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us_svrwx_202504/severe_storm (MapServer)

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Service Description:

Note: this data is currently in testing and is experimental.

Date of Images:

Post-Event: 4/2/2025-4/6/2025

Summary:

Storms that produce damaging winds, hail, and tornadoes often exhibit distinct cloud-top patterns in satellite imagery. Two of these patterns, overshooting tops (OTs) and above-anvil cirrus plumes (AACPs), are frequently observed over intense storms. Using deep learning techniques, researchers at NASA Langley Research Center developed software to automatically detect these severe storm signatures in 500m GOES satellite data collected every 5 minutes.

Emergency managers can use this raster data to quickly identify locations where severe storms likely occurred, complementing ground-based reports in regions with limited observations. Severe weather on the ground is more likely when OTs and AACPs are both detected and in areas where detections are clustered or observed repeatedly. Long, nearly straight lines of OT and AACP time-aggregated detections can indicate severe storm tracks.

Suggested Use and Use Cases:

Target audiences: GIS specialists, tactical emergency managers

Information Needed: Near real-time situational awareness about locations where severe storm impacts may have occurred.

Example Uses: Target additional information collection. Prioritize field activities (e.g. assessments, resource allocation).

Value Proposition: Low resolution, low latency data shows areas that may have recently or may soon experience severe weather (nowcasting).

Satellite/Sensor

Satellite: Geostationary Operational Environmental Satellite (GOES) Satellite remote sensing over North & South America

Resolution: 5 minute temporal resolution observation frequency, 500m spatial resolution

Product Specifications:

Capability type

Experimental

Data type

Raster of binary OT detections aggregated over a designated incident time frame

Min. update frequency

Daily during working hours

Area coverage

Bounded subset

Other key attributes

Earliest detection time - earliest time (in UTC) an overshooting top was flagged.

Count of observations - the number of Overshooting Tops detected within each geostationary satellite 0.5 km pixel for every 5 min conus scan from 2 April 12UTC - 6 April 12UTC.

Binary Overshooting Detection Flag - indicator for if any overshooting top was detected over a given 0.5km pixel.

Visualization

Single-color raster map

Time-aggregated plots of severe storm signatures

Caveats:

While the presence of OTs and AACPs often correlates with severe weather, this product does not observe ground impacts and may detect features that do not correspond to severe weather.

Esri REST Endpoint:

See URL on the right side of the page.

WMS Endpoint:

https://maps.disasters.nasa.gov/ags03/services/us_svrwx_202504/severe_storm/MapServer/WMSServer

Data Download:

https://maps.disasters.nasa.gov/download/gis_products/event_specific/2025/us_svrwx_202504/severestorm/



Map Name: severe_storm

Legend

All Layers and Tables

Dynamic Legend

Dynamic All Layers

Layers: Description: Note: this data is currently in testing and is experimental.Date of Images:Post-Event: 4/2/2025-4/6/2025Summary:Storms that produce damaging winds, hail, and tornadoes often exhibit distinct cloud-top patterns in satellite imagery. Two of these patterns, overshooting tops (OTs) and above-anvil cirrus plumes (AACPs), are frequently observed over intense storms. Using deep learning techniques, researchers at NASA Langley Research Center developed software to automatically detect these severe storm signatures in 500m GOES satellite data collected every 5 minutes. Emergency managers can use this raster data to quickly identify locations where severe storms likely occurred, complementing ground-based reports in regions with limited observations. Severe weather on the ground is more likely when OTs and AACPs are both detected and in areas where detections are clustered or observed repeatedly. Long, nearly straight lines of OT and AACP time-aggregated detections can indicate severe storm tracks.Suggested Use and Use Cases:Target audiences: GIS specialists, tactical emergency managersInformation Needed: Near real-time situational awareness about locations where severe storm impacts may have occurred. Example Uses: Target additional information collection. Prioritize field activities (e.g. assessments, resource allocation). Value Proposition: Low resolution, low latency data shows areas that may have recently or may soon experience severe weather (nowcasting).Satellite/SensorSatellite: Geostationary Operational Environmental Satellite (GOES) Satellite remote sensing over North & South AmericaResolution: 5 minute temporal resolution observation frequency, 500m spatial resolutionProduct Specifications: Capability type Experimental Data type Raster of binary OT detections aggregated over a designated incident time frame Min. update frequency Daily during working hours Area coverage Bounded subset Other key attributes Earliest detection time - earliest time (in UTC) an overshooting top was flagged. Count of observations - the number of Overshooting Tops detected within each geostationary satellite 0.5 km pixel for every 5 min conus scan from 2 April 12UTC - 6 April 12UTC. Binary Overshooting Detection Flag - indicator for if any overshooting top was detected over a given 0.5km pixel. Visualization Single-color raster map Time-aggregated plots of severe storm signatures Caveats:While the presence of OTs and AACPs often correlates with severe weather, this product does not observe ground impacts and may detect features that do not correspond to severe weather.Esri REST Endpoint:See URL on the right side of the page.WMS Endpoint:https://maps.disasters.nasa.gov/ags03/services/us_svrwx_202504/severe_storm/MapServer/WMSServerData Download:https://maps.disasters.nasa.gov/download/gis_products/event_specific/2025/us_svrwx_202504/severestorm/

Service Item Id: 06e4feb95ba5401d87f8a6fc493eee1e

Copyright Text: NASA; Jack Cooney, Kris Bedka

Spatial Reference: 4326  (4326)


Single Fused Map Cache: false

Initial Extent: Full Extent: Units: esriDecimalDegrees

Supported Image Format Types: PNG32,PNG24,PNG,JPG,DIB,TIFF,EMF,PS,PDF,GIF,SVG,SVGZ,BMP

Document Info: Supports Dynamic Layers: true

MaxRecordCount: 2000

MaxImageHeight: 4096

MaxImageWidth: 4096

Supported Query Formats: JSON, geoJSON, PBF

Supports Query Data Elements: true

Min Scale: 0

Max Scale: 0

Supports Datum Transformation: true



Child Resources:   Info   Dynamic Layer

Supported Operations:   Export Map   Identify   QueryLegends   QueryDomains   Find   Return Updates