Evaluation of snowmelt simulation in the Weather Research and Forecasting model

被引:34
|
作者
Jin, Jiming [1 ,2 ]
Wen, Lijuan [1 ,2 ]
机构
[1] Utah State Univ, Dept Watershed Sci, Logan, UT 84322 USA
[2] Utah State Univ, Dept Plants Soils & Climate, Logan, UT 84322 USA
关键词
LAND-SURFACE PROCESSES; WESTERN UNITED-STATES; PART I; SNOWPACK; TRENDS; PARAMETERIZATION; PRECIPITATION; VARIABILITY; CIRCULATION; HYDROLOGY;
D O I
10.1029/2011JD016980
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The objective of this study is to better understand and improve snowmelt simulations in the advanced Weather Research and Forecasting (WRF) model by coupling it with the Community Land Model (CLM) Version 3.5. Both WRF and CLM are developed by the National Center for Atmospheric Research. The automated Snow Telemetry (SNOTEL) station data over the Columbia River Basin in the northwestern United States are used to evaluate snowmelt simulations generated with the coupled WRF-CLM model. These SNOTEL data include snow water equivalent (SWE), precipitation, and temperature. The simulations cover the period of March through June 2002 and focus mostly on the snowmelt season. Initial results show that when compared to observations, WRF-CLM significantly improves the simulations of SWE, which is underestimated when the release version of WRF is coupled with the Noah and Rapid Update Cycle (RUC) land surface schemes, in which snow physics is oversimplified. Further analysis shows that more realistic snow surface energy allocation in CLM is an important process that results in improved snowmelt simulations when compared to that in Noah and RUC. Additional simulations with WRF-CLM at different horizontal spatial resolutions indicate that accurate description of topography is also vital to SWE simulations. WRF-CLM at 10 km resolution produces the most realistic SWE simulations when compared to those produced with coarser spatial resolutions in which SWE is remarkably underestimated. The coupled WRF-CLM provides an important tool for research and forecasts in weather, climate, and water resources at regional scales.
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页数:16
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