Assessment of Precipitation Simulations in Central Asia by CMIP5 Climate Models

被引:33
|
作者
Ta, Zhijie [1 ,2 ,3 ]
Yu, Yang [1 ,3 ]
Sun, Lingxiao [1 ,3 ]
Chen, Xi [1 ,3 ]
Mu, Guijin [1 ,3 ]
Yu, Ruide [1 ,3 ]
机构
[1] Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China
[2] Xinjiang Univ, Coll Resource & Environm Sci, Urumqi 830046, Peoples R China
[3] Univ Chinese Acad Sci, Xinjiang Inst Ecol & Geog, Beijing 100049, Peoples R China
关键词
CMIP5; precipitation; performance evaluation; Central Asia; ABSOLUTE ERROR MAE; RIVER-BASIN; TEMPERATURE; PERFORMANCE; RAINFALL; CHINA; RESOLUTION; EXTREMES; BIASES; RMSE;
D O I
10.3390/w10111516
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Coupled Model Intercomparison Project Phase 5 (CMIP5) provides data, which is widely used to assess global and regional climate change. In this study, we evaluated the ability of 37 global climate models (GCMs) of CMIP5 to simulate historical precipitation in Central Asia (CA). The relative root mean square error (RRMSE), spatial correlation coefficient, and Kling-Gupta efficiency (KGE) were used as criteria for evaluation. The precipitation simulation results of GCMs were compared with the Climatic Research Unit (CRU) precipitation in 1986-2005. Most models show a variety of precipitation simulation capabilities both spatially and temporally, whereas the top six models were identified as having good performance in CA, including HadCM3, MIROC5, MPI-ESM-LR, MPI-ESM-P, CMCC-CM, and CMCC-CMS. As the GCMs have large uncertainties in the prediction of future precipitation, it is difficult to find the best model to predict future precipitation in CA. Multi-Model Ensemble (MME) results can give a good simulation of precipitation, and are superior to individual models.
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页数:14
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