLOODWARN]

XFLOODWARN

[HVTEC]

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.

[WFOG]

Fog Hazards

[Severe]

Tornado, Thunderstorm, Flash Flood and Marine Warning polygons.

[SAW]

Severe Weather Watch Box - Aviation

[WWTOR]

Tornado Watches and Warnings

[TSFCST]

National Hurricane Center Tropical Storm & Hurricane Forecast

[VAA]

Volcanic Ash Advisories: Ash Clouds

[WWIND]

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.

[WWINTER]

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.

[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 Window spanning from the previous 24hrs to 24hrs in the future at 1hr increments.

[RVER-ICEC-MB]

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)

[RVER-ICEC-NC]

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)

[RVER-ICEC-NE]

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)

[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 represent a composite of all available VIIRS daylight imagery over the past 1 day. For more information visit: Here

[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 represent a composite of all available VIIRS daylight imagery over the past 5 days. For more information visit: Here

[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 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

[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 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

[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 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

[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, 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[RIVER-ICE-AP]

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

[RIVER-ICE-MB]

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)

[RIVER-ICE-NC]

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)

[RIVER-ICE-NE]

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)

[madisonir]

Infrared 6 inch Imagery of Madison

[NAIPWI]

National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA.

[NAIPWICIR]

National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA (Color Infrared)

[WIcoastallidar]

WI Coastal LiDAR

[WIcoastalshdrlf]

WI coastal shaded relief map generated from LiDAR data.

[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 visualized here with coordination and funding from the WI State Dept. of Administration, Geographic Information Office and NOAA"s coastal management program.

[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.

[HIMAWARI-B03]

Himawari AHI Full Disk B03 Hi-Res "Red" Visible

[HIMAWARI-B04]

Himawari AHI Full Disk B04 "Veggie"

[HIMAWARI-B07]

Himawari AHI Full Disk B07 "Fire"

[HIMAWARI-B07-FIRE]

View of HIMAWARI-B07

[HIMAWARI-B09]

Himawari AHI Full Disk B09 Mid-level Water Vapor

[HIMAWARI-B09-VAPR]

View of HIMAWARI-09

[HIMAWARI-B13]

Himawari AHI Full Disk B13 "Clean" Infrared

[HIMAWARI-B13-GRAD]

View of HIMAWARI-B13

[H-DayConvectiveStorm-cve]

Himawari AHI Full Disk Day Convective Storm (ave)

[H-DayMicrophysics-dms]

Himawari AHI Full Disk Day Microphysics (dms)

[H-Dust-dst]

Himawari AHI Full Disk Dust (dst)

[H-NaturalColor-dnc]

Himawari AHI Full Disk Natural Color (dnc)

[H-NightMicrophysics-ngt]

Himawari AHI Full Disk Night Microphysics (nms)

[H-24hrAirMass-arm]

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.

[H-SnowFog-dsl]

Himawari AHI Full Disk Snow and Fog (dsl)

[H-TrueColor-wgt]

Himawari AHI Full Disk True Color (wgt)

[HIMAWARI-JP-B03]

Himawari AHI Japan B03 Hi-Res "Red" Visible

[HIMAWARI-JP-B07]

Himawari AHI Japan Bo7 "Fire"

[HIMAWARI-JP-B07-FIRE]

View of HIMAWARI-JP-B07

[HIMAWARI-JP-B09]

Himawari AHI Japan B09 Mid-level Water Vapor

[HIMAWARI-JP-B09-VAPR]

View of HIMAWARI-JP-B09

[HIMAWARI-JP-B14]

Himawari AHI Japan B14 Infrared

[HIMAWARI-JP-B14-GRAD]

View of HIMAWARI-JP-B14

[HIMAWARI-T1-B03]

Himawrai AHI Target B03 Hi-Res "Red" Visible

[HIMAWARI-T1-B07]

Himawari AHI Target B07 "Fire"

[HIMAWARI-T1-B07-FIRE]

View of HIMAWARI-T1-B07

[HIMAWARI-T1-B14]

Himawari AHI Target B14 Infrared

[HIMAWARI-T1-B14-GRAD]

Himawari AHI Target B14 Infrared enhanced

[HIMAWARI-T1-B09]

Himawari AHI Target Mid-level Water Vapor

[HIMAWARI-T1-B09-VAPR]

