Simulation of Northern Eurasian Local Snow Depth, Mass, and Density Using a Detailed Snowpack Model and Meteorological Reanalyses

被引:111
作者
Brun, Eric [1 ,2 ]
Vionnet, Vincent [1 ,2 ]
Boone, Aaron [1 ,2 ]
Decharme, Bertrand [1 ,2 ]
Peings, Yannick [1 ,2 ]
Valette, Remi [1 ,2 ]
Karbou, Fatima [3 ,4 ]
Morin, Samuel [3 ,4 ]
机构
[1] Meteo France, CNRM GAME, F-31057 Toulouse, France
[2] CNRS, F-31057 Toulouse, France
[3] Meteo France, CNRM GAME, Grenoble, France
[4] CNRS, Ctr Etudes Neige, Grenoble, France
关键词
INDIAN-SUMMER MONSOON; LAND-SURFACE MODEL; BLOWING-SNOW; WATER EQUIVALENT; RADIOMETER DATA; COVER; VARIABILITY; SOIL; SUBLIMATION; VALIDATION;
D O I
10.1175/JHM-D-12-012.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The Crocus snowpack model within the Interactions between Soil Biosphere Atmosphere (ISBA) land surface model was run over northern Eurasia from 1979 to 1993, using forcing data extracted from hydrometeorological datasets and meteorological reanalyses. Simulated snow depth, snow water equivalent, and density over open fields were compared with local observations from over 1000 monitoring sites, available either once a day or three times per month. The best performance is obtained with European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim). Provided blowing snow sublimation is taken into account, the simulations show a small bias and high correlations in terms of snow depth, snow water equivalent, and density. Local snow cover durations as well as the onset and vanishing dates of continuous snow cover are also well reproduced. A major result is that the overall performance of the simulations is very similar to the performance of existing gridded snow products, which, in contrast, assimilate local snow depth observations. Soil temperature at 20-cm depth is reasonably well simulated. The methodology developed in this study is an efficient way to evaluate different meteorological datasets, especially in terms of snow precipitation. It reveals that the temporal disaggregation of monthly precipitation in the hydrometeorological dataset from Princeton University significantly impacts the rain snow partitioning, deteriorating the simulation of the onset of snow cover as well as snow depth throughout the cold season.
引用
收藏
页码:203 / 219
页数:17
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