- 24hr Snow Depth
ID: SNOWDEPTH24
24hr SnowDepth (in)
- 24hr Snow Fall
ID: SNOWFALL24
24hr SnowFall (in)
- 2015 WI NAIP Counties
ID: wi-counties
This layer displays Wisconsin county outlines. Right-click-probe allows downloads of source imagery for the 2015 Wisconsin NAIP aerial photography county mosaics.
- 2015 WI NAIP DOQQs
ID: NAIPWI2015fp
This layer displays the coverage footprints for the 2015 Wisconsin NAIP aerial photography. Right-click probe allows downloads of source imagery.
- African Wildfire Targets
ID: CSIR
Southern Africa Wild Fire targets are fires detected by the MODIS sensor on the Terra and Aqua satellites. It is produced by CSIR (The Council for Scientific and Industrial Research) and updated every 60 minutes to include any new information.
- Aqua Aerosol Optical Depth
ID: AQUA-AER
MODIS: AQUA Aerosol Optical Depth (ta)
- Aqua False Color
ID: aquafalsecolor
CIMSS-MODIS Satellite False Color (Aqua)
- AQUA Orbit
ID: POESNAV-AQUA
- Australia DNB 2019 - Dynamic
ID: NppDynamicDnb
Proof of concept VIIRS Day/Night Band imagery for the 2019 fires in New South Wales and Queensland, Australia. Source: NOAA CLASS.
- Australia DNB 2019 - HNCC
ID: NppHnccDnb
Proof of concept VIIRS Day/Night Band imagery for the 2019 fires in New South Wales and Queensland, Australia. Source: NOAA CLASS.
- Australian Soil Moisture - Root Zone
ID: 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.
- Blended TPW GPS
ID: NESDIS-BTPWgps
NESDIS-BTPWgps
- Blended TPW Percent
ID: NESDIS-BTPWpct
NESDIS-BTPWpct
- Cladophora Classification
ID: clad
Estimate of 2005 algae extent along coastal Lake Michigan.
- Cloud Top Cooling targets
ID: CIMSS-CTCtargets
CIMSS-Cloud Top Cooling targets
- CMORPH2 1-Day Precip Accumulation
ID: 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 low earth orbit (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).
- CMORPH2 1-Hour Precip Accumulation
ID: 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 low earth orbit (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).
- CMORPH2 7-Day Precip Accumulation
ID: 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 low earth orbit (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).
- Composite River Ice: Alaska
ID: ICE-COMP-AP
- Composite River Ice: Missouri Basin
ID: ICE-COMP-MB
- Composite River Ice: North Central
ID: ICE-COMP-NC
- Composite River Ice: Northeast
ID: ICE-COMP-NE
- Convective Outlook - Categorical
ID: SPC-ConvOutlook-CATG
SPC Convective Outlook - Categorical
- Convective Outlook - Categorical (color map)
ID: SPC-ConvOutlook-CATG-cmap
View of SPC-ConvOutlook-CATG
- Convective Outlook Day1
ID: SPCcoday1
Convective Outlook Day1 (Category)
id=SPCcoday1
- Convective Outlook Day2
ID: SPCcoday2
Convective Outlook Day2 (Category)
- Convective Outlook Day3
ID: SPCcoday3
Convective Outlook Day3 (Categorical)
- CSPP VIIRS Flood Detection
ID: cspp-flood
Daily direct broadcast-produced flood products created by latest alpha version of the CSPP VIIRS Flood Detection software.
- CSPP VIIRS Flood Detection (no cloud)
ID: cspp-flood-nocloud
An alternate view of the CSPP VIIRS Flood Detection product with cloud & cloud shadow pixels set to transparent.
- CSPP VIIRS Flood Detection - Global (no clouds)
ID: cspp-viirs-flood-globally-nocloud
Global flood products created from Suomi-NPP SDRs by the latest alpha version of the CSPP VIIRS Flood Detection software.
This product has cloudy & cloud shadow pixels removed so that, in cases where granules overlap, only cloud free data points are displayed.
- Current Large Fires
ID: Current-Fires
Current large fire incidents in the USA and Canada as tracked by USDA Forest Service
- DNB ClearView
ID: DNB-ClearView
DNB-ClearView
- DNB ClearView Monthly - Test
ID: dnb-monthly-nightlights
- Earthquake Magnitude
ID: Earthquake-mag
Earthquake Magnitude (Past 24hr)
- Eclipse Path
ID: Eclipse
Eclipse Path
- Excessive Rainfall Threat Area Day1
ID: ERTAday1
WPC Excessive Rainfall Threat Area Day1:
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. WPC 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
- Excessive Rainfall Threat Area Day2
ID: ERTAday2
WPC Excessive Rainfall Threat Area Day2: 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. WPC 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
- Excessive Rainfall Threat Area Day3
ID: ERTAday3
WPC Excessive Rainfall Threat Area Day3: 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. WPC 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
- Excessive Rainfall Threat Area Forecast
ID: ERTAfcast
WPC Excessive Rainfall Threat Area Forecast. 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. WPC 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
- Excessive Rain Forecast
ID: WPC-ExcessiveRain
WPC-ExcessiveRain
- Fire Danger Index Africa
ID: ZAFDI
MODIS Fire Danger Index South Africa by CIMSS-DBCRAS
- Fire Danger Index ConUS
ID: CONUSFDI
MODIS Fire Danger Index (FDI) ConUS by CIMSS-DBCRAS
- Fire Hazards (Issued)
ID: REDFLAG
REDFLAG
- Fire Hazards (Valid)
ID: 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
- Fire Radiative Power VIIRS 375m Alaska
ID: FIRMS-VIIRS-Alaska-ActiveFires
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.
- Fire Radiative Power VIIRS 375m Australia
ID: FIRMS-VIIRS-Australia-ActiveFires
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.
- Fire Radiative Power VIIRS 375m CAmerica
ID: FIRMS-VIIRS-Central-America-ActiveFires
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.
- Fire Radiative Power VIIRS 375m Canada
ID: FIRMS-VIIRS-Canada-ActiveFires
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.
- Fire Radiative Power VIIRS 375m ConUS
ID: FIRMS-VIIRS-ConUS-Hawaii-ActiveFires
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.
- Fire Radiative Power VIIRS 375m Europe
ID: FIRMS-VIIRS-Europe-ActiveFires
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.
- Fire Radiative Power VIIRS 375m Global >16
ID: FIRMS-VIIRS-Global-ActiveFires-Filtered
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.
- Fire Radiative Power VIIRS 375m Global IMG
ID: FIRMS-VIIRS-Global-ActiveFires-Raster
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 otherscience applications requiring improved fire mapping fidelity.
- Fire Radiative Power VIIRS 375m NAfrica
ID: FIRMS-VIIRS-Northern-Africa-ActiveFires
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.
- Fire Radiative Power VIIRS 375m Russia
ID: FIRMS-VIIRS-Russia-ActiveFires
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.
- Fire Radiative Power VIIRS 375m SAfrica
ID: FIRMS-VIIRS-Southern-Africa-ActiveFires
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.
- Fire Radiative Power VIIRS 375m SAmerica
ID: FIRMS-VIIRS-South-America-ActiveFires
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.
- Fire Radiative Power VIIRS 375m SAsia
ID: FIRMS-VIIRS-SAsia-ActiveFires
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.
- Fire Radiative Power VIIRS 375m SEAsia
ID: FIRMS-VIIRS-SEAsia-ActiveFires
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 otherscience applications requiring improved fire mapping fidelity.
- Fire Radiative Power VIIRS I-band DB
ID: 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.
- Fire Weather Outlook - Categorical
ID: SPC-FireOutlook-CATG
SPC Fire Weather Outlook - Categorical
- Fire Weather Outlook Day1
ID: SPCfwday1
Fire Weather Outlook Day1 (Category)
- Fire Weather Outlook Day2
ID: SPCfwday2
Fire Weather Outlook Day2 (Category)
- Flash Flood Hazards (Zones)
ID: WFLASH
Flash Flood Hazards
- Flood Hazards (Zones)
ID: WWFLOOD
Flood Watches and Warnings
- Flood Outlook Product
ID: FOP
WPC FLood Outlook Product
- Flood Warnings (Issued)
ID: FLOODWARN
Flood Warning Polygons
- Flood Warnings (Valid)
ID: XFLOODWARN
XFLOODWARN
- Flood Warnings Hydrological-VTEC (Issued)
ID: 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.
