Training materials

• ProbSevere version 2 (operational)
• ProbSevere version 3
• IntenseStormNet
• LightningCast

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ProbSevere v2

Real-time page.

Training video and slides

Click for Powerpoint Articulate Training Module
Download Training Slides

WFO-centric validation map

GRLevelX placefiles (v2.60+ required for loops)

• ProbSevere 1-hr loop
• ProbSevere latest scan
• ProbTor 1-hr loop
• ProbTor latest scan

Publications and presentations

• NOAA ProbSevere v2.0--ProbHail, ProbWind, and ProbTor, WAF (2020)
• The NOAA/CIMSS ProbSevere Model: Incorporation of Total Lightning and Validation, WAF (2018)
• An Empirical Model for Assessing the Severe Weather Potential of Developing Convection, WAF (2014)
• Evolution of Severe and Nonsevere Convection Inferred from GOES-Derived Cloud Properties, JAMC (2013)
• A Satellite-Based Convective Cloud Object Tracking and Multipurpose Data Fusion Tool with Application to Developing Convection, J. Tech. (2012)
• Advances in Extracting Cloud Composition Information from Spaceborn Infrared Radiances--A Robust Alternative to Brightness Temperatures. Part I: Theory, JAMC (2010)
• Preliminary Evaluation of a Fused Algorithm for the Prediction of Severe Storms, AMS Annual Meeting (2014)
• NWS Great Lakes SOOs talk (2018)
• NWS Great Lakes SOOs talk (2016)
• NWS Southern Region talk (2016)
• NWS Western Region talk (2016)
• NWS Central Region talk (2015)

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ProbSevere v3

Experimental real-time page.

Training video and slides

Training slides

Model predictors

GRLevelX placefiles (v2.60+ required)

• ProbSevere-v3 1-hr loop
• ProbTor-v3 1-hr loop

Publications and presentations

• ProbSevere Version 3: Improved Exploitation of Data Fusion and Machine Learning for Nowcasting Severe Weather, WAF (2024)
• NWS Southern Region Science Circle (April 2022)

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IntenseStormNet

See this blog post for a succinct introduction to IntenseStormNet. Other related posts can be found on the CIMSS satellite blog and GOES-R HWT blog.

Experimental real-time page.

Publications and presentations

• A Deep-Learning Model for Automated Detection of Intense Midlatitude Convection Using Geostationary Satellite Images, WAF (2020)
• A Deep-Learning Approach to Severe Convective Weather Prediction Using Geostationary Satellite Data, AMS satellite conference (2019)

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LightningCast (probability of lightning)

See this blog post for a succinct introduction to LightningCast.

Experimental real-time page.

Training video and slides

Download training slides

GRLevelX placefiles (v2.60+ required)

These placefiles are all parallax-corrected with a constant cloud-height assumption of 9 km.

• GOES-East CONUS sector
• GOES-East Meso1 sector
• GOES-East Meso2 sector
• GOES-West CONUS sector
• GOES-West Meso1 sector
• GOES-West Meso2 sector

Publications and presentations

• NOAA’s ProbSevere LightningCast: Progress and Updates toward Transition-to-Operations (AMS Annual Meeting 2024)
• Applying ProbSevere LightningCast (invited, NWS SOO meeting 2023)
• ProbSevere LightningCast for decision-support services (AMS Annual Meeting 2023)
• NOAA’s ProbSevere LightningCast: Artificial intelligence for nowcasting lightning from geostationary satellites (EUMETSAT 2022)
• ProbSevere LightningCast: A Deep-Learning Model for Satellite-based Lightning Nowcasting, WAF (2022)
• NESDIS Satellite Book Club (2021)
• NWS Southern Region Science Circle (2021)
• Using GOES ABI and Deep Learning to Nowcast Lightning (Monday Jan 11; Joint 2.5), AMS Annual Meeting (2021)
• Lightning Prediction in the Atlantic offshore region, NOAA AI Workshop (2020)

Notebooks

• Using machine learning to train a lightning nowcasting model

Verification

These verification metrics, for LCv1 (ABI-only predictors) were computed from the GOES-16 CONUS sector, every 10 minutes, for approximately all of 2023.

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