Abstract
Assessing the regional impact of climate change on agriculture, hydrology, and forests is vital for sustainable management. Trustworthy projections of climate change are needed to support these assessments. In this paper, 18 global climate models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to simulate regional climate change in Zhejiang Province, Southeast China. Simple graphical approaches and three indices are used to evaluate the performance of six key climatic variables during simulations from 1971 to 2000. These variables include maximum and minimum air temperature, precipitation, wind speed, solar radiation, and relative humidity. These variables are of great importance to researchers and decision makers in climate change impact studies and developing adaptation strategies. This study found that most GCMs failed to reproduce the observed spatial patterns, due to insufficient resolution. However, the seasonal variations of the six variables are simulated well by most GCMs. Maximum and minimum air temperatures are simulated well on monthly, seasonal, and yearly scales. Solar radiation is reasonably simulated on monthly, seasonal, and yearly scales. Compared to air temperature and solar radiation, it was found that precipitation, wind speed, and relative humidity can only be simulated well at seasonal and yearly scales. Wind speed was the variable with the poorest simulation results across all GCMs.









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Acknowledgments
This research was financially supported by Zhejiang Provincial Natural Science Foundation of China (LR14E090001), National Natural Science Foundation of China (51379183), and International Science and Technology Cooperation Program of China (2010DFA24320). We are grateful to the China Meteorological Administration and Zhejiang Meteorological Bureau for providing meteorological data in Zhejiang Province. Many thanks are also given to Dr. Qian Budong from Agriculture and Agri-Food Canada for providing valuable comments on this manuscript. Finally, the comments from the editor and anonymous reviewers are greatly appreciated.
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Xuan, W., Ma, C., Kang, L. et al. Evaluating historical simulations of CMIP5 GCMs for key climatic variables in Zhejiang Province, China. Theor Appl Climatol 128, 207–222 (2017). https://doi.org/10.1007/s00704-015-1704-7
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DOI: https://doi.org/10.1007/s00704-015-1704-7