- Fog Hazards
ID: WFOG
Fog Hazards
- Freezing Rain Forecast (0.25")
ID: WPC-picezgt25
WPC-picezgt25
- Freezing Rain Probability (0.01"/24h)
ID: WPC-picez24gep01
WPC-picez24gep01
- Freezing Rain Probability (0.10"/24h)
ID: WPC-picez24gep10
WPC-picez24gep10
- Freezing Rain Probability (0.25"/24h)
ID: WPC-picez24gep25
WPC-picez24gep25
- Freezing Rain Probability (0.50"/24h)
ID: WPC-picez24gep50
WPC-picez24gep50
- Freezing Rain Probability (1.00"/24h)
ID: WPC-picez24ge1
WPC-picez24ge1
- Fronts and Troughs
ID: Fronts
NCEP Frontal Analysis: fronts and troughs
- GLM FlashAvgArea
ID: FlashAvgArea
GOES-16 GLM average flash area
3-min average over flash extent density footprint
- GLM FlashCentroidDensity
ID: FlashCentroidDensity
- GLM FlashExtentDensity
ID: FlashExtentDensity
GOES-16 flash extent density
3-min accumulation of footprint of all observed flashes
- glmgroupdensity-west
ID: glmgroupdensity-west
- GLM TotalEnergy
ID: TotalEnergy
GOES-16 total optical energy
3-min accumulation over flash extent density footprint.
- Global Black Marble
ID: VIIRS-MASK-54000x27000
VIIRS Night Global Black Marble by NASA
- Global Infrared
ID: 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.
- Global Infrared - Aviation
ID: 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.
- Global Infrared - Dvorak
ID: 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.
- Global Infrared - Funk Top
ID: 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.
- Global Infrared - Rainbow
ID: 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.
- Global Infrared - Rain Rate
ID: 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.
- Global Infrared - Tops
ID: 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.
- Global Night Lights
ID: NightLightsColored
Global Night Lights (enhanced)
- Global Visible
ID: 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.
- Global Visible (transparent Night)
ID: 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.
- Global Visible - fill
ID: 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.
- Global Visible - full
ID: global1kmvisfull
- Global Water Vapor
ID: 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.
- Global Water Vapor - Gradient
ID: 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.
- GOES-East GLM storm objects
ID: GLMOBJ
- GOES 15 ConUS IR
ID: GOES-W-CONUS-IR
GOES 15 ConUS IR
- GOES 15 ConUS LWIR
ID: GOES-W-CONUS-LWIR
GOES 15 ConUS LWIR
- GOES 15 ConUS NIR
ID: GOES-W-CONUS-NIR
GOES 15 ConUS NIR
- GOES 15 ConUS VIS
ID: GOES-W-CONUS-VIS
GOES 15 ConUS VIS
- GOES 15 ConUS WV
ID: GOES-W-CONUS-WV
GOES 15 ConUS WV
- GOES 15 Full Disk IR
ID: GOES-W-FD-IR
GOES 15 Full Disk IR (Infrared)
- GOES 15 Full Disk LWIR
ID: GOES-W-FD-LWIR
GOES 15 Full Disk LWIR (Long Wave Infrared)
- GOES 15 Full Disk NIR
ID: GOES-W-FD-NIR
GOES 15 Full Disk NIR (Near Infrared)
- GOES 15 Full Disk VIS
ID: GOES-W-FD-VIS
GOES 15 Full Disk VIS (Visible)
- GOES 15 Full Disk WV
ID: GOES-W-FD-WV
GOES 15 Full Disk WV (Water Vapor)
- GOES17 ABI CONUS B07 IR Fire contours
ID: GOES17-ABI-CONUS-B07-ARC-FIRES
- GOES17 ABI CONUS B07 IR Fire enhanced
ID: GOES17-ABI-CONUS-B07-ARC-ENH
View of GOES17-ABI-CONUS-B07-ARCHIVE
- GOES CAPE
ID: cimssdpicapeli
CIMSS-DPI Convective Available Potential Energy (Li et al. 2008)
- GOES East ABI ConUS B02 Hi-Res "Red" Visible
ID: 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.
- GOES East ABI ConUS B03 "Veggie"
ID: 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.
- GOES East ABI ConUS B07 "Fire"
ID: 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.
- GOES East ABI ConUS B07 "Fire" enhanced
ID: 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.
- GOES East ABI ConUS B07 "Fire" stretch
ID: G16-ABI-CONUS-BAND07D
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.
- GOES East ABI ConUS B09 Mid-level Water Vapor
ID: 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.
- GOES East ABI ConUS B09 Mid-level Water Vapor enhanced
ID: 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.
- GOES East ABI ConUS B13 "Clean" Infrared
ID: 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.
- GOES East ABI ConUS B13 "Clean" Infrared enhanced
ID: 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.
- GOES East ABI ConUS FLS IFR Fog Probability
ID: G16-ABI-CONUS-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.
- GOES East ABI ConUS L2 "Sandwich"
ID: 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 ABI ConUS RGB True Color
ID: 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.
- GOES East ABI Full Disk B02 Hi-Res "Red" Visible
ID: 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.
- GOES East ABI Full Disk B03 "Veggie"
ID: 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.
- GOES East ABI Full Disk B07 "Fire"
ID: 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.
- GOES East ABI Full Disk B07 "Fire" enhanced
ID: 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.
- GOES East ABI Full Disk B09 Mid-level Water Vapor
ID: 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.
- GOES East ABI Full Disk B09 Mid-level Water Vapor enhanced
ID: 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.
- GOES East ABI Full Disk B13 "Clean" Infrared
ID: 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.
- GOES East ABI Full Disk B13 "Clean" Infrared enhanced
ID: 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.
- GOES East ABI Full Disk RGB True Color
ID: 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 EAST ABI L2 South America Sandwich
ID: 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.
- GOES East ABI Meso1 B02 Hi-Res "Red" Visible
ID: 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.
- GOES East ABI Meso1 B03 "Veggie"
ID: 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.
- GOES East ABI Meso1 B07 "Fire"
ID: 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.
- GOES East ABI Meso1 B07 "Fire" enhanced
ID: 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.
- GOES East ABI Meso1 B09 Mid-level Water Vapor
ID: 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.
- GOES East ABI Meso1 B09 Mid-level Water Vapor enhanced
ID: 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.
- GOES East ABI Meso1 B13 "Clean" Infrared
ID: 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.
- GOES East ABI Meso1 B13 "Clean" Infrared enhanced
ID: 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.
- GOES East ABI Meso1 B13 "Clean" Infrared red
ID: 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.
- GOES East ABI Meso1 L2 "Sandwich"
ID: 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 ABI Meso1 RGB True Color
ID: 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 East ABI Meso2 B02 Hi-Res "Red" Visible
ID: 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.
- GOES East ABI Meso2 B03 "Veggie"
ID: 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.
- GOES East ABI Meso2 B07 "Fire"
ID: 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.
- GOES East ABI Meso2 B07 "Fire" enhanced
ID: 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.
- GOES East ABI Meso2 B09 Mid-level Water Vapor
ID: 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.
- GOES East ABI Meso2 B09 Mid-level Water Vapor enhanced
ID: 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.
- GOES East ABI Meso2 B13 "Clean" Infrared
ID: 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.
- GOES East ABI Meso2 B13 "Clean" Infrared blue
ID: 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.
- GOES East ABI Meso2 B13 "Clean" Infrared enhanced
ID: 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.
- GOES East ABI Meso2 L2 "Sandwich"
ID: 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 ABI Meso2 RGB True Color
ID: 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.
