NOHRSC OPERATIONS AND THE SIMULATION OF SNOW COVER PROPERTIES FOR THE COTERMINOUS U.S.

The National Operational Hydrologic Remote Sensing Center (NOHRSC), National Weather Service (NWS), National Oceanic and Atmospheric Administration (NOAA), generates satellite-derived areal extent of snow cover observations and makes airborne snow water equivalent measurements over large regions of the country. Additionally, the NOHRSC ingests a wide variety of real-time, ground-based hydrometeorological data sets along with real-time, numerical weather prediction (NWP) model data sets for the country. NWP model output data sets are used to force a physically-based, snow-modeling, and snow-data-assimilation system. The ground-based, airborne, and satellite snow cover observations will soon be assimilated, in near real-time, into the gridded fields generated by the snow accumulation and ablation model. Products include a variety of alphanumeric and gridded representations of the snow pack state variables.A distributed, energy-and-mass-balance snow model and data assimilation system has been developed and implemented at the NOHRSC to augment basic hydrologic analysis. The purpose of the Snow Data Assimilation System (SNODAS) is to provide a physically consistent framework for integrating the wide variety of snow data that is available at various times. SNODAS includes: (1) data ingest and downscaling procedures, (2) a spatially distributed energy-and-mass-balance snow model that is run once each day, for the previous 24-hour period and for a 12-hour forecast period, at high spatial (1 kin) and temporal (1 hr) resolutions, and (3) data assimilation and updating procedures. The snow model is driven by downscaled analysis and forecast fields from a mesoscale, NWP model, surface weather observations, satellite-derived solar radiation data, and radar-derived precipitation data. The snow model states can be updated using satellite, airborne, and ground-based snow observations. The model is cast in an assimilation framework and serves to organize various snow observations and to track the evolution of the snow pack between observations. SNODAS permits more frequent and timely product generation—near real-time model analyses and forecasts—and provides several new products, including maps of modeled snow characteristics such as snow ripeness, melt rates, and sublimation losses. Preliminary simulations for test periods during the 2001 snow season give encouraging results.