Abstract
As part of the 2022 NOAA Hazardous Weather Testbed Spring Forecasting Experiment, the Center for Analysis and Prediction of Storms produced FV3-LAM real-time ensemble forecasts to study its use in convection-allowing ensemble forecasts for the severe weather forecasting problem and to inform the optimization of the upcoming operational Rapid Refresh Forecast System. We evaluate deterministic and ensemble forecasts in terms of surrogate severe weather reports (SSRs) and surrogate severe probability forecasts (SSPFs) created from simulated 0–3- and 2–5-km updraft helicity (UH), and 10-m wind speed. Forecasts are verified against observed storm reports (OSRs) and observed severe probabilistic fields (OSPFs) derived from tornado and hail, wind, and all types of local storm reports, and 0600 UTC Day 1 convective outlooks issued by the Storm Prediction Center (SPC) for three cases.
UH ensemble SSPFs have better reliability and discrimination when verified with OSRs from all storm reports. Spatial smoothing generally increases reliability while smaller smoothing lengths optimize discrimination ability. Case studies demonstrate that UH SSPFs are consistent with SPC Day 1 convective outlooks, indicating that these forecasts are qualitatively similar to operational guidance. The ensemble mean of SSRs is generally more skillful than individual members when based on UH, but not 10-m wind. In fact, SSRs and SSPFs based on 10-m wind display little skill predicting severe wind events; we therefore conclude that UH seems to better inform severe hazard risk, even compared to prognosed surface wind speed. Model resolution dictates its ability to prognose rotating updrafts and severe wind.
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