- GOES East GLM Full Disk Group Density
ID: glmgroupdensity
The Geostationary Lightning Mapper, or GLM, on board Geostationary Operational Environmental Satellite– R Series spacecraft, is the first operational lightning mapper flown in geostationary orbit. 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 oods, snowstorms and res.
- GOES East GLM Full Disk Group Points
ID: glmgrouppoints
glmgrouppoints
- GOES IR Aviation
ID: conusiravn
GOES IR Aviation
- GOES IR Dvorak
ID: conusirbd
GOES IR Dvorak
- GOES IR Funk Top
ID: conusirfunk
GOES IR Funk Top
- GOES IR Overshooting Tops
ID: conusirott
GOES IR Overshooting Tops
- GOES IR Rainbow
ID: conusirnhc
GOES IR Rainbow
- GOES Lifted Index
ID: cimssdpilili
GOES-DPI Lifted Index (Li et al. 2008)
- GOES Ozone
ID: cimssdpiozli
GOES-DPI Ozone (Li etal 2008)
- GOES Precipitable Water
ID: cimssdpipwli
CIMSS-DPI Precipitable Water (mm)
- GOES West ABI ConUS B02 Hi-Res "Red" Visible
ID: G17-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.
- GOES West ABI ConUS B03 "Veggie"
ID: G17-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.
- GOES West ABI ConUS B07 "Fire"
ID: G17-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.
- GOES West ABI ConUS B07 "Fire" enhanced
ID: G17-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.
- GOES West ABI ConUS B09 Mid-level Water Vapor
ID: G17-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.
- GOES West ABI ConUS B09 Mid-level Water Vapor enhanced
ID: G17-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.
- GOES West ABI ConUS B13 "Clean" Infrared
ID: G17-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.
- GOES West ABI ConUS B13 "Clean" Infrared enhanced
ID: G17-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.
- GOES West ABI ConUS RGB True Color
ID: G17-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.
- GOES West ABI Full Disk B02 Hi-Res "Red" Visible
ID: G17-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.
- GOES West ABI Full Disk B03 "Veggie"
ID: G17-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.
- GOES West ABI Full Disk B07 "Fire"
ID: G17-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.
- GOES West ABI Full Disk B07 "Fire" enhanced
ID: G17-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.
- GOES West ABI Full Disk B09 Mid-level Water Vapor
ID: G17-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.
- GOES West ABI Full Disk B09 Mid-level Water Vapor enhanced
ID: G17-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.
- GOES West ABI Full Disk B13 "Clean" Infrared
ID: G17-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.
- GOES West ABI Full Disk B13 "Clean" Infrared enhanced
ID: G17-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 ABI Full Disk RGB True Color
ID: G17-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’ (0.86 µm) bands. The use of the Veggie band is important because it mimics the enhanced reflectivity present in the Green Band.
- GOES West ABI Meso1 B02 Hi-Res "Red" Visible
ID: G17-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.
- GOES West ABI Meso1 B03 "Veggie"
ID: G17-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.
- GOES West ABI Meso1 B07 "Fire"
ID: G17-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.
- GOES West ABI Meso1 B07 "Fire" enhanced
ID: G17-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.
- GOES West ABI Meso1 B09 Mid-level Water Vapor
ID: G17-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.
- GOES West ABI Meso1 B09 Mid-level Water Vapor enhanced
ID: G17-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.
- GOES West ABI Meso1 B13 "Clean" Infrared
ID: G17-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.
- GOES West ABI Meso1 B13 "Clean" infrared enhanced
ID: G17-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.
- GOES West ABI Meso1 B13 "Clean" Infrared green
ID: G17-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 ABI Meso1 RGB True Color
ID: G17-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 West ABI Meso2 B02 Hi-Res "Red" Visible
ID: G17-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.
- GOES West ABI Meso2 B03 "Veggie"
ID: G17-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.
- GOES West ABI Meso2 B07 "Fire"
ID: G17-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.
- GOES West ABI Meso2 B07 "Fire" enhanced
ID: G17-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.
- GOES West ABI Meso2 B09 Mid-level Water Vapor
ID: G17-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.
- GOES West ABI Meso2 B09 Mid-level Water Vapor enhanced
ID: G17-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.
- GOES West ABI Meso2 B13 "Clean" Infrared
ID: G17-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.
- GOES West ABI Meso2 B13 "Clean" Infrared enhanced
ID: G17-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.
- GOES West ABI Meso2 B13 "Clean" Infrared yellow
ID: G17-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.
- GOES West ABI Meso2 RGB True Color
ID: G17-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.
- Great Lakes Surface Environmental Analysis
ID: GLERL-GLSEAimage
Great Lakes Surface Environmental Analysis (GLSEA) from GLERL. For more info see:
http://coastwatch.glerl.noaa.gov/glsea/doc
- Hail Outlook Day1
ID: SPChaday1
Hail Outlook Day1 (%)
- Himawari AHI Full Disk B03 Hi-Res "Red" Visible
ID: HIMAWARI-B03
Himawari AHI Full Disk B03 Hi-Res "Red" Visible
- Himawari AHI Full Disk B04 "Veggie"
ID: HIMAWARI-B04
Himawari AHI Full Disk B04 "Veggie"
- Himawari AHI Full Disk B07 "Fire"
ID: HIMAWARI-B07
Himawari AHI Full Disk B07 "Fire"
- Himawari AHI Full Disk B07 "Fire" enhanced
ID: HIMAWARI-B07-FIRE
View of HIMAWARI-B07
- Himawari AHI Full Disk B09 Mid-level Water Vapor
ID: HIMAWARI-B09
Himawari AHI Full Disk B09 Mid-level Water Vapor
- Himawari AHI Full Disk B09 Mid-level Water Vapor enhanced
ID: HIMAWARI-B09-VAPR
View of HIMAWARI-09
- Himawari AHI Full Disk B13 "Clean" Infrared
ID: HIMAWARI-B13
Himawari AHI Full Disk B13 "Clean" Infrared
- Himawari AHI Full Disk B13 "Clean" Infrared enhanced
ID: HIMAWARI-B13-GRAD
View of HIMAWARI-B13
- Himawari AHI Full Disk Day Convective Storm (ave)
ID: H-DayConvectiveStorm-cve
Himawari AHI Full Disk Day Convective Storm (ave)
- Himawari AHI Full Disk Day Microphysics (dms)
ID: H-DayMicrophysics-dms
Himawari AHI Full Disk Day Microphysics (dms)
- Himawari AHI Full Disk Dust (dst)
ID: H-Dust-dst
Himawari AHI Full Disk Dust (dst)
- Himawari AHI Full Disk Natural Color (dnc)
ID: H-NaturalColor-dnc
Himawari AHI Full Disk Natural Color (dnc)
- Himawari AHI Full Disk Night Microphysics (nms)
ID: H-NightMicrophysics-ngt
Himawari AHI Full Disk Night Microphysics (nms)
- Himawari AHI Full Disk RGB Air Mass (arm)
ID: 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.
