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Preface to Special Issue on CMIP6 Experiments: Model and Dataset Descriptions

doi: 10.1007/s00376-020-0008-8

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  • Eyring V., S. Bony, G. A. Meehl, A. S. Catherine, S. Bjorn, J. S. Ronald, and E. T. Karl, 2016: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9, 1937−1958,
    Zhou, T. J., and coauthors, 2020: Development of climate and earth system models in China: Past achievements and new CMIP6 results. J. Meteor. Res., 34(1), 1−19,
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    [2] Bian HE, Yimin LIU, Guoxiong WU, Qing BAO, Tianjun ZHOU, Xiaofei WU, Lei WANG, Jiandong LI, Xiaocong WANG, Jinxiao LI, Wenting HU, Xiaoqi ZHANG, Chen SHENG, Yiqiong TANG, 2020: CAS FGOALS-f3-L Model Datasets for CMIP6 GMMIP Tier-1 and Tier-3 Experiments, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 18-28.  doi: 10.1007/s00376-019-9085-y
    [3] Zhongfeng XU, Ying HAN, Meng-Zhuo ZHANG, Chi-Yung TAM, Zong-Liang YANG, Ahmed M. EL KENAWY, Congbin FU, 2024: Assessing the Performance of a Dynamical Downscaling Simulation Driven by a Bias-Corrected CMIP6 Dataset for Asian Climate, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 974-988.  doi: 10.1007/s00376-023-3101-y
    [4] Pengfei LIN, Zhipeng YU, Hailong LIU, Yongqiang YU, Yiwen LI, Jirong JIANG, Wei XUE, Kangjun CHEN, Qian YANG, Bowen ZHAO, Jilin WEI, Mengrong DING, Zhikuo SUN, Yaqi WANG, Yao MENG, Weipeng ZHENG, Jinfeng MA, 2020: LICOM Model Datasets for the CMIP6 Ocean Model Intercomparison Project, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 239-249.  doi: 10.1007/s00376-019-9208-5
    [5] Shang-Ping XIE, 2016: Preface to the Special Issue "Unified Perspective of Climate Variability and Change", ADVANCES IN ATMOSPHERIC SCIENCES, 33, 409-410.  doi: 10.1007/s00376-015-0003-7
    [6] Huijun WANG, 2017: Preface to the Special Issue on the "Forecast and Evaluation of Meteorological Disasters" (FEMD), ADVANCES IN ATMOSPHERIC SCIENCES, 34, 127-128.  doi: 10.1007/s00376-016-6007-0
    [7] Xiquan DONG, 2018: Preface to the Special Issue: Aerosols, Clouds, Radiation, Precipitation, and Their Interactions, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 133-134.
    [8] Stephen BELCHER, Peter STOTT, Lianchun SONG, Qingchen CHAO, Riyu LU, Tianjun ZHOU, 2018: Preface to Special Issue on Climate Science for Service Partnership China, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 897-898.  doi: 10.1007/s00376-018-8002-0
    [9] Jiang ZHU, 2017: Preface to the Special Issue on Commemorating the Centenary of Duzheng YE's Birth, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 1135-1136.  doi: 10.1007/s00376-017-7002-9
    [10] Peng ZHANG, Jun YANG, Jinsong WANG, Xinwen YU, 2021: Preface to the Special Issue on Fengyun Meteorological Satellites: Data, Application and Assessment, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1265-1266.  doi: 10.1007/s00376-021-1002-5
    [11] Liguang WU, Bin WANG, Johnny C. L. CHAN, Kyung-Ja HA, Il-Ju MOON, Jun MATSUMOTO, Zhemin TAN, Ke FAN, 2022: Preface to the Special Issue: Climate Change and Variability of Tropical Cyclone Activity, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 203-204.  doi: 10.1007/s00376-021-1020-3
    [12] Tianbao ZHAO, Aiguo DAI, Jianping HUANG, Lixia ZHANG, 2024: Preface to the Special Issue on Causes, Impacts, and Predictability of Droughts for the Past, Present, and Future, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 191-192.  doi: 10.1007/s00376-023-3017-6
    [13] Jiping LIU, David BROMWICH, Dake CHEN, Raul CORDERO, Thomas JUNG, Marilyn RAPHAEL, John TURNER, Qinghua YANG, 2020: Preface to the Special Issue on Antarctic Meteorology and Climate: Past, Present and Future, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 421-422.  doi: 10.1007/s00376-020-2001-7
    [14] Ye PU, Hongbo LIU, Ruojing YAN, Hao YANG, Kun XIA, Yiyuan LI, Li DONG, Lijuan LI, He WANG, Yan NIE, Mirong SONG, Jinbo XIE, Shuwen ZHAO, Kangjun CHEN, Bin WANG, Jianghao LI, Ling ZUO, 2020: CAS FGOALS-g3 Model Datasets for the CMIP6 Scenario Model Intercomparison Project (ScenarioMIP), ADVANCES IN ATMOSPHERIC SCIENCES, 37, 1081-1092.  doi: 10.1007/s00376-020-2032-0
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    [17] Pengfei LIN, Zhipeng YU, Hailong LIU, Yongqiang YU, Yiwen LI, Jirong JIANG, Wei XUE, Kangjun CHEN, Qian YANG, Bowen ZHAO, Jilin WEI, Mengrong DING, Zhikuo SUN, Yaqi WANG, Yao MENG, Weipeng ZHENG, Jinfeng MA, 2020: Erratum to: LICOM Model Datasets for the CMIP6 Ocean Model Intercomparison Project, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 662-662.  doi: 10.1007/s00376-020-2005-3
    [18] Binghao JIA, Longhuan WANG, Yan WANG, Ruichao LI, Xin LUO, Jinbo XIE, Zhenghui XIE, Si CHEN, Peihua QIN, Lijuan LI, Kangjun CHEN, 2021: CAS-LSM Datasets for the CMIP6 Land Surface Snow and Soil Moisture Model Intercomparison Project, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 862-874.  doi: 10.1007/s00376-021-0293-x
    [19] Yuyang GUO, Yongqiang YU, Pengfei LIN, Hailong LIU, Bian HE, Qing BAO, Shuwen ZHAO, Xiaowei WANG, 2020: Overview of the CMIP6 Historical Experiment Datasets with the Climate System Model CAS FGOALS-f3-L, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 1057-1066.  doi: 10.1007/s00376-020-2004-4
    [20] Shuai HU, Bo WU, Yiming WANG, Tianjun ZHOU, Yongqiang YU, Bian HE, Pengfei LIN, Qing BAO, Hailong LIU, Kangjun CHEN, Shuwen ZHAO, 2023: CAS FGOALS-f3-L Model Datasets for CMIP6 DCPP Experiment, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 1911-1922.  doi: 10.1007/s00376-023-2122-x

