Improving Ensemble CAPE Forecasts with a Diffusion Model Incorporating Aerosol Information
Convective available potential energy (CAPE) is an important variable for forecasting severe weather and understanding deep convection and precipitation. The latest versions of the Global Forecast System (GFS) and related Global Ensemble Forecast System (GEFS) have exhibited a bias towards underestimating CAPE values during the summertime. We train an artificial intelligence (AI) diffusion model to improve the skill and uncertainty quantification of afternoon 6-hour lead time ensemble forecasts over the United States. Our model takes a GFS CAPE forecast as input and outputs an ensemble that significantly outperforms both GFS and GEFS 6-hour forecasts on root mean square error, continuous ...
| Authors | Zachary James, Joseph Guinness, Arthur DeGaetano |
|---|---|
| Primary category | physics.ao-ph |
| Published | 19 May 2026 |
| Last updated at source | 19 May 2026 |
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