- Himawari AHI Full Disk Snow and Fog (dsl)
ID: H-SnowFog-dsl
Himawari AHI Full Disk Snow and Fog (dsl)
- Himawari AHI Full Disk True Color (wgt)
ID: H-TrueColor-wgt
Himawari AHI Full Disk True Color (wgt)
- Himawari AHI Japan B03 Hi-Res "Red" Visible
ID: HIMAWARI-JP-B03
Himawari AHI Japan B03 Hi-Res "Red" Visible
- Himawari AHI Japan B07 "Fire"
ID: HIMAWARI-JP-B07
Himawari AHI Japan Bo7 "Fire"
- Himawari AHI Japan B07 "Fire" enhanced
ID: HIMAWARI-JP-B07-FIRE
View of HIMAWARI-JP-B07
- Himawari AHI Japan B09 Mid-level Water Vapor
ID: HIMAWARI-JP-B09
Himawari AHI Japan B09 Mid-level Water Vapor
- Himawari AHI Japan B09 Mid-level Water Vapor enhanced
ID: HIMAWARI-JP-B09-VAPR
View of HIMAWARI-JP-B09
- Himawari AHI Japan B14 Infrared
ID: HIMAWARI-JP-B14
Himawari AHI Japan B14 Infrared
- Himawari AHI Japan B14 Infrared enhanced
ID: HIMAWARI-JP-B14-GRAD
View of HIMAWARI-JP-B14
- Himawari AHI Target B03 Hi-Res "Red" Visible
ID: HIMAWARI-T1-B03
Himawrai AHI Target B03 Hi-Res "Red" Visible
- Himawari AHI Target B07 "Fire"
ID: HIMAWARI-T1-B07
Himawari AHI Target B07 "Fire"
- Himawari AHI Target B07 enhanced
ID: HIMAWARI-T1-B07-FIRE
View of HIMAWARI-T1-B07
- Himawari AHI Target B14 Infrared
ID: HIMAWARI-T1-B14
Himawari AHI Target B14 Infrared
- Himawari AHI Target B14 Infrared enhanced
ID: HIMAWARI-T1-B14-GRAD
Himawari AHI Target B14 Infrared enhanced
- Himawari AHI Target Mid-level Water Vapor
ID: HIMAWARI-T1-B09
Himawari AHI Target Mid-level Water Vapor
- Himawari AHI Target Mid-level Water Vapor enhanced
ID: HIMAWARI-T1-B09-VAPR
Himawari AHI Target Mid-level Water Vapor enhanced
- HRRR Alaska Near Surface Smoke
ID: HRRR-AK-smoke-surface
NOAA Earth System Research Laboratory High Resolution Rapid Refresh (HRRR) Surface Smoke forecast model, uses VIIRS inputs.
- HRRR Alaska Vertically Integrated Smoke
ID: HRRR-AK-smoke-column
NOAA Earth System Research Laboratory High Resolution Rapid Refresh (HRRR) Vertically Integrated Smoke forecast model, uses VIIRS inputs.
- HRRR ConUS Latest Freezing MASK
ID: HRR-CONUS-FZRN-SFC
HRRR ConUS Latest Freezing MASK
- HRRR ConUS Latest Ice Mask
ID: HRR-CONUS-ICEP-SFC
HRRR ConUS Latest Ice Mask
- HRRR ConUS Latest Precipitation Rate
ID: HRR-CONUS-PCP-LATEST
View of HRR-CONUS-PCP-SFC
- HRRR ConUS Latest Rain Mask
ID: HRR-CONUS-RAIN-SFC
HRRR ConUS Latest Rain Mask
- HRRR ConUS Latest Rate Mask
ID: HRR-CONUS-PCP-SFC
HRR-CONUS-PCP-SFC
- HRRR ConUS Latest Simulated Radar
ID: HRR-CONUS-RADAR-LATEST
View of HRR-CONUS-PCP-SFC
- HRRR ConUS Latest Snow Depth
ID: HRR-CONUS-SNOD-SFC
- HRRR ConUS Latest Snow Mask
ID: HRR-CONUS-SNOW-SFC
HRRR ConUS Latest Snow Mask
- HRRR ConUS Near Surface Smoke
ID: 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 ConUS Vertically Integrated Smoke
ID: 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.
- Hydro Estimator Rainfall
ID: 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.
- Icing Advisory
ID: AIRMET-ICE
AIRMET Icing Advisory
- ICPRadM1
ID: ICPRadM1
Intense Convection Probability -- GOES East Mesoscale 1
- ICPRadM2
ID: ICPRadM2
Intense Convection Probability -- GOES East Mesoscale 2
- IFR Advisory
ID: AIRMET-IFR
AIRMET-IFR Advisory
- Infrared 6 inch Imagery of Madison
ID: madisonir
Infrared 6 inch Imagery of Madison
- Insolation East
ID: 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 West
ID: 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.
- Intense Convection Probability
ID: ICP
Deep learning model that predicts where "intense" convection" is present, based on features that humans associate with intense convection.
- IR Winds 250-100mb
ID: AMV-ULhigh
AMV: Upper Level IR/WV (100-250mb)
- IR Winds 350-251mb
ID: AMV-ULmid
AMV: Upper Level IR/WV (251-350mb)
- IR Winds 500-351mb
ID: AMV-ULlow
AMV: Upper Level IR/WV (351-500mb)
- IR Winds 599-400mb
ID: AMV-LLhigh
AMV: 400-599mb Low Level IR winds
- IR Winds 799-600mb
ID: AMV-LLmid
AMV: Lower Level IR (600-799mb)
- IR Winds 950-800mb
ID: AMV-LLlow
AMV: Lower Level IR (800-950mb)
- Lake Michigan Surface Currents
ID: glofsnowcast
Water currents speed and direction of the top level in Lake Michigan from The Great Lakes Operational Forecast System (GLOFS), uint: m/s
- Landsat-7 Orbit
ID: POESNAV-LSAT7
- Landsat-8 Orbit
ID: POESNAV-LSAT8
- landsat-example
ID: landsat-example
- Landsat Footprints (WRS-2)
ID: 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.
- Landsat Footprints (WRS-2)
ID: 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.
- Landsat Look Natural Color (Daily)
ID: lsat8-llook-fc-daily
View of lsat8-llook-fc
- Landsat Look Natural Color (Daily)
ID: lsat8-llook-fc-daily
View of lsat8-llook-fc
- Landsat Look Natural Color (Swaths)
ID: lsat8-llook-fc
LandsatLook images are full resolution files derived from Landsat Level 1 data products. The images are compressed and stretched to create an image optimized for image selection and visual interpretation. "Natural Color" is a false color composite that minimizes haze by combining bands 6 (1.57 - 1.65µ), 5 (0.85 - 0.88µ), and 4 (0.64 - 0.67µ) as Red, Green, and Blue.
- Landsat Look Natural Color (Swaths)
ID: lsat8-llook-fc
LandsatLook images are full resolution files derived from Landsat Level 1 data products. The images are compressed and stretched to create an image optimized for image selection and visual interpretation. "Natural Color" is a false color composite that minimizes haze by combining bands 6 (1.57 - 1.65µ), 5 (0.85 - 0.88µ), and 4 (0.64 - 0.67µ) as Red, Green, and Blue.
- Landsat Look Thermal IR (Daily)
ID: lsat8-llook-tir-daily
View of lsat8-llook-tir
- Landsat Look Thermal IR (Daily)
ID: lsat8-llook-tir-daily
View of lsat8-llook-tir
- Landsat Look Thermal IR (Swaths)
ID: lsat8-llook-tir
The LandsatLook "Thermal" image is a one-band gray scale .jpg image made to display thermal properties of the scene. The image is made from band 10 (10.60 - 11.19µ) with darker values representing colder temperatures.
- Landsat Look Thermal IR (Swaths)
ID: lsat8-llook-tir
The LandsatLook "Thermal" image is a one-band gray scale .jpg image made to display thermal properties of the scene. The image is made from band 10 (10.60 - 11.19µ) with darker values representing colder temperatures.
- Landsat Scene Footprints (WRS-2)
ID: wrs2-scenes
- Landsat Scene Footprints (WRS-2)
ID: wrs2-scenes
- LaRC Cloud Phase GOESE 8km
ID: LARC-CloudPhase-GOESE-8km
LaRC Cloud Phase GOESE 8km
- LaRC Cloud Phase GOESW 8km
ID: LARC-CloudPhase-GOESW-8km
LaRC Cloud Phase GOESW 8km
- LaRC Cloud Phase HM 8km
ID: LARC-CloudPhase-HM-8km
LaRC Cloud Phase HM 8km
- LaRC Cloud Phase MET8 9km
ID: LARC-CloudPhase-MET8-9km
LaRC Cloud Phase MET8 9km
- LaRC Cloud Phase MSG 9km
ID: LARC-CloudPhase-MSG-9km
LaRC Cloud Phase MSG 9km
- LaRC Cloud Top Height GOESE 8km
ID: LARC-CloudZtop-GOESE-8km
LaRC Cloud Top Height GOESE 8km
- LaRC Cloud Top Height GOESW 8km
ID: LARC-CloudZtop-GOESW-8km
LaRC Cloud Top Height GOESW 8km
- LaRC Cloud Top Height HM 8km
ID: LARC-CloudZtop-HM-8km
LaRC Cloud Top Height HM 8km
- LaRC Cloud Top Height MET8 9km
ID: LARC-CloudZtop-MET8-9km
LaRC Cloud Top Height MET8 9km
- LaRC Cloud Top Height MSG 9km
ID: LARC-CloudZtop-MSG-9km
LaRC Cloud Top Height MSG 9km
- Low/High Pressure
ID: HighLow
NCEP Frontal Analysis: Highs and Lows
- MADIS Surface DewPoint
ID: 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/.
