Characterizing and optimizing precipitation forecasts from a convection-permitting ensemble initialized by a mesoscale ensemble Kalman filter

Subensembles composed of 20–30 members usually demonstrated comparable resolution, reliability, and skill as the full 50-member ensemble. On average, deterministic forecasts initialized from mean EnKF analyses were at least as or more skillful than forecasts initialized from individual ensemble members "closest" to the mean EnKF analyses, and "patched together" forecasts composed of members closest to the ensemble mean during each forecast interval were skillful but came with caveats.

The collective results underscore the need to improve convection-permitting ensemble spread and have important implications for optimizing EnKF-initialized forecasts.