Primary Convener:
Guoqing Ge, CIRES, University of Colorado Boulder

Convener:
Minghua Zheng, Center for Western Weather and Water Extremes (CW3E), Scripps Institution of Oceanography, UC San Diego
Haiqin Li, Cooperative Institute for Research in Environmental Sciences (CIRES)
Anders Jensen, NOAA/GSL

Chair:
Guoqing Ge, CIRES/NOAA GSL
Minghua Zheng, Center for Western Weather and Water Extremes (CW3E), Scripps Institution of Oceanography, UC San Diego
Haiqin Li, Cooperative Institute for Research in Environmental Sciences (CIRES)
Anders Jensen, NOAA/GSL

High-impact weather events, such as extreme rainfall, severe storms, damaging winds, landfalling atmospheric rivers, hurricanes/typhoons, wildfires, heatwaves, and droughts, have significant impacts on our society and daily life. Atmospheric modeling, data assimilation, artificial intelligence (AI)/machine learning (ML), and Research to Operations (R2O) play a crucial role in enhancing forecasts for these events. This session will focus on recent research and advancements in atmospheric modeling, data assimilation, artificial intelligence, and R2O aimed at improving analyses and forecasts for high-impact weather events, including those intended for operational and impact-oriented applications. We encourage submissions that explore various topics, such as the development and enhancement of model physics, advancements in data assimilation algorithms and systems, observational impact studies, ensemble forecasting and predictability, R2O activities, forecast verification, synergies between AI and DA (AI4DA), synergies between AI and modeling (AI4NWP), and other relevant studies.

Index Terms
0320 Cloud physics and chemistry
3315 Data assimilation
3399 General or miscellaneous
1942 Machine learning

Suggested Itineraries:
Machine Learning and AI

Neighborhoods:
3. Earth Covering