The High Resolution Rapid Refresh Atmospheric Model to Supplement a Sparse Measurement Network for Snow Modeling

Operational application of the physically based snow model, iSnobal, over watersheds in the Sierra Nevada, California has surfaced issues associated with the sparse meteorological measurement network. The limited measurements that are available only capture the elevational gradient in the low to mid elevations due to wilderness areas at the highest elevations and can severely affect the uncertainty of the model results. To combat the sparse network, USDA ARS has investigated the use of the High Resolution Rapid Refresh (HRRR), an operational atmospheric model from the National Weather Service, as inputs to iSnobal. HRRR outputs 3km spatial and 1 hour temporal meteorological conditions with everything needed as input to iSnobal. Before using HRRR extensively in an operational application, we must evaluate HRRR inputs for iSnobal to properly understand any potential short comings or strengths of the model integration. We present a comparison of HRRR output from WY 2017 and 2018 to point meteorological measurements and spatial iSnobal results for basins in Idaho and California.