Assessment of Precipitation Simulations in Central Asia by CMIP5 Climate Models

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...

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Bibliographic Details
Published inWater (Basel) Vol. 10; no. 11; p. 1516
Main Authors Ta, Zhijie, Yu, Yang, Sun, Lingxiao, Chen, Xi, Mu, Guijin, Yu, Ruide
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 25.10.2018
Subjects
Central Asia
Climate change
Climate models
CMIP5
Correlation coefficient
Correlation coefficients
Datasets
Experiments
Global climate models
International relations
Mean square errors
Performance evaluation
Precipitation
Simulation
Central Asia
China
Africa
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Summary: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.
ISSN:2073-4441
2073-4441
DOI:10.3390/w10111516