The Spatiotemporal Variability of Temperature and Precipitation Over the Upper Indus Basin: An Evaluation of 15 Year WRF Simulations

被引:17
作者
Dars, Ghulam Hussain [1 ]
Strong, Courtenay [2 ]
Kochanski, Adam K. [2 ]
Ansari, Kamran [1 ]
Ali, Syed Hammad [3 ]
机构
[1] Mehran Univ Engn & Technol, US Pakistan Ctr Adv Studies Water, Jamshoro 76090, Pakistan
[2] Univ Utah, Dept Atmospher Sci, Salt Lake City, UT 84112 USA
[3] Water & Power Dev Author WAPDA, GMRC, Lahore 54000, Pakistan
来源
APPLIED SCIENCES-BASEL | 2020年 / 10卷 / 05期
关键词
WRF-ARW model; Upper Indus Basin; Karakoram region; Pakistan; climate change; HYDROLOGICAL REGIMES; TIBETAN PLATEAU; CLIMATE; KARAKORAM; RIVER; PARAMETERIZATION; HIMALAYA; EVENT;
D O I
10.3390/app10051765
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Investigating the trends in the major climatic variables over the Upper Indus Basin (UIB) region is difficult for many reasons, including highly complex terrain with heterogeneous spatial precipitation patterns and a scarcity of gauge stations. The Weather Research and Forecasting (WRF) model was applied to simulate the spatiotemporal variability of precipitation and temperature over the Indus Basin from 2000 through 2015 with boundary conditions derived from the Climate Forecast System Reanalysis (CFSR) data. The WRF model was configured with three nested domains (d01-d03) with horizontal resolutions increasing inward from 36 km to 12 km to 4 km horizontal resolution, respectively. These simulations were a continuous run with a spin-up year (i.e., 2000) to equilibrate the soil moisture, snow cover, and temperature at the beginning of the simulation. The simulations were then compared with TRMM and station data for the same time period using root mean squared error (RMSE), percentage bias (PBIAS), mean bias error (MBE), and the Pearson correlation coefficient. The results showed that the precipitation and temperature simulations were largely improved from d01 to d03. However, WRF tended to overestimate precipitation and underestimate temperature in all domains. This study presents high-resolution climatological datasets, which could be useful for the study of climate change and hydrological processes in this data-sparse region.
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页数:15
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