Improvements to the Assimilation of Doppler Radial Winds for Convection-Permitting Forecasts of a Heavy Rain Event

Abstract

AbstractThis work describes developments to improve the Doppler radial wind data assimilation scheme used in the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) data assimilation system with a focus on convection-permitting, 0–18-h forecasts of a heavy precipitation single case study. This work focuses on two aspects: 1) the extension of the radial wind observation operator to include vertical velocity and 2) a refinement of the radial wind super-observation processing. The refinement includes reducing the magnitude of observation smoothing and allowing observations from higher scan angles into the analysis with the intent to improve the assimilation of the radar data for operational, convection-permitting models. The results of this study demonstrate that there is sensitivity to the refinement in super-observation settings. The inclusion of vertical velocity in the observation operator is shown to have a neutral to slightly positive impact on the forecast. Results from this study are suggested to be used as a foundation to prioritize future research into the effective assimilation of radial winds in an operational setting.