Abstract
The first fully coupled atmosphere-ocean-sea ice model developed in China was released in the mid-1990s. Since then, significant advances in climate system model developments have been achieved by improving the representations of major physical processes, increasing resolutions, and including an ice-shelf component. There have also been many modeling studies in China on the polar climate system, including weather and sea-ice numerical forecasts to meet the national needs of polar scientific expeditions, assessments of the state-of-the-art coupled model performance, and process-oriented studies. Future model developments and modeling activities will need to address several big scientific questions originating from the polar climate system: i) How will polar ice mass balance evolve and affect global sea level? ii) How can we properly simulate open-ocean deep convection and quantify its role in driving the lower branch of the global overturning circulation? iii) How are Arctic and Antarctic connected and what caused the contrasting sea ice trends in the two polar regions over the last decades? To address these questions, polar climate system modelers will need to analyze extended observational datasets on a global scale and work together with other polar researchers to develop a more comprehensive and sustainable observation system in the polar regions.
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Acknowledgements
We would like to thank Dr Chengyan Liu, Dr Yang Wu, Mr Rui Bian, Ms Mingyi Gu, Ms Qing Qin and Ms Jiangchao Qian for their assistance during the preparation of this manuscript. This work was supported by the Global Change Research Program of China (Grant No. 2015CB953900), the Major State Basic Research Development Program of China (Grant No. 2016YFA0601804), the National Natural Science Foundation of China (Grant No. 41876220), and the Fundamental Research Funds for the Central Universities (Grant Nos. 2017B04814 & 2017B20714).
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Wang, Z., Chen, D. Polar climate system modeling in China: Recent progress and future challenges. Sci. China Earth Sci. 62, 1076–1091 (2019). https://doi.org/10.1007/s11430-018-9355-2
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DOI: https://doi.org/10.1007/s11430-018-9355-2