(Peer-Reviewed) Projection of climate extremes in China, an incremental exercise from CMIP5 to CMIP6
Huanhuan Zhu 朱欢欢 ¹ ², Zhihong Jiang 江志红 ² ³, Laurent Li 李肇新 ⁴
¹ Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China 南京信息工程大学 气候与环境变化国际合作联合实验室
² Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China 南京信息工程大学 气象灾害预报预警与评估协同创新中心
³ Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China 南京信息工程大学 气象灾害教育部重点实验室
⁴ Laboratoire de Météorologie Dynamique, CNRS, Sorbonne Université, Ecole Normale Supérieure, Ecole Polytechnique, Paris 75005, France
Science Bulletin, 2021-07-21
Abstract
This paper presents projections of climate extremes over China under global warming of 1.5, 2, and 3 °C above pre-industrial (1861-1900), based on the latest Coupled Model Intercomparison Project phase 6 (CMIP6) simulations. Results are compared with what produced by the precedent phase of the project, CMIP5. Model evaluation for the reference period (1985-2005) indicates that CMIP6 models outperform their predecessors in CMIP5, especially in simulating precipitation extremes.
Areal averages for changes of most indices are found larger in CMIP6 than in CMIP5. The emblematic annual mean temperature, when averaged over the whole of China in CMIP6, increases by 1.49, 2.21, and 3.53 °C (relative to 1985-2005) for 1.5, 2, and 3 °C above-preindustrial global warming levels, while the counterpart in CMIP5 is 1.20, 1.93 and 3.39 °C respectively. Similarly, total precipitation increases by 5.3%, 8.6%, and 16.3% in CMIP6 and by 4.4%, 7.0% and 12.8% in CMIP5, respectively.
The spatial distribution of changes for extreme indices is generally consistent in both CMIP5 and CMIP6, but with significantly higher increases in CMIP6 over northeast and northwest China for the hottest day temperature, and south China for the coldest night temperature.
In the south bank of the Yangtze River, and most regions around 40°N, CMIP6 shows higher increases for both total precipitation and heavy precipitation. The projected difference between CMIP6 and CMIP5 is mainly attributable to the physical upgrading of climate models and largely independent from their emission scenarios.
Emerging optical techniques for sorting and detection of chiral particles
Yuzhi Shi, Chengfeng Li, Xiaolei Lin, Wenwen Xue, Chengxing Lai, Tao He, Qinghua Song, Zhanshan Wang, Yulan Wang, Din Ping Tsai, Xinbin Cheng, Haidong Zou
Opto-Electronic Advances
2026-06-08
Phonon-assisted absorption photoconductive switch
Zhao Wang, Lixin Zhang, Lu Cheng, Danwen Zhang, Yu Lu, Naiji Zhang, Xin Zhang, Duanyang Chen, Zhan Sui, Hongji Qi, Wei Zheng
Opto-Electronic Science
2026-05-25
Photonic spiking reinforcement learning for intelligent routing
Shuiying Xiang, Yonghang Chen, Ling Zheng, Zhicong Tu, Xintao Zeng, Mengting Yu, Shuai Wang, Yahui Zhang, Xingxing Guo, Weitao Pan, Yue Hao
Opto-Electronic Science
2026-05-25
Massively parallel and programmable photonic differential equation solver
Jiahao Wang, Wen Chen, Zhou Zhou, Dongyu Hu, Zile Li, Peng Chen, Yan-qing Lu, Shuang Zhang, Cheng-Wei Qiu, Shaohua Yu, Guoxing Zheng
Opto-Electronic Advances
2026-05-15
Femtosecond laser rapid customization of high-performance anti-reflection windows
Yulong Ding, Xiang Jiang, Cong Wang, Xianshi Jia, Linpeng Liu, Weina Han, Zheng Gao, Shiyu Wang, Nai Lin, Dejin Yan, Ji'an Duan
Opto-Electronic Science
2026-04-23
Ppt-level volatile organic compounds detection via microsecond-pulse-enhanced mid-infrared photoacoustic
Senyu Wang, Liang Zhao, Hongyu Luo, Xiangyu Zhao, Jianfeng Li, Wei Wang, Hao Lei, Mingrui Jiang, Jinlong Wan, Binxing Zhao, Bincheng Li, Yong Liu
Opto-Electronic Science
2026-04-23