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A physically-based snow model coupled to a general circulation model for hydro-climatological studies

Posted on:2003-05-05Degree:Ph.DType:Dissertation
University:The University of ArizonaCandidate:Jin, JimingFull Text:PDF
GTID:1460390011489156Subject:Hydrology
Abstract/Summary:
A Snow-Atmosphere-Soil Transfer (SAST) model has been developed to extend the point snowmelt model to vegetated areas using the parameterization concepts of the Biosphere-Atmosphere Transfer Scheme (Dickinson et al. 1993). The model applications for short-grass and forest fields show that the simulated surface temperature, albedo, and snow depth have close agreement with observations. In addition, because of biases in simulated runoff in the high-latitudes, a Shuffled Complex Evolution (Sorooshian et al. 1993) scheme for automatic calibration has been connected with the SAST model to determine the realistic distribution of runoff components from different soil layers and search the optimized parameter set. The calibrated runoff closely matches observations.; Because the Community Climate Model version 3 (CCM3) coupled with the SAST model overestimates snow depth and precipitation and underestimates surface temperature over the Rocky Mountains, remotely sensed snow depth data have been assimilated in the model to alleviate model discrepancies based on energy and mass balances. The improved surface temperature simulations result from the decreased snowmelt and albedo in winter and spring and from the weakened evaporation in summer due to drier soil. Meanwhile, modeled summer precipitation over the Rocky Mountains has a minor improvement.; The relationship between the variations of tropical Pacific SST and snowpack anomalies in the western United States (U.S.) has been studied by comparing observations and CCM3 output. The results indicate that in the northwestern U.S., the warm tropical Pacific phase of the El Niño-Southern Oscillation (ENSO) is associated with diminished snowpack while its cool phase is related to enhanced snowpack. This relationship is largely determined by winter precipitation variability for the observations; however, it relies heavily on the variations of temperature due to the biases in atmospheric patterns for the model output. In the southwestern U.S., positive snowpack anomalies for both observations and simulations result from the strong warm phase of the ENSO and negative ones are connected with exaggerated local precipitation in fall.
Keywords/Search Tags:Model, Snow, SAST, Precipitation
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