Consistent with the RAP focus on providing short-range situational awareness guidance for aviation, severe weather, renewable energy and other forecast applications, a sophisticated set of analysis procedures have been developed for initializing 3-D hydrometeor fields in cloudy and precipitating areas. Cloud/hydrometeor fields are initialized via a non-variational cloud analysis procedure, which uses METAR and satellite-derived cloud-top information to modify hourly cycled explicit 3-D cloud hydrometeor fields. Recent work has focused on 1) reducing a positive moisture bias (relative to radiosonde observations) introduced from satellite observation-based mid- and high-level cloud building while 2) still improving retention of initial cloud fields through model improvements.
We will present recent modifications to both the data assimilation and model numerics for the RAP and the experimental 3-km HRRR model to improve ceiling and visibility forecasts. We will also show work on a new 3-km analysis application of the fully 3D Gridpoint Statistical Interpolation (GSI, including the cloud, radar, and surface analysis modules) to 3-km HRRR background fields. Initial results have been encouraging and the fully 3D 3-km analysis has many possible uses, including improved HRRR forecasts.