Himawari AHI Target Mid-level Water Vapor enhanced

[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 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

[VIIRS-3Dflood]

VIIRS downscaling software is designed to downscale the VIIRS 375-m flood products to 30-m flood products. The software uses Suomi-NPP

[ICE-COMP-MB]

[ICE-COMP-NC]

[ICE-COMP-NE]

[RVER-ICEC-MB]

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)

[RVER-ICEC-NC]

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)

[RVER-ICEC-NE]

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)

[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 represent a composite of all available VIIRS daylight imagery over the past 1 day. For more information visit: Here

[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 represent a composite of all available VIIRS daylight imagery over the past 5 days. For more information visit: Here

[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, 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

[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, 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

[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, 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

[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, 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

[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, 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

[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 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

[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 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

[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, 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

[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, 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[RIVER-ICE-AP]

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

[RIVER-ICE-MB]

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)

[RIVER-ICE-NC]

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)

[RIVER-ICE-NE]

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)

[MADIS-dewt]

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/.

[MIRS-BT90]

MIRS 90Ghz Brightness Temperature

[MIRS-RainRate]

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.

[nppadpam]

NPP Day/Night AM Composite - Adaptive

[nppdnbdyn-hnl]

NPP Day/Night Band (DNB) - Honolulu DB

[nppdnb]

NPP Day/Night Band - Dynamic

[nppfc]

NPP False Color

[AQUA-AER]

MODIS: AQUA Aerosol Optical Depth (ta)

[aquafalsecolor]

CIMSS-MODIS Satellite False Color (Aqua)

[VIIRS-MASK-54000x27000]

VIIRS Night Global Black Marble by NASA

[NightLightsColored]

Global Night Lights (enhanced)

[TERRA-AER]

MODIS: TERRA Aerosol Optical Depth (ta)

[terrafalsecolor]

CIMSS-MODIS Satellite False Color (Terra)

[terratruecolor]

CIMSS-MODIS Satellite True Color (Terra)

[AURA-SO2]

AURA - OMI Total Column Sulphur Dioxide (SO2)

[BRDF]

MODIS Clear View ConUS Composite. BRDF (Bidirectional Reluctance Distribution Function) is a 16-day cloud-free composite.

[RVER-ICEC-MB]

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)

[RVER-ICEC-NC]

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)

[RVER-ICEC-NE]

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)

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[RIVER-ICE-AP]

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

[RIVER-ICE-MB]

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)

[RIVER-ICE-NC]

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)

[RIVER-ICE-NE]

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)

[Aguascalientes]

Aguascalientes

[BajaCalif]

BajaCalif

[BCS]

BCS

[Campeche]

Campeche

[CDMX]

CDMX

[Chiapas]

Chiapas

[Chihuahua]

Chihuahua

[Coahuila]

Coahuila

[Colima]

Colima

[Durango]

Durango

[EdoMex]

EdoMex

[Guanajuato]

Guanajuato

[Guerrero]

Guerrero

[Hidalgo]

Hidalgo

[Jalisco]

Jalisco

[Michoacan]

Michoacan

[Morelos]

Morelos

[Nayarit]

Nayarit

[NuevoL]

NuevoL

[Oaxaca]

Oaxaca

[Puebla]

Puebla

[Queretaro]

Queretaro

[QuintanaRoo]

QuintanaRoo

[SanLuisPotosi]

SanLuisPotosi

[Sinaloa]

Sinaloa

[Sonora]

Sonora

[Tabasco]

Tabasco

[Tamaulipas]

Tamaulipas

[Tlaxcala]

Tlaxcala

[Veracruz]

Veracruz

[Yucatan]

Yucatan

[Zacatecas]

Zacatecas

[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.

[lsat8-llook-fc]

View of lsat8-llook-fc-scenes

[lsat8-llook-tir]

View of lsat8-llook-tir-scenes

[lsat9-llook-fc]

View of lsat9-llook-fc-scenes

[lsat9-llook-tir]

View of lsat9-llook-tir-scenes

[wrs2-land]

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.

[glmgroupdensity-west]

[glmgroupdensity]

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.

[glmgrouppoints]

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.

[MIRS-BT90]

MIRS 90Ghz Brightness Temperature

[MIRS-RainRate]

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.

[MIRS-RainRate-AK]

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.

