| description abstract | Numerical simulations of two snowfall events over the Black Hills of South Dakota are made to demonstrate the use and potential of a coupled atmospheric and land surface model. The Coupled Atmospheric?Hydrologic Model System was used to simulate a moderate topographic snowfall event of 10?11 April 1999 and a blizzard event of 18?23 April 2000. These two cases were chosen to provide a contrast of snowfall amounts, locations, and storm dynamics. The model configuration utilized a nested grid with an outer grid of 16-km spacing driven by numerical forecast model data and an inner grid of 4 km centered over the Black Hills region. Simulations for the first case were made with the atmospheric model, the Advanced Regional Prediction System (ARPS) alone, and with ARPS coupled with the National Center for Atmospheric Research Land Surface Model (LSM). Results indicated that the main features of the precipitation pattern were captured by ARPS alone. However, precipitation amounts were greatly overpredicted. ARPS coupled with LSM produced a very similar precipitation pattern, but with precipitation amounts much closer to those observed. The coupled model also permits simulation of the resulting snow cover and snowmelt. Simulated percentage snow melting occurred somewhat more rapidly than that of the observed. Snow?rain discrimination may be taken from the precipitation type falling out of the atmospheric model based on the microphysical parameterization, or by the use of a surface temperature criteria, as used in most large-scale models. The resulting snow accumulation patterns and amounts were nearly identical. The coupled model configuration was used to simulate the second case. In this case the simulated precipitation and snow depth maximum over the eastern Black Hills were biased to the east and north by about 24 km. The resulting spatial correlation of the simulated snowfall and observations was only 0.37. If this bias is removed, the shifted pattern over the Black Hills region has a correlation of 0.68. Snow-melting patterns for 21 and 22 April appeared reasonable, given the spatial bias in the snowfall simulation. | |
