Deep Learning for CAPE Bias Correction in the NOAA Global Forecast System

Accurate forecasting of Convective Available Potential Energy (CAPE) is critical for severe weather prediction. However, the operational GFS model exhibits a persistent low-CAPE bias. In this work, we apply a two-step regression–diffusion model (NVIDIA CorrDiff) to address this issue. Our results indicate that while a standard U-Net can successfully reduce the bulk systematic bias, the generated output remains overly smoothed. This occurs because, for data with long-tailed statistical distributions such as CAPE,…