Revisiting Sensitivity to Horizontal Grid Spacing in Convection-Allowing Models over the Central-Eastern United States Using a Large Dataset

This presentation will describe results from 497 retrospective, deterministic, 36-h Weather Research and Forecasting (WRF) model forecasts with 3- and 1-km horizontal grid spacing over the conterminous United States (CONUS) east of the Rockies, with a focus on next-day precipitation and tornado forecasts. The 497 cases were chosen based on observed severe weather events occurring between 2010–2017 and spanned both the warm and cool seasons.

Model surrogates of low-level rotation (such as updraft helicity) indicated 1-km forecasts yielded more accurate next-day tornado forecasts than 3-km forecasts. Furthermore, 1-km model climatologies of precipitation generally aligned better with those observed than 3-km climatologies. Regarding precipitation placement, during the cool season and spring, when large-scale forcing was strong and precipitation entities were large, 1-km precipitation forecasts were more skillful than 3-km forecasts. Conversely, during summertime, when synoptic-scale forcing was weak and precipitation entities were small, 3- and 1-km precipitation forecasts had similar skill.

These collective results differ substantially from previous work finding 4-km forecasts had comparable springtime skill as 1- or 2-km forecasts over the central–eastern CONUS, and hypotheses regarding this disparity will be provided.