- Maximum Arctic Sea Ice Extent
ID: Max-Arctic-Sea-Ice-Extent
This product represents a single date selected by researchers to show the maximum extent of Arctic sea ice in recent years. These data are from the U.S. National Ice Center (NIC), a multi-agency center operated by the United States Navy, the National Oceanic and Atmospheric Administration, and the United States Coast Guard.
- Mean Snow Duration 1988-2017
ID: mean-snow-cover-1988-2017
mean-snow-cover-1988-2017
- METAR
ID: SSEC-METAR
Global METAR
- Meteosat 8 SEVIRI Full Disk B01 Vis (0.6um)
ID: 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.
- Meteosat 8 SEVIRI Full Disk B04 IR Fire (3.9um)
ID: 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.
- Meteosat 8 SEVIRI Full Disk B05 WV High (6.2um)
ID: 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).
- Meteosat 8 SEVIRI Full Disk B09 IR Clean (10.8um)
ID: 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).
- Meteosat 8 SEVIRI Full Disk B09 IR Clean (10.8um) enhanced
ID: 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).
- Meteosat 8 SEVIRI Full Disk B12 Vis HRV (0.7um)
ID: 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.
- Meteosat 11 SEVIRI Full Disk B01 Vis (0.6um)
ID: 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.
- Meteosat 11 SEVIRI Full Disk B04 IR Fire (3.9um)
ID: 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.
- Meteosat 11 SEVIRI Full Disk B05 WV High (6.2um)
ID: 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).
- Meteosat 11 SEVIRI Full Disk B09 IR Clean (10.8um)
ID: 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).
- Meteosat 11 SEVIRI Full Disk B09 IR Clean (10.8um) enhanced
ID: 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).
- Meteosat 11 SEVIRI Full Disk B12 Vis HRV (0.7um)
ID: 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.
- Midwest Winter Road Conditions
ID: ROADS-IADOT
Conditions are updated every 10 minutes during the winter season (October 15 to April 15) and on an as-needed basis during the non-winter months. Layer and service is maintained by the Iowa DOT GIS team on behalf of the Office of Traffic Operations. This data is provided as is through this value added REST service. All conditions have been remapped to the best of our ability to meet the condition reporting criteria as defined by the Iowa DOT. Some discrepancies may appear. This data service should only be used for reference only. For the most accurate information, please utilize the authoritative state 511 sites below.
State 511 Sites 511 Vendor Disclaimers
North Dakota Iteris The data is provided as is and without liability from the North Dakota Department of Transportation (NDDOT). The NDDOT does not guarantee this data to be free from errors, or inaccuracies, and disclaims any responsibility or liability for interpretations or decisions based on this data.
- MIMIC Total Precip Water v2
ID: MIMICTPW2
MIMIC-TPW2 is an experimental global product of total precipitable water (TPW), using morphological compositing of the MIRS retrieval from several available operational microwave-frequency sensors. MIMIC stands for "Morphed Integrated Microwave Imagery at CIMSS." The specific technique used here was initially described in a 2010 paper by Wimmers and Velden. This Version 2 is developed from an older method (still running in real-time) that uses simpler, but more limited TPW retrievals and advection calculations.
- MIRS 90Ghz Brightness Temperature
ID: MIRS-BT90
MIRS 90Ghz Brightness Temperature
- MIRS Rain Rate
ID: MIRS-RainRate
MIRS Rain Rate
- Mountains Obscured Advisory
ID: AIRMET-MTN
AIRMET-Mountain Obscured Advisory
- MRMS MergedReflectivity
ID: MERGEDREF
Multi-Radar/Multi-Sensor MergedReflectivityQCComposite
- NAIP WI
ID: NAIPWI
National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA.
- NAIP WI Color Infrared
ID: NAIPWICIR
National Agricultural Imagery Program aerial photography from the Wisconsin Farm Service Agency (WI-FSA) of the USDA (Color Infrared)
- NAM-CONUS-PRAT-SFC
ID: NAM-CONUS-PRAT-SFC
NAM-CONUS-PRAT-SFC
- NEXRAD Alaska Base Reflectivity
ID: NEXRAD-Alaska
NEXRAD-Alaska
- NEXRAD CanAm Base Reflectivity mask
ID: nexrrain
NEXRAD CanAm base Reflectivity mask
- NEXRAD CanAm Precipitation Phase
ID: nexrphase
NEXRAD CanAm Precipitation Phase
- NEXRAD ConUS Hybrid Reflectivity mask
ID: nexrhres
NEXRADConUS Hybrid Reflectivity mask
- NEXRAD ConUS Storm Total Precipitation
ID: nexrstorm
NEXRAD ConUS Storm Total Precipitation
- NEXRAD Guam Base Reflectivity
ID: NEXRAD-Guam
NEXRAD Guam Base Reflectivity
- NEXRAD Hawaii Base Reflectivity
ID: NEXRAD-Hawaii
NEXRAD Hawaii Base Reflectivity
- NEXRAD Puerto Rico Base Reflectivity
ID: NEXRAD-PuertoRico
NEXRAD Puerto Rico Base Reflectivity
- NOAA-15 Orbit
ID: POESNAV-N15
- NOAA-18 Orbit
ID: POESNAV-N18
- NOAA-20 Orbit
ID: POESNAV-N20
- NOAA-20 VIIRS Daily DNB (Adaptive)
ID: j01-viirs-adaptive-dnb-daily
j01-viirs-adaptive-dnb-daily
- NOAA-20 VIIRS Daily I02
ID: j01-viirs-i02-daily
j01-viirs-i02-daily
- NOAA-20 VIIRS Daily I05
ID: j01-viirs-i05-daily
j01-viirs-i05-daily
- NOAA-20 VIIRS Daily I05 (tops)
ID: j01-viirs-i05-daily-tops
View of j01-viirs-i05-daily
- NOAA-20 VIIRS False Color (Daily Composite)
ID: j01-viirs-false-color-daily
View of j01-viirs-false-color-swath
- NOAA-20 VIIRS False Color (Hourly Composite)
ID: j01-viirs-false-color-hourly
View of j01-viirs-false-color
- NOAA-20 VIIRS False Color (Swaths)
ID: j01-viirs-false-color-swath
View of j01-viirs-false-color
- NOAA-20 VIIRS Hourly DNB (Adaptive)
ID: j01-viirs-adaptive-dnb
j01-viirs-adaptive-dnb
- NOAA-20 VIIRS Hourly I02
ID: j01-viirs-i02
j01-viirs-i02
- NOAA-20 VIIRS Hourly I05
ID: j01-viirs-i05
j01-viirs-i05
- NOAA-20 VIIRS Hourly I05 (tops)
ID: j01-viirs-i05-tops
View of j01-viirs-i05
- NOAA-20 VIIRS M-Band Fire RGB (Swaths)
ID: j01-viirs-swath-fire-color
This image is made by on-the-fly combining VIIRS bands M11 (2.25um) as red, M7 (8.66um) as green, and M4 (5.55) as blue. Because the M11 shortwave infrared band is sensitive to bright fires, it highlights active especially hot fires in red while preserving a natural color appearance in the rest of the image.
- NOAA-20 VIIRS M-Band Fire Temp (Swaths)
ID: j01-viirs-swath-fire-temp
On-the-fly combination of bands 11, 10, 12.
