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

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Abstract

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.

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Acknowledgements

This study is supported by National Key R&D Program of China (2017YFA0603804) and National Natural Science Foundation of China (41971072, 41771069 and 41911530187). Fudan University-Tibet University Joint Laboratory for Biodiversity and Global Change is acknowledged. We are very grateful to the reviewers for their constructive comments and thoughtful suggestions.

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Authors and Affiliations

  1. Department of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, Room 5002-1, Environmental Science Building, No.2005 Songhu Road, Yangpu, Shanghai, 200438, China

    Qinglong You & Ziyi Cai

  2. Innovation Center of Ocean and Atmosphere System, Zhuhai Fudan Innovation Research Institute, Zhuhai, 518057, China

    Qinglong You

  3. Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Nanjing University of Information Science and Technology (NUIST), Nanjing, 210044, China

    Fangying Wu & Zhihong Jiang

  4. Department of Geography, University of Portsmouth, Portsmouth, UK

    Nick Pepin

  5. Department of Mathematics and Statistics, San Diego State University, San Diego, CA, 92182, USA

    Samuel S. P. Shen

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  1. Qinglong You
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  2. Ziyi Cai
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You, Q., Cai, Z., Wu, F. et al. Temperature dataset of CMIP6 models over China: evaluation, trend and uncertainty. Clim Dyn 57, 17–35 (2021). https://doi.org/10.1007/s00382-021-05691-2

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