An examination of the impact of grid spacing on WRF simulations of wintertime precipitation in the Mid-Atlantic United States

A large set of deterministic and ensemble forecasts was produced to identify the optimal spacing for forecasting U.S. East Coast snowstorms. WRF forecasts were produced on cloud-allowing (similar to 1-km grid spacing) and convection-allowing (3-4 km) grids, and compared against forecasts with parameterized convection (> similar to 10 km). Performance diagrams were used to evaluate 19 deterministic forecasts from the winter of 2013-14. Ensemble forecasts of five disruptive snowstorms spanning the years 2015-18 were evaluated using various methods to evaluate probabilistic forecasts. While deterministic forecasts using cloud-allowing grids were not better than convection-allowing forecasts, both had lower bias and higher success ratios than forecasts with parameterized convection. All forecasts were underdispersive. Nevertheless, forecasts on the higher-resolution grids were more reliable than those with parameterized convection. Forecasts on the cloud-allowing grid were best able to discriminate areas that received heavy snow and those that did not, while the forecasts with parameterized convection were least able to do so. It is recommended to use convection-resolving and (if computationally possible) to use cloud-allowing forecast grids when predicting East Coast winter storms.