A four-dimensional Coupled Data Assimilation System (CDAS) using a forward, full-physics model in which the precipitation and clouds are an optimized combination of observed and forecast fields has been developed at the Forecast Systems Laboratory. It is based on the Rapid Update Cycle, and the precipitation and cloud fields are updated hourly using GOES cloud-top pressure, NEXRAD radar reflectivity, lightning data, and GPS precipitable water. The resolution of the RUC CDAS is 20 km, with high-resolution fixed surface fields from USGS (land-use) and STATSGO soil types.

This system runs in real time and provides refinements to the 0-1 hour precipitation forecasts that drive a land-surface climate in the model by accounting for errors in both observations and model precipitation forecasts. As a result cycled soil moisture and snow water equivalent are improved compared to the operational RUC without assimilation of the radar, lightning and GPS data. Most improvements occur from more accurate placement of predicted precipitation. At the same time certain deficiencies still exist in the amounts of the precipitation in RUC CDAS, causing most often underestimation of cycled snow depth. This also has a delayed effect on the soil moisture climate and surface physics in the warm season.

Further improvements of the cycled snow depth could be achieved by updating the snow state fields from existing observations. This approach has been implemented at the National Operational Hydrologic Remote Sensing Center (NOHRSC) National Snow Analysis (NSA). The NOHRSC snow model is forced by the RUC precipitation and atmospheric forcing. Therefore, work on further improvements of the RUC snow variables and 0-1h precipitation will be beneficial for both RUC and NOHRSC NSA. The first step in this direction is to compare RUC CDAS snow state variables to the NOHRSC NSA and identify the areas with the largest deficiencies. Results of these comparisons will be presented at the meeting, as well as the comparisons between the RUC CDAS snow water equivalent with the operational RUC.