Advancing the Rapid Refresh Cloud and Precipitation Hydrometeor Analysis Towards Hybrid Ensemble-Variational Data Assimilation

The 13-km Rapid Refresh (RAP) and 3-km convective-allowing High-Resolution Rapid Refresh (HRRR) are hourly updating weather forecast models that use a specially configured version of the Advanced Research WRF (ARW) model and assimilate many novel and most conventional observation types on an hourly basis using Gridpoint Statistical Interpolation (GSI). Included in this assimilation is a procedure for initializing ongoing precipitation systems from observed radar reflectivity data, a cloud analysis to initialize stable layer clouds from METAR and satellite observations, and special techniques to enhance retention of surface observation information.

This cloud and precipitation hydrometeor analysis is currently non-variational and explicitly builds or removes cloud and precipitating hydrometeors and correspondingly saturates or dries the background to support the cloud hydrometeor changes. In order to improve the analysis and prediction of clouds and precipitation we are beginning the process of transitioning this analysis process to a variational and then hybrid ensemble-variational system. To this end, this presentation will demonstrate initial work to accomplish this goal through generalization of background and observation input-output for all GSI applications and the formation of new hydrometeor observation operators including the addition of cloud control variables and establishing static background covariances for cloud hydrometeors.