Data Availability for use in High Resolution Snowpack Modeling

The growing population of the western United States relies heavily on water resources stored in the form of high elevation snowpack. Managing water resources may be impeded by the absence of surface data with high spatial and temporal resolution. The high cost of installing and maintaining such networks often limits their coverage to an extent below what is required to provide adequate data coverage necessary to drive high resolution model simulations. Rather than rely on interpolating a limited amount of station data over environments known for variability in meteorological parameters, an alternative can be found in very high resolution atmospheric analysis routines such as Local Analysis and Prediction System (LAPS) and the North American Land Data Assimilation System (NLDAS). These routines provide spatial resolutions that are orders of magnitude greater than surface observations, while at the same time maintaining the benefits of real world forcing. A modeling study using LAPS and NLDAS was proposed to investigate snowpack water loss via the process of sublimation. This study spanned the majority of the Upper Colorado River Basin, and was carried out using a numerical snow-evolution model known as SnowModel at spatial resolutions of 100 meters or less.