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Preface to Special Issue on CMIP6 Experiments: Model and Dataset Descriptions

  • Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China


  • The Coupled Model Intercomparison Project (CMIP) supports research in climate change and assessment, including the Intergovernmental Panel on Climate Change (IPCC) Assessment Report (AR), through providing enormous datasets mainly produced by Earth system models (ESMs) and climate system models (CSMs). The newest (sixth) phase of CMIP (CMIP6) has been launched, including the DECK (Diagnostic, Evaluation and Characterization of Klima) and 23 endorsed MIP experiments, to address new scientific questions in climate fields (Eyring et al., 2016). Now, the datasets simulated by the new versions of ESMs and CSMs have been/will be published on the Earth System Grid Federation (ESGF). Hence, descriptions of the CMIP6 models, experiment designs and datasets are important for the community; evaluations and comparisons of the models with other CMIP models are useful to understand the progress and simulation biases of models.

    This special issue, consisting of two parts, mainly focuses on introducing and evaluating the datasets simulated by the CMIP6 models developed in China [see Zhou et al. (2020) for a review], covering the experiment settings, descriptions and evaluations of the variables, and comparisons with other CMIP6/CMIP5 simulations. The experiment settings include the external forcings, such as greenhouses gases, aerosols and solar irradiance, integration periods, and initialization conditions for different members. The MIPs covered in this issue comprise the Paleoclimate MIP phase 4 (PMIP4), the Global Monsoons MIP (GMMIP), the Ocean MIP (OMIP), the Flux-Anomaly-Forced MIP (FAFMIP), and the Scenario MIP (ScenarioMIP), using the component and coupled models respectively. The datasets are principally described with the variable names, their physical meanings and frequencies etc. published on the ESGF. The evaluations generally involve validation using reanalysis/observation, as well as comparison with other simulations to verify whether the simulation is within a reasonable range, and showcase the strengths and weaknesses of the models.

    Compared with CMIP5, the CMIP6 simulations offer substantial improvements in certain aspects—for instance, climatological temperature and precipitation, climate extreme indices for both temperature and precipitation over China, and winter monsoon—albeit some obvious biases still remain. When compared to proxy records, the two versions of FGOALS capture the large-scale climate responses to the solar insolation changes during the interglacial epochs, but disagreements between the simulations and proxy records are apparent. In some idealized experiments, e.g., FAMIP and abrupt-4×CO2 in DECK, the simulation by a model is mostly compared with the simulations by other CMIP6 models and/or its other type of simulation, as there are no observed references.

    The papers in this special issue of Advances in Atmospheric Sciences provide valuable datasets from different CMIP6 models and MIP experiments for the next 5–10 years of climate research, as well as useful information about the experiment settings and models. Nonetheless, more in-depth analyses and attributions are still needed for the CMIP6 simulations to further understand the physical processes and improve the models.

    Acknowledgements. Special thanks to Dr. Lijuan LI and Dr. Qing BAO for helping design and coordinate submissions to this special issue.




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