Temperature dataset of CMIP6 models over China: evaluation, trend and uncertainty

被引:0
|
作者
Qinglong You
Ziyi Cai
Fangying Wu
Zhihong Jiang
Nick Pepin
Samuel S. P. Shen
机构
[1] Fudan University,Department of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences
[2] Zhuhai Fudan Innovation Research Institute,Innovation Center of Ocean and Atmosphere System
[3] Nanjing University of Information Science and Technology (NUIST),Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)
[4] University of Portsmouth,Department of Geography
[5] San Diego State University,Department of Mathematics and Statistics
来源
Climate Dynamics | 2021年 / 57卷
关键词
Future climate change; Near term; CMIP6; China;
D O I
暂无
中图分类号
学科分类号
摘要
The information on the projected climate changes over China is of great importance for preparing the nation’s societal adaptiveness to the future natural ecosystem. This study reports the surface mean temperature changes during 2014–2100 over China and its four sub-regions (Northern China, Northwestern China, Southern China, and the Tibetan Plateau) by analyzing 20 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under three Shared Socio-economic Pathway (SSP) scenarios: SSP126, SSP245 and SSP585. The multi-model ensemble mean (MMEM) of 20 CMIP6 models has cold biases over China during 1979–2014, with improved performance compared with the CMIP5 models. In contrast, the CMIP6 models simulate well in the spatial climatology with lower warming rates over China. Relative to 1986–2005, the regionally averaged surface mean temperatures from the MMEM over China under SSP126, SSP245, SSP585 scenarios are projected to increase by 1.31 °C, 1.32 °C, 1.45 °C in the near-term (2021–2040), 1.75 °C, 2.06 °C, 2.66 °C in the mid-term (2041–2060), and 1.08 °C, 2.97 °C, 5.62 °C in the long-term (2081–2100), respectively. The CMIP6 models simulate accelerated warming occurs over the Northwestern China and the Tibetan Plateau, suggesting that the arid and semi-arid regions are particularly sensitive to future climate warming. We quantify uncertainty for future projections of temperature changes over China, and the main sources of uncertainty are model and scenario uncertainty particularly for the regions with the largest cold bias. This suggests that the observational constraints on these regions will lead to significant improvements for climatic projections over China.
引用
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页码:17 / 35
页数:18
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