- NOAA-20 VIIRS True Color (Daily Composite)
ID: j01-viirs-true-color-daily
View of j01-viirs-true-color-swath
- NOAA-20 VIIRS True Color (Hourly Composite)
ID: j01-viirs-true-color-hourly
View of j01-viirs-true-color
- NOAA-20 VIIRS True Color (Swaths)
ID: j01-viirs-true-color-swath
View of j01-viirs-true-color
- NorthWest Winter Road Conditions
ID: ROADS
NorthWest Winter Road Conditions (WRC) decoded from state DOT text.
- NUCAPS-MADIS-SBCAPE
ID: NUCAPS-MADIS-SBCAPE
The MADIS-NUCAPS Surface-Based CAPE merges hourly average surface observations from the NCEP Meteorological Assimilation Data Ingest System (MADIS) with NOAA NUCAPS soundings from the most recent overpass of operational meteorological satellites (SNPP, METOP, or NOAA-20). The SB-CAPE is computed using the SHARPYpy software derived from software used by the NWS Storm Prediction Center (SPC). The satellite data are obtained using the SSEC direct broadcast antennae, processed using CSPP software in near-real time, and displayed in near-real time using SSEC"s RealEarth.
- NUCAPS-MADIS Mean Layer CAPE
ID: NUCAPS-MADIS-MLCAPE
NUCAPS-MADIS-MLCAPE
- NUCAPS-MADIS Mean Layer CIN
ID: NUCAPS-MADIS-MLCIN
NUCAPS-MADIS-MLCIN
- NUCAPS-MADIS Mean Layer LI
ID: NUCAPS-MADIS-MLLI
NUCAPS-MADIS-MLLI
- NUCAPS-MADIS Surface CAPE
ID: MADIS-NUCAPS-Surface-CAPE
The MADIS-NUCAPS Surface-Based CAPE merges hourly average surface observations from the NCEP Meteorological Assimilation Data Ingest System (MADIS) with NOAA NUCAPS soundings from the most recent overpass of operational meteorological satellites (SNPP, METOP, or NOAA-20). The SB-CAPE is computed using the SHARPYpy software derived from software used by the NWS Storm Prediction Center (SPC). The satellite data are obtained using the SSEC direct broadcast antennae, processed using CSPP software in near-real time, and displayed in near-real time using SSEC"s RealEarth.
- NUCAPS-MADIS Surface CIN
ID: NUCAPS-MADIS-SBCIN
NUCAPS-MADIS-SBCIN
- NUCAPS-MADIS Surface LI
ID: NUCAPS-MADIS-SBLI
NUCAPS-MADIS-SBLI
- NUCAPS CAA Temp 180mb
ID: NUCAPS-CAA-temp-180mb
- NUCAPS CAA Temp 200mb
ID: NUCAPS-CAA-temp-200mb
- NUCAPS CAA Temp 235mb
ID: NUCAPS-CAA-temp-235mb
- NUCAPS CAA Temp 260mb
ID: NUCAPS-CAA-temp-260mb
- NUCAPS CAA Temp 286mb
ID: NUCAPS-CAA-temp-286mb
- NWS-AK-TPCP-1DAY
ID: NWS-AK-TPCP-1DAY
NWS-AK-TPCP-1DAY
- NWS-CONUS-TPCP-1DAY
ID: NWS-CONUS-TPCP-1DAY
NWS-CONUS-TPCP-1DAY
- NWS County Warning Areas
ID: NWSCWA
NWS County Warning Areas
- NWSWARNS12Z12Z
ID: NWSWARNS12Z12Z
NWSWARNS12Z12Z (Severe and Tornado. No SVSs)
- Overshooting Tops targets
ID: CIMSS-OTtargets
Cloud OverShooting Tops targets
- Pilot Reports
ID: PIREP
PIREP
- PLTG GOES-East CONUS
ID: PLTGGOESEastRadC
Probability of lightning in the next 60 min
- PLTG GOES-East MESO1
ID: PLTGGOESEastRadM1
Probability of lightning in the next 60 min
- PLTG GOES-East MESO2
ID: PLTGGOESEastRadM2
Probability of lightning in the next 60 min
- PLTG GOES-West CONUS
ID: PLTGGOESWestRadC
- PNPOINTALL
ID: PNPOINTALL
PNPOINTALL
- PNTRACKALL
ID: PNTRACKALL
PNTRACKALL
- Probabilistic Precip Forecast
ID: PQPF6hr
WPC 6hr Probabilistic Precip PQPF .01in (%)
Purpose – The probabilistic quantitative precipitation forecast (PQPF) guidance is used by forecasters and hydrologists to determine the probability of any rainfall amount at a given location. The PQPF can be used to assist forecasters in the issuance of flash flood and flood watches at an WFO or RFC.
- PROBSEVACCUM
ID: PROBSEVACCUM
≥ 50%
- ProbSevere
ID: ProbSevere
ProbSevere
- ProbSevere (version2)
ID: PROBSEVERE
The probability of any severe is the max(ProbHail,ProbWind,ProbTor).
- ProbSevere (version 3)
ID: PROBSEVEREV3
PSv3 models use a machine-learning model called gradient-boosted decision trees.
- ProbSevere Accumulation 20% to 49%
ID: PROBSEVACCUMLOW
ProbSevere Accumulation 20% to 49%
- PROBSEVTESTACCUM
ID: PROBSEVTESTACCUM
- PROBSEVTESTACCUMLOW
ID: PROBSEVTESTACCUMLOW
- PROBTOR
ID: PROBTOR
- PROBTORACCUM
ID: PROBTORACCUM
- PSNCO
ID: PSNCO
- PSNSSL
ID: PSNSSL
- Quantitative Precip Forecast
ID: QPF6hr
WPC 6hr Quantitative Precip Forecast QPF (in)
- Quantitative Precipitation Forecast
ID: WPC-QPF
WPC-QPF
- RAP ConUS Latest Simulated Radar
ID: RAP-CONUS-PRAT-SFC-DBZ
View of RAP-CONUS-PRAT-SFC
- RAP North America Near Surface Smoke
ID: 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 North America Vertically Integrated Smoke
ID: 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.
- River-ICE-CONCENTRATION: Alaska
ID: RVER-ICEC-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 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, Alaska region
- RIVER-ICE-CONCENTRATION: Missouri Basin
ID: 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)
- River-ICE-CONCENTRATION: North Central Basin
ID: 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)
- River-ICE-CONCENTRATION: North East Basin
ID: 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 Flood: 1 day VIIRS composite
ID: 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 Flood: 5 day VIIRS composite
ID: 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-daily
ID: 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: ABI-daily (tsp)
ID: 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
ID: 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: ABI-hourly (tsp)
ID: 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 Flood: AHI
ID: 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 Flood: Alaska
ID: 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 Flood: Alaska (transparent)
ID: 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 Flood: Global
ID: 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 Flood: Joint ABI/VIIRS
ID: 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 Flood: Joint AHI/VIIRS
ID: 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 Flood: Missouri Basin
ID: 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 Flood: Missouri Basin (transparent)
ID: 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 Flood: North Central Basin
ID: 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 Flood: North Central Basin (transparent)
ID: 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 Flood: North East Basin
ID: 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 Flood: North East Basin (transparent)
ID: 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 Flood: North West
ID: 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 Flood: North West (transparent)
ID: 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 Flood: South East
ID: 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 Flood: South East (transparent)
ID: 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 Flood: South West
ID: 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 Flood: South West (tsp)
ID: 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 Flood: US
ID: 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 Flood: US (transparent)
ID: 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 Flood: West Gulf Basin
ID: 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 Flood: West Gulf Basin (transparent)
ID: 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: Alaska
ID: 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: Missouri Basin
ID: 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: North Central Basin
ID: 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: North East Basin
ID: 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)
- Sea Ice Concentration
ID: NPP-SIC-ENH
The Sea Ice Concentration product is based on NOAA Enterprise Algorithm. The original spatial resolution is 750 m as the data input are VIIRS M band at 750 m resolution. It is regridded to the original resolution to 1 km EASE2-Grid. For the reference, you can refer to
Liu, Y., Key, J., & Mahoney, R. (2016). Sea and freshwater ice concentration from VIIRS on Suomi NPP and the future JPSS satellites. Remote Sensing, 8(6), 523.