[AQUA-AER]

MODIS: AQUA Aerosol Optical Depth (ta)

[aquafalsecolor]

CIMSS-MODIS Satellite False Color (Aqua)

[TERRA-AER]

MODIS: TERRA Aerosol Optical Depth (ta)

[terrafalsecolor]

CIMSS-MODIS Satellite False Color (Terra)

[terratruecolor]

CIMSS-MODIS Satellite True Color (Terra)

[BRDF]

MODIS Clear View ConUS Composite. BRDF (Bidirectional Reluctance Distribution Function) is a 16-day cloud-free composite.

[Met8-SEVIRI-FD-BAND01]

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.

[Met8-SEVIRI-FD-BAND04]

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.

[Met8-SEVIRI-FD-BAND05]

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).

[Met8-SEVIRI-FD-BAND09]

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).

[Met8-SEVIRI-FD-BAND09-enh]

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).

[Met8-SEVIRI-HRV-BAND12]

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.

[Met11-SEVIRI-FD-BAND01]

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.

[Met11-SEVIRI-FD-BAND04]

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.

[Met11-SEVIRI-FD-BAND05]

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).

[Met11-SEVIRI-FD-BAND09]

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).

[Met11-SEVIRI-FD-BAND09-enh]

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).

[Met11-SEVIRI-HRV-BAND12]

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.

[NAIPWI]

National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA.

[NAIPWICIR]

National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA (Color Infrared)

[SCIT-ALL]

Storm Cell Identification and Tracking (SCIT) Filters 1| ALL Cells 2| Moderate Threat level Cells 3| Severe Threat level Cells

[SCIT-MOD]

Storm Cell Identification and Tracking (SCIT) Filters 1| ALL Cells 2| Moderate Threat level Cells 3| Severe Threat level Cells

[SCIT-SEV]

Storm Cell Identification and Tracking (SCIT) Filters 1| ALL Cells 2| Moderate Threat level Cells 3| Severe Threat level Cells

[SCIT-MOD-FCST]

Storm Cell Identification and Tracking (SCIT) Filter2 - 15min Forecast Trajectories 1| ALL Cells 2| Moderate Threat level Cells 3| Severe Threat level Cells

[nexrrain]

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.

[nexrhhc-phase]

View of nexrhhc

[nexrhres]

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.

[nexrstorm]

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.

[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)

[NEXRAD-Guam]

NEXRAD Guam Base Reflectivity

[NEXRAD-Hawaii]

NEXRAD Hawaii Base Reflectivity

[NEXRAD-PuertoRico]

WSR 88D NEXRAD Radar Base Reflectivity Tilt 1 for San Juan, Puerto Rico

[c2accum1dy]

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).

[c2accum1hr]

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).

[c2accum7dy]

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).

[SNOWDEPTH24]

24hr SnowDepth (in)

[SNOWFALL24]

24hr SnowFall (in)

[Fronts]

NCEP Frontal Analysis: fronts and troughs

[HighLow]

NCEP Frontal Analysis: Highs and Lows

[SSEC-METAR]

Global METAR

[PIREP]

PIREP

[SSEC-ShipBuoy]

Global Ship & Buoy

[SNODAS-Thickness]

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.

[SNODAS-Accumulate]

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.

[StormReports]

Storm Reports (last 3hrs)

[TAF]

Terminal Aerodrome Forecast (TAF)

[RgbAirMove]

[dnb-monthly-nightlights]

[aquatruecolor]

aquatruecolor

[BOM-Root-Zone-Soil-Moisture]

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.

[SPC-ConvOutlook-CATG]

SPC Convective Outlook - Categorical

[SPC-ConvOutlook-CATG-cmap]

View of SPC-ConvOutlook-CATG

[glmgroupdensity-west]

[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 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.

[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 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.

[landsat-example]

[NAM-CONUS-PRAT-SFC]

NAM-CONUS-PRAT-SFC

[NWS-Alerts-All]

All NWS Alerts

[PNPOINTALL]

PNPOINTALL

[PNTRACKALL]

PNTRACKALL

[usgs-ard-grid]

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.

[AKCAN-boundary]

[LCMETEOGRAMS]

[CURRENTNIFC]

LightningCast and GLM meteograms for current fire incidents.

[GOESEastGLMFEDRadC]

GOES-East flash-extent density, a 5-min accumulation of flashes at each point.

