Will Perturbing Soil Moisture Improve Warm-Season Ensemble Forecasts? A Proof of Concept

Current generation short-range ensemble forecast members tend to be unduly similar to each other, especially for variables such as surface temperature. One possible cause of this is a lack of perturbations to the land-surface state. In this experiment, a two member-ensemble of the WRF model was run from two different soil moisture analyses. One-day forecasts were conducted for six warm-season cases over the central United States, both with explicitly resolved convection at 5-km grid spacing and with parameterized convection at 20-km grid spacing. At 5 km, the forecast differences due to changing the soil moisture were comparable to the differences in 20-km simulations with the same soil moisture but with a different convective parameterization. The differences of 20-km simulations from different soil moistures were less than the differences from changing the convective parameterization. Perturbing the state of the land surface is thus judged to be likely to improve operational short-range ensemble forecasts of precipitation and surface temperature, especially for explicitly resolved convective forecasts at high resolution.