6 papers
Explainable Deep Learning for Probabilistic Nowcasting of Radar Reflectivity in Tornadic Storms
Nathan Erickson, Amy McGovern, Aaron Hill
Tornadoes pose substantial risk to human life and property in the United States, causing more than 50 fatalities and $100 million of property damage on average annually. When torn…
Diffusion-Based Rollouts as a Stabilization Mechanism for Long-Horizon Environmental Forecasting
Marina Vicens-Miquel, Amy McGovern, Aaron J. Hill +2
Extending forecast lead times while maintaining predictive skill remains a major challenge in environmental forecasting. We investigate diffusion-based rollouts as a stabilization…
Global Evaluation of AI and NWP Precipitation Forecasts During Atmospheric River Events
Marina Vicens-Miquel, Taylor Mandelbaum, Amy McGovern +2
Atmospheric rivers (ARs) produce many of the world's most extreme precipitation events and hydrometeorological hazards. Although artificial intelligence weather prediction (AIWP) m…
Prediction of Drought and Flash Drought in Africa at the Seasonal-to-Subseasonal Scale using the Community Research Earth Digital Intelligence Twin Framework
Stuart Edris, Amy McGovern, Jason Hickey
Droughts and flash droughts (rapidly developing droughts; FDs) remain impactful events that are known to desiccate landscape and destroy crops. In particular, droughts in Africa ar…
A Diffusion-Based Framework for High-Resolution Precipitation Forecasting over CONUS
Marina Vicens-Miquel, Amy McGovern, Aaron J. Hill +3
Accurate precipitation forecasting is essential for hydrometeorological risk management, especially for anticipating extreme rainfall that can lead to flash flooding and infrastruc…
Oya: Deep Learning for Accurate Global Precipitation Estimation
Emmanuel Asiedu Brempong, Mohammed Alewi Hassen, MohamedElfatih MohamedKhair +7
Accurate precipitation estimation is critical for hydrological applications, especially in the Global South where ground-based observation networks are sparse and forecasting skill…