Multi-Model Ensemble Projection of Precipitation Changes over China under Global Warming of 1.5 and 2℃ with Consideration of Model Performance and Independence

作     者：Tong LI Zhihong JIANG Lilong ZHAO Laurent LI Tong LI;Zhihong JIANG;Lilong ZHAO;Laurent LI

作者机构：Joint International Research Laboratory of Climate and Environmental Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing 210044China Key Laboratory of Meteorological DisasterMinistry of Education(KLME)/CIC-FEMDNanjing University of Information Science&TechnologyNanjing 210044China Laboratoire de Météorologie DynamiqueL’Institut Pierre-Simon Laplace(IPSL)Centre National de la Recherche Scientifique(CNRS)Sorbonne UniversitéEcole Normale SupérieureEcole PolytechniqueParis 75005France 

出 版 物：《Journal of Meteorological Research》 (气象学报（英文版）)

年 卷 期：2021年第35卷第1期

页      面：184-197页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0706[理学-大气科学] 

基　　金：Supported by the National Key Research and Development Program of China (2017YFA0603804  2016YFA0600402  and 2018YFC1507704) 

主　　题：model performance and independence multi-model ensemble mean and extreme precipitation future projection 1.5 and 2℃global warming 

摘      要：A weighting scheme jointly considering model performance and independence(PI-based weighting scheme) is employed to deal with multi-model ensemble prediction of precipitation over China from 17 global climate models. Four precipitation metrics on mean and extremes are used to evaluate the model performance and independence. The PIbased scheme is also compared with a rank-based weighting scheme and the simple arithmetic mean(AM) scheme. It is shown that the PI-based scheme achieves notable improvements in western China, with biases decreasing for all parameters. However, improvements are small and almost insignificant in eastern China. After calibration and validation, the scheme is used for future precipitation projection under the 1.5 and 2℃ global warming targets(above preindustrial level). There is a general tendency to wetness for most regions in China, especially in terms of extreme precipitation. The PI scheme shows larger inhomogeneity in spatial distribution. For the total precipitation PRCPTOT(95 th percentile extreme precipitation R95 P), the land fraction for a change larger than 10%(20%) is 22.8%(53.4%)in PI, while 13.3%(36.8%) in AM, under 2℃ global warming. Most noticeable increase exists in central and east parts of western China.