Evaluating historical simulations of CMIP5 GCMs for key climatic variables in Zhejiang Province, China

• Published in: Theoretical and applied climatology Vol. 128; no. 1-2; pp. 207 - 222
• Main Authors: Xuan, Weidong, Ma, Chong, Kang, Lili, Gu, Haiting, Pan, Suli, Xu, Yue-Ping
• Format: Journal Article
• Language: English
• Published: Vienna Springer Vienna 01.04.2017; Springer; Springer Nature B.V
• Subjects: Air temperature; Analysis; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; Climate change; Climate models; Climate science; Climatology; Earth and Environmental Science; Earth Sciences; Environmental impact; General circulation models; Global climate; Global temperature changes; Humidity; Hydrology; Original Paper; Precipitation (Meteorology); Radiation (Physics); Relative humidity; Seasonal variations; Simulation; Solar radiation; Sustainability management; Waste Water Technology; Water Management; Water Pollution Control; Wind speed; China; Zhejiang China; ISEW, China, People's Rep., Zhejiang Prov; Solar Radiation; Climatic Variable; Climate Change Impact; Root Mean Square Error; Wind Speed
• ISSN: 0177-798X; 1434-4483
• DOI: 10.1007/s00704-015-1704-7

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.