机构地区:[1]Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences [2]Laboratory of Arid Climatic Changing and Reducing Disaster of Gansu Province, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences [3]Institut fr Umweltplanung, Gottfried Wilhelm Leibniz Universitt [4]Department of Plants, Soils, and Climate, Utah State University
出 处:《Advances in Atmospheric Sciences》2013年第5期1449-1460,共12页大气科学进展(英文版)
基 金:under the auspices of the National Natural Science Foundation of China (Grant No. 41275014);the National Basic Research Program of China (973 Program) Project (Grant No. 2010CB950503)
摘 要:This study investigates the impact of rain snow threshold (RST) temperatures on snow depth simulation using the Community Land Model (CLM) and the Weather Research and Forecasting model (WRF--coupled with the CLM and hereafter referred to as WRF_CLM), and the difference in impacts. Simulations were performed from 17 December 1994 to 30 May 1995 in the French Alps. Results showed that both the CLM and the WRF_CLM were able to represent a fair simulation of snow depth with actual terrain height and 2.5~C RST temperature. When six RST methods were applied to the simulation using WRF_CLM, the simulated snow depth was the closest to observations using 2.5~C RST temperature, followed by that with Pipes', USACE, Kienzle's, Dai's, and 0~C RST temperature methods. In the case of using CLM, simulated snow depth was the closest to the observation with Dai's method, followed by with USACE, Pipes', 2.5~C RST temperature, Kienzle's, and 0~C RST temperature method. The snow depth simulation using the WRF_CLM was comparatively sensitive to changes in RST temperatures, because the RST temperature was not only the factor to partition snow and rainfall. In addition, the simulated snow related to RST temperature could induce a significant feedback by influencing the meteorological variables forcing the land surface model in WRF_CLM. In comparison, the above variables did not change with changes in RST in CLM. Impacts of RST temperatures on snow depth simulation could also be influenced by the patterns of temperature and precipitation, spatial resolution, and input terrain heights.This study investigates the impact of rain snow threshold (RST) temperatures on snow depth simulation using the Community Land Model (CLM) and the Weather Research and Forecasting model (WRF--coupled with the CLM and hereafter referred to as WRF_CLM), and the difference in impacts. Simulations were performed from 17 December 1994 to 30 May 1995 in the French Alps. Results showed that both the CLM and the WRF_CLM were able to represent a fair simulation of snow depth with actual terrain height and 2.5~C RST temperature. When six RST methods were applied to the simulation using WRF_CLM, the simulated snow depth was the closest to observations using 2.5~C RST temperature, followed by that with Pipes', USACE, Kienzle's, Dai's, and 0~C RST temperature methods. In the case of using CLM, simulated snow depth was the closest to the observation with Dai's method, followed by with USACE, Pipes', 2.5~C RST temperature, Kienzle's, and 0~C RST temperature method. The snow depth simulation using the WRF_CLM was comparatively sensitive to changes in RST temperatures, because the RST temperature was not only the factor to partition snow and rainfall. In addition, the simulated snow related to RST temperature could induce a significant feedback by influencing the meteorological variables forcing the land surface model in WRF_CLM. In comparison, the above variables did not change with changes in RST in CLM. Impacts of RST temperatures on snow depth simulation could also be influenced by the patterns of temperature and precipitation, spatial resolution, and input terrain heights.
关 键 词:snow simulation RST temperature WRF_CLM CLM
分 类 号:P426.635[天文地球—大气科学及气象学] S661.1[农业科学—果树学]
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