A Mesoscale Study of the Role of Snowpack in Climate Variability and Water Resources Over the Sierra Nevada Region

The Penn Sate-National Center for Atmospheric Research fifth-generation Mesoscale Model driven by a 6-hourly reanalysis dataset from the National Centers for Environment Prediction has been used to study the impact of snowpack on climate variability and water resources over the Sierra Nevada region. The analyses on a one way 48km-12km nested model run during the 1998 snowmelt season (April - June) showed that the underestimated snowpack produced a strong warm bias at the surface and low level atmosphere, which strengthened the convective precipitation, and dried streamflow in the region. An observed daily snowpack dataset collected from the automated Snowpack Telemetry system was assimilated in the model to improve its performance. The results showed that the assimilation processes greatly reduced the warm bias because the tremendous amount of energy used to increase the temperature in the original model run was consumed by snowmelt. Meanwhile, the increased surface albedo that resulted from the assimilated thicker snowpack played a secondary role in the temperature reduction. The cooled surface and low atmosphere led to a more stable simulated atmospheric structure, reduced the intensity of spring storms, and therefore, suppressed the exaggerated convective precipitation. Simulated runoff, based on the observed snowpack, also approached the observed runoff amounts within the model domain studied. Moreover, the origin of the simulated lower snowdepth and the model predictability on snowpack as well as the associated variables in the snowmelt season have been investigated through model sensitivity tests.