极地研究

极地研究 ›› 2024, Vol. 36 ›› Issue (2): 183-198.DOI: 10.13679/j.jdyj.20220439

• 研究论文 • 上一篇    下一篇

基于我国CMIP6模式的北极海冰厚度比较及评价

王梓琦1  王晓春1  金梅兵1  喻小勇2  赵立清1   

  1. 1南京信息工程大学, 海洋科学学院, 江苏 南京 210044;
    2无锡学院, 大气与遥感学院, 江苏 无锡 214000
  • 出版日期:2024-06-30 发布日期:2024-07-18
  • 作者简介:王梓琦,女, 1996年生。硕士研究生, 主要从事海冰模式研究。E-mail: 915616456@qq.com
  • 基金资助:
    国家重点研发计划(2018YFA0605904)和国家自然科学基金(42376200)资助

Comparison and evaluation of Arctic sea ice thickness based on Chinese CMIP6 model

WANG Ziqi1, WANG Xiaochun1, JIN Meibing1, YU Xiaoyong2, ZHAO Liqing1   

  1. 1 School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China;
    2 Institute of Atmosphere and Remote Sensing, Wuxi University, Wuxi 214000, China
  • Online:2024-06-30 Published:2024-07-18

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摘要： 本文选取了第六次国际耦合模式比较计划(CMIP6)中的 8个中国地球气候系统模式, 将这些模式的北极海冰厚度与华盛顿大学的PIOMAS海冰厚度同化产品进行对比, 评估了所选模式1980—2014年北极海冰厚度多年平均空间分布和长期趋势, 并通过泰勒评分法对各模式的模拟能力进行了量化。结果表明, 无论3月还是9月, 所有模式均与PIOMAS存在差异, 偏差位置主要集中在格陵兰岛北部、巴伦支海、白令海峡附近。模式均低估北极3月和9月海冰中心区域厚度, 此外还普遍高估3月海冰边缘区厚度。其中空间分布与PIOMAS最为相近的模式为FIO-ESM-2-0, 其次为FGOALS-f3-L模式。海冰厚度的长期趋势表明, 海冰厚度整体呈下降趋势, 并且9月的下降程度明显大于3月, 与PIOMAS长期趋势空间分布最为相似的模式为NESM3。在此基础上, 本文进一步对比了82°N以北3种大气再分析资料、1种卫星观测产品与8个CMIP6模式的辐射分量, 再分析资料及模式间辐射分量有很大的差别, 其中有两个模式的辐射存在明显的异常, FGOALS-f3-L模式3月上行短波辐射和CIESM模式9月上行短波辐射严重偏小, 这可能是由于模式模拟存在误差。

Abstract: In this research, output from eight Chinese Earth climate system models from the International Coupled Model Intercomparison Project Phase 6 (CMIP6) were selected. The spatial distribution and long-term trend of the multi-year mean Arctic sea ice thickness between 1980 to 2014 from the models were evaluated by comparing them with the sea ice thickness data assimilation product from the Pan-Arctic Ice-Ocean and Assimilating System (PIOMAS). The capability of each model was quantified using the Taylor Score. The results show that there are differences between output from all models and PIOMAS data in both March and September, and the deviations are mainly located in the north of Greenland, the Barents Sea, and around the Bering Strait. Models underestimate March and September ice thickness of the Arctic central region in, and generally overestimated the thickness of the Arctic sea ice margin region in March. In terms of spatial distribution of ice thickness, the difference between PIOMAS data and FIO-ESM-2-0 output is the smallest among the eight models and the difference between PIOMAS and FGOALS-f3-L is the second smallest. The long-term trend of sea ice thickness is negative, with sea ice thickness decreasing faster, in September than in March. In terms of the spatial distribution of the long-term sea ice thickness trend, the difference between PIOMAS data and model output is the smallest for NESM3 among the eight models. The radiation components from the eight CMIP6 models were compared with three reanalysis products and one satellite data set for the region north of 82°N to examine the factors underlying the model bias in sea ice thickness. There are large differences among the radiation components of the reanalysis products and the model output, with clear anomalies in the radiation of two models. The upward shortwave radiation of FGOALS-f3-L in March and that of CIESM in September are remarkably low, which may be the reason for the bias in the sea ice thickness simulation of these two models.