- Sea Surface Temperature
ID: NESDIS-SST
NESDIS: Hi-Res Sea Surface Temperature
- SENTINEL 2A Orbit
ID: POESNAV-SEN2A
POESNAV-SEN2A
- SENTINEL 2B Orbit
ID: POESNAV-SEN2B
POESNAV-SEN2B
- Severe Weather Outlook Day2
ID: SPCsvday2
Severe Weather Outlook Day2
- Severe Weather Outlook Day3
ID: SPCsvday3
Severe Weather Outlook Day3
- Severe Weather Outlook Day4
ID: SPCsvday4
Severe Weather Outlook Day4
- Severe Weather Outlook Day5
ID: SPCsvday5
Severe Weather Outlook Day5
- Severe Weather Warning Outlines
ID: SevereOutl
Tornado, Thunderstorm, Flash Flood and Marine Warnings (outlines only, no fill)
- Severe Weather Warnings
ID: Severe
Tornado, Thunderstorm, Flash Flood and Marine Warning polygons.
- Severe Weather Warning Vectors
ID: SevereVect
Tornado and Thunderstorm Warning Vectors
- Severe Weather Watch Box
ID: SAW
Severe Weather Watch Box - Aviation
- Severe Wind Outlook Day1
ID: SPCwnday1
Severe Wind Outlook Day1 (%)
- Ship & Buoy
ID: SSEC-ShipBuoy
Global Ship & Buoy
- Snow Depth (SNODAS)
ID: 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.
- Snow Fall Rate
ID: NESDIS-SnowFallRate
AMSU Snow Fall Rate Global by NOAA-NESDIS
- Snowfall Reports (6hr)
ID: lsr-snow
Snowfall Reports
- Snowfall Total - 24hr (SNODAS)
ID: 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.
- Snow Forecast (4")
ID: WPC-psnowgt04
WPC-psnowgt04
- Snow Forecast (8")
ID: WPC-psnowgt08
WPC-psnowgt08
- Snow Forecast (12")
ID: WPC-psnowgt12
WPC-psnowgt12
- Snow Probability (0.1"/24h)
ID: WPC-psnow24gep1
WPC-psnow24gep1
- Snow Probability (1.0"/24h)
ID: WPC-psnow24ge1
WPC-psnow24ge1
- Snow Probability (2.0"/24h)
ID: WPC-psnow24ge2
WPC-psnow24ge2
- Snow Probability (4.0"/24h)
ID: WPC-psnow24ge4
WPC-psnow24ge4
- Snow Probability (6.0"/24h)
ID: WPC-psnow24ge6
WPC-psnow24ge6
- Snow Probability (8.0"/24h)
ID: WPC-psnow24ge8
WPC-psnow24ge8
- Snow Probability (12.0"/24h)
ID: WPC-psnow24ge12p0
WPC-psnow24ge12p0
- Snow Probability (18.0"/24h)
ID: WPC-psnow24ge18p0
WPC-psnow24ge18p0
- SNPP Day/Night AM Composite - Adaptive
ID: nppadpam
NPP Day/Night AM Composite - Adaptive
- SNPP Day/Night Band (DNB) - Honolulu DB
ID: nppdnbdyn-hnl
NPP Day/Night Band (DNB) - Honolulu DB
- SNPP Day/Night Band (DNB) - Madison DB
ID: nppdnbdyn-msn
Suomi NPP Day/Night Band (DNB) imagery received and processed by the SSEC UW-Madison direct reception facility by Direct Broadcast from the satellite.
- SNPP Day/Night Band (DNB) - Puerto Rico DB
ID: nppdnbdyn-upr
NPP Day/Night Band (DNB) - Puerto Rico DB
- SNPP Day/Night Band - Dynamic
ID: nppdnb
NPP Day/Night Band - Dynamic
- SNPP False Color
ID: nppfc
NPP False Color
- SNPP NUCAPS CO-MR-496mb
ID: CO-MR-496mb
This a proof of concept example of NUCAPS from Suomi NPP CrIS/ATMS data, converted to a gridded NetCDF.
- SNPP Orbit
ID: POESNAV-NPP
- SNPP Sea Surface Temperature
ID: nppsst
NPP Sea Surface Temperature
- SNPP Sea Surface Temperature (SST) - Madison DB
ID: nppsst-msn
NPP Sea Surface Temperature (SST) - Madison DB
- SNPP True Color (TC) - Honolulu DB
ID: npptc-hnl
NPP True Color (TC) - Honolulu DB
- SNPP True Color (TC) - Puerto Rico DB
ID: npptc-upr
NPP True Color (TC) - Puerto Rico DB
- SNPP VIIRS Daily DNB (Adaptive)
ID: npp-viirs-adaptive-dnb-daily
npp-viirs-adaptive-dnb-daily
- SNPP VIIRS Daily I02
ID: npp-viirs-i02-daily
npp-viirs-i02-daily
- SNPP VIIRS Daily I05
ID: npp-viirs-i05-daily
npp-viirs-i05-daily
- SNPP VIIRS Daily I05 (tops)
ID: npp-viirs-i05-daily-tops
View of npp-viirs-i05-daily
- SNPP VIIRS False Color (Daily Composite)
ID: npp-viirs-false-color-daily
View of npp-viirs-false-color-swath
- SNPP VIIRS False Color (Daily Composite)
ID: npp-viirs-false-color-daily
View of npp-viirs-false-color-swath
- SNPP VIIRS False Color (Hourly Composite)
ID: npp-viirs-false-color-hourly
View of npp-viirs-false-color
- SNPP VIIRS False Color (Hourly Composite)
ID: npp-viirs-false-color-hourly
View of npp-viirs-false-color
- SNPP VIIRS False Color (Swaths)
ID: npp-viirs-false-color-swath
View of npp-viirs-false-color
- SNPP VIIRS False Color (Swaths)
ID: npp-viirs-false-color-swath
View of npp-viirs-false-color
- SNPP VIIRS False Color - Madison DB
ID: nppfc-msn
Suomi-NPP VIIRS False Color imagery received and processed by the SSEC UW-Madison direct reception facility by Direct Broadcast from the satellite.
- SNPP VIIRS Fire RGB (Swaths)
ID: npp-viirs-swath-fire-color
View of npp-viirs-bands-day-swath
- SNPP VIIRS Fire RGB (Swaths)
ID: npp-viirs-swath-fire-color
View of npp-viirs-bands-day-swath
- SNPP VIIRS Fire Temp (Swaths)
ID: npp-viirs-swath-fire-temp
View of npp-viirs-bands-day-swath
- SNPP VIIRS Fire Temp (Swaths)
ID: npp-viirs-swath-fire-temp
View of npp-viirs-bands-day-swath
- SNPP VIIRS Hourly DNB (Adaptive)
ID: npp-viirs-adaptive-dnb
npp-viirs-adaptive-dnb
- SNPP VIIRS Hourly I02
ID: npp-viirs-i02
npp-viirs-i02
- SNPP VIIRS Hourly I05
ID: npp-viirs-i05
npp-viirs-i05
- SNPP VIIRS Hourly I05 (tops)
ID: npp-viirs-i05-tops
View of npp-viirs-i05
- SNPP VIIRS True Color (Daily Composite)
ID: npp-viirs-true-color-daily
View of npp-viirs-true-color-swath
- SNPP VIIRS True Color (Daily Composite)
ID: npp-viirs-true-color-daily
View of npp-viirs-true-color-swath
- SNPP VIIRS True Color (Hourly Composite)
ID: npp-viirs-true-color-hourly
View of npp-viirs-true-color
- SNPP VIIRS True Color (Hourly Composite)
ID: npp-viirs-true-color-hourly
View of npp-viirs-true-color
- SNPP VIIRS True Color (Swaths)
ID: npp-viirs-true-color-swath
View of npp-viirs-true-color
- SNPP VIIRS True Color (Swaths)
ID: npp-viirs-true-color-swath
View of npp-viirs-true-color
- SNPP VIIRS True Color - Madison DB
ID: npptc-msn
Suomi-NPP VIIRS True Color imagery received and processed by the SSEC UW-Madison direct reception facility by Direct Broadcast from the satellite.
