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Hot off the press: The OU School of Meteorology (Oklahoma Meteorology) & School of Civil Engineering and Environmental Science have a joint tenure-track faculty position focused on the broad areas of Hydrometeorology and Hydrology that is now open. Apply here: apply.interfolio.com/137372

Great presentations from #NSSL scientists continue here at #AMS2024, including researchers Kim Hoogewind and Adam Clark at the NOAA booth talking about trends in severe thunderstorms and tornadoes in a changing climate.

**Experimental (Not Public Yet)** The new AI hail size algorithm says 2 in is possible!

Our paper on the usefulness of the "WoFS-ML-Severe" products examined during the 2022 HWT-SFE is available in EOR. This paper explores subjective verification, objective verification, and qualitative analysis of the participant's feedback. journals.ametsoc.org/view/journals/…

🤔How can science provide more warning when 🌪️tornadoes threaten? The Warn-on-Forecast System, equips forecasters with critical information between watches and warnings, enabling them to give longer lead times in the face of severe weather and tornadoes. inside.nssl.noaa.gov/nsslnews/2024/…

Our paper combining AI/ML, storm-scale ensemble prediction, and "forecasting forecast skill" is now in final form in @AMS_AIES: doi.org/10.1175/AIES-D… Co-authors: Montgomery Flora, Ph.D., Patrick Skinner, @tonyreinhart, Brian Matilla

Huge kudos to Montgomery Flora, Ph.D. for leading this awesome work! AI will undoubtedly play a major role in NWP at all scales.

Monte Flora: Future of storm-scale AI: generating large-member (100+) hi-res (~1-km) ensemble forecasts in seconds. AI system in the WoFS framework already can produce “closely matching” forecasts with far less computational burden than #WoFS (far faster). #31sls

WoFSCast is the first AI system trained and developed to emulate a sub-hourly convection-allowing weather model (CAM). WoFSCast speeds up forecast generation versus WoFS by at least a factor of ten, from minutes to seconds. #AMS2025

🌪️🌩️ Studying tornadoes in the field has always been at the heart of the NSSL mission. With roots in the 90s, the VORTEX-USA project continues to blaze a trail in tornado science with the ultimate goal to protect lives and property. 🌪️ UP CLOSE: inside.nssl.noaa.gov/nsslnews/2024/…

🚨 New paper! 🚨 Available in EOR is our paper exploring training AI models on MRMS MESH vs. reported hail sizes: journals.ametsoc.org/view/journals/…

🤖 How can AI help scientists predict thunderstorms faster? 🤔 A new paper from NSSL and CIWRO discusses how WoFSCast, a new AI-powered model, can accurately predict how storms will evolve up to two hours in advance. ⛈️ 📝: inside.nssl.noaa.gov/nsslnews/2025/…

Meteorologists are turning to AI as a quick, efficient alternative to traditional weather prediction algorithms. Now researchers including Montgomery Flora, Ph.D. & Corey K Potvin have extended this tech to cover localized extreme weather as well as global forecasts. eos.org/research-spotl…

Can we use AI to predict thunderstorm evolution? Recently published in AGU (American Geophysical Union) GRL, we refactored Google DeepMind's GraphCast for regional modeling and trained it on CIWRO / NOAA National Severe Storms Laboratory's archived Warn-on-Forecast System (WoFS) data.