[GOESEastGLMMFARadC]

GOES-East minimum flash density

[GOESEastGLMTOERadC]

GOES-East total optical energy, in femto Joules (fJ).

[GOESWestGLMFEDRadC]

GOES-West flash-extent density, a 5-min accumulation of flashes at each point.

[GOESWestGLMFED-USSAMOA]

[GUAM-boundary]

[PLTGGOESEastRadC]

An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.

[PLTGGOESEastRadF]

An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.

[PLTGGOESEastRadM1]

An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.

[PLTGGOESEastRadM2]

An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.

[PLTGGOESEastRadCAL]

An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.

[PLTGGOESEastRadM2Gridded]

An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.

[PLTGGOESWestRadFAKCAN]

An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.

[PLTGGOESWestRadFUSSAMOA]

An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.

[PLTGGOESWestRadC]

An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.

[PLTGGOESWestRadM1]

An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.

[PLTGGOESWestRadM2]

An AI model that predicts the probability of lightning in the next 60 minutes using GOES-R ABI data.

[PLTGAHIJAPANFLDKGUAM]

An AI model that predicts the probability of lightning in the next 60 minutes using Himawari AHI data.

[NWSCWA]

NWS County Warning Areas

[OFFSHOREZONES]

[PROBSEVTESTACCUM]

[PROBSEVTESTACCUMLOW]

[PROBTOR]

[PROBTORACCUM]

[PSCNN]

[PSNSSL]

[STADIUMS]

[TEST]

[USSAMOA-boundary]

[vt-floods-2023-CIR]

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.

[vt-floods-2023]

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.

[vt-floods-2023-nbr]

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

[NESDIS-BTPWgps]

NESDIS-BTPWgps

[NESDIS-BTPWpct]

NESDIS-BTPWpct

[historic-fire-scars-conus]

These data come from the interagency MTBS (Monitoring Trends in Burn Severity) program through their direct download service.

[POESNAV-AQUA]

[POESNAV-LSAT8]

[POESNAV-LSAT9]

Orbit track for Landsat 9

[POESNAV-N15]

[POESNAV-N18]

[POESNAV-N20]

[POESNAV-N21]

POESNAV-N21

[POESNAV-SEN2A]

POESNAV-SEN2A

[POESNAV-SEN2B]

POESNAV-SEN2B

[POESNAV-NPP]

[POESNAV-TERRA]

[NESDIS-GHE-HourlyRainfall]

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.

[NESDIS-SnowFallRate]

AMSU Snow Fall Rate Global by NOAA-NESDIS

[HRR-CONUS-RADAR-LATEST]

View of HRR-CONUS-PCP-SFC

[RAP-CONUS-PRAT-SFC-DBZ]

View of RAP-CONUS-PRAT-SFC

[SCIT-ALL]

Storm Cell Identification and Tracking (SCIT) Filters 1| ALL Cells 2| Moderate Threat level Cells 3| Severe Threat level Cells

[SCIT-MOD]

Storm Cell Identification and Tracking (SCIT) Filters 1| ALL Cells 2| Moderate Threat level Cells 3| Severe Threat level Cells

[SCIT-SEV]

Storm Cell Identification and Tracking (SCIT) Filters 1| ALL Cells 2| Moderate Threat level Cells 3| Severe Threat level Cells

[SCIT-MOD-FCST]

Storm Cell Identification and Tracking (SCIT) Filter2 - 15min Forecast Trajectories 1| ALL Cells 2| Moderate Threat level Cells 3| Severe Threat level Cells

[MERGEDREF]

Multi-Radar/Multi-Sensor MergedReflectivityQCComposite

[PROBSEVEREV3]

PSv3 models use a machine-learning model called gradient-boosted decision trees.

[nexrrain]

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.

[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)

[nexrhhc-phase]

View of nexrhhc

[nexrhres]

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.

[nexrstorm]

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.

[NEXRAD-Guam]

NEXRAD Guam Base Reflectivity

[NEXRAD-Hawaii]

NEXRAD Hawaii Base Reflectivity

[NEXRAD-PuertoRico]

WSR 88D NEXRAD Radar Base Reflectivity Tilt 1 for San Juan, Puerto Rico

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[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 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

[RIVER-FLDtsp-AP]