- SPC reports 12Z to 12Z
ID: SPCREPS12Z12Z
SPCREPS12Z12Z
- Storm Cell Id and Tracking - Point
ID: SCIT-PNT
Storm Cell Identification and Tracking (SCIT)
Filters
CELL | Cell Id
SITE | NEXRAD Site Id
TVS | Tornado Vortex Signature
MDA | Mesocyclone
- Storm Cell Id and Tracking - Track
ID: SCIT
Storm Cell Id and Tracking - Track
- Storm Reports 3hrs
ID: StormReports
Storm Reports (last 3hrs)
- Storm Reports 24hrs
ID: StormReports24
Storm Reports (last 24hrs)
- Stroke Density XP
ID: XLSD
XLSD - Experimental product, Restricted to SSEC internal use only!
- SVRWARNS12Z12Z
ID: SVRWARNS12Z12Z
- Terminal Area Forecasts
ID: TAF
Terminal Aerodrome Forecast (TAF)
- Terra Aerosol Optical Depth
ID: TERRA-AER
MODIS: TERRA Aerosol Optical Depth (ta)
- Terra False Color
ID: terrafalsecolor
CIMSS-MODIS Satellite False Color (Terra)
- Terra Land Surface True Color
ID: GLOBALterratc
MODIS: Terra land Surface True Color composite
- TERRA Orbit
ID: POESNAV-TERRA
- Terra True Color
ID: terratruecolor
CIMSS-MODIS Satellite True Color (Terra)
- TEST
ID: TEST
- TESTGRBRADF
ID: TESTGRBRADF
TESTGRBRADF
- Thunderstorm Watches/Warnings
ID: WWSEVTRW
Thunderstorm Watches and Warnings
- Tornado Outlook Day1
ID: SPCtnday1
Tornado Outlook Day1 (%)
- Tornado Watches/Warnings
ID: WWTORNADO
Tornado Watches and Warnings
- Tornado Watches and Warnings
ID: WWTOR
Tornado Watches and Warnings
- TORWARNS12Z12Z
ID: TORWARNS12Z12Z
- Total Column Sulphur Dioxide
ID: AURA-SO2
AURA - OMI Total Column Sulphur Dioxide (SO2)
- True Color Clear View
ID: BRDF
MODIS Clear View ConUS Composite. BRDF (Bidirectional Reluctance Distribution Function) is a 16-day cloud-free composite.
- TS Cones - Atlantic and EPacific
ID: TSCONEALL
TS Cones - Atlantic and EPacific
- TS Cones - CPacific and WPacific
ID: PNCONEALL
TS Cones - CPacific and WPacific
- TS HDOB - Atlantic points
ID: TSHDOBATLparm
TS HDOB - Atlantic points
- TS HDOB - Atlantic winds
ID: TSHDOBATL
TS HDOB - Atlantic winds
- TS HDOB - EPacific points
ID: TSHDOBEPACparm
TS HDOB - EPacific points
- TS HDOB - EPacific winds
ID: TSHDOBEPAC
TS HDOB - EPacific winds
- TS Points - Atlantic and EPacific
ID: TSPOINTALL
TS Points - Atlantic and EPacific
- TS Tracks - Atlantic and EPacific
ID: TSTRACKALL
TS Tracks - Atlantic and EPacific
- Turbulence Advisory
ID: AIRMET-TURB
AIRMET-Turlulence Advisory
- US Landsat Analysis Ready Data (ARD) Grids
ID: 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.
- VIIRS Fire RGB - CIRA
ID: 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 RGB - GINA
ID: DayLandCloudFire-RGB-GINA
This RGB is created by assigning the VIIRS 3.74um channel to red, 0.87um channel to green, and the 0.64um channel to blue. It is used to assess fire perimeters and burn scars. These data are produced by the Geographic Information Network of Alaska (GINA).
- VIIRS Fire Temp RGB - CIRA
ID: 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 - GINA
ID: FireTemperature-RGB-GINA
This RGB is created by assigning the VIIRS 3.74um channel to red, 2.25um channel to green, and the 1.61um channel to blue. It is used to assess fire intensity and size, with fires ranging from red (lowest) to yellow to white (hottest or biggest). These data are produced by the Geographic Information Network of Alaska (GINA).
- VIIRS i04 - GINA
ID: VIIRS-i04-GINA
This is the VIIRS 3.74um single channel i-band with 376 m resolution. It is an IR channel that is very sensitive to fires and hot spots and is available day or night. A special colormap is used to enhance the warm-hot pixels. The sensors can become saturated by very intense fires and daytime radiance values can affected by reflected sunlight. These data are produced by the Geographic Information Network of Alaska (GINA).
- VIIRS NDVI 16-day Composite
ID: NDVI-16day-before
This CONUS NDVI product is clipped from the global VIIRS composite product VNP13A1-001 using AppEEARS at the NASA LPDAAC. The spatial resolution is 500m. It is made with in alternating 8-day cycles from best available pixels. See link below for more information.
- VIIRS Snowmelt - GINA
ID: VIIRS-Snowmelt-GINA
This RGB is created by assigning the VIIRS 1.61um channel to red, 1.24um channel to green, and the 0.64um channel to blue. The blue shades identify snow cover characteristics. Darker blue shows wetter or older snow and lighter blues show drier or newer snow. These data are produced by the Geographic Information Network of Alaska (GINA).
- Vis Winds 800-700mb
ID: AMV-VISmid
AMV: Middle Level Visible (700-800mb)
- Vis Winds 925-801mb
ID: AMV-VISlow
AMV: Lower Level Visible (801-925mb)
- Volcanic Ash Adv plumes
ID: VAA
Volcanic Ash Advisories: Ash Clouds
- WI Coastal Imagery
ID: 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.
- WI Coastal LiDAR
ID: WIcoastallidar
WI Coastal LiDAR
- WI Coastal Shaded Relief
ID: WIcoastalshdrlf
WI coastal shaded relief map generated from LiDAR data.
- WI Lake Clarity
ID: LakesTSI
These data represent the estimated clarity, or transparency, of the 8,000 largest of those lakes as measured by satellite remote sensing (Landsat).
- Wind Hazards
ID: 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.
- WI Nordic Ski Trails
ID: SKITrails
SKITrails
- Winter Storm Severity Index
ID: WPC-WSSI
- Winter Weather Hazards (Issued)
ID: 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.
- Winter Weather Hazards (Valid)
ID: 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.
- WISCLAND 1993
ID: wiscland
In 1993 a team of researchers from University of Wisconsin-Madison (ERSC) and the Wisconsin DNR developed WISCLAND, the first satellite-derived land cover map of Wisconsin. The UW-Madison (SCO) and the DNR partnered on a project to produce an updated land cover map of Wisconsin. The resulting dataset, known as Wiscland 2.0, was completed in August 2016.
- Wisconsin Counties
ID: wi-counties-basic
- Wisconsin in 3D (SRTM)
ID: wisc-3d
The Space Shuttle Endeavour collected data to produce a digital elevation model of the Earth during the Shuttle Radar Topography Mission (SRTM), flown from February 11-22, 2000. Researchers clipped Wisconsin from this data to produce this 3D anaglyph. To see the 3D effect, use Red-Blue 3D glasses (red over left eye).
- Wisconsin LIDAR Hillshade
ID: 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.
- WI USGS Landsat Poster
ID: 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.
- WSSI Blowing Snow
ID: WPC-WSSI-BlowingSnow
- WSSI Flash Freeze
ID: WPC-WSSI-FlashFreeze
- WSSI Ground Blizzard
ID: WPC-WSSI-Blizzard
- WSSI Ice Accumulation
ID: WPC-WSSI-IceAccum
- WSSI Snow Amount
ID: WPC-WSSI-SnowAmount
- WSSI Snow Load
ID: WPC-WSSI-SnowLoad