首页|最新版海冰模式CICE的优势:基于北极海冰时空特征的评估

最新版海冰模式CICE的优势:基于北极海冰时空特征的评估

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  • 国家科技期刊平台
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[研究目的]海冰模式CICE (Los Alamos sea ice model)作为当前国际上的主流海冰模式之一,已被耦合进了大部分地球系统模式,对该模式模拟能力的评估工作是发展地球系统模式的重要参考依据.[创新点]通过观测数据与不同版本CICE模式对北极海冰数值模拟结果进行对比分析,研究了最新版本CICE6.0模拟能力及优势.[重要结论]CICE6.0模拟结果的年际误差最小,且季节变化与观测值最为吻合.相较而言,CICE4.0严重高估了冬季海冰总面积及低估了夏季海冰总面积,而CICE5.0在冬季的误差明显大于其他版本.此外,我们也关注了三个模式对多年冰和季节冰的模拟效果,从其均方根误差空间分布看出:模拟误差主要出现在中央海区及其周边海域.CICE4.0和CICE5.0在这些区域模拟的多年冰偏少、季节冰偏多,均低估了多年冰的变化趋势,且高估了季节冰的变化趋势;CICE6.0很好地解决了这些问题,其模拟的多年冰和季节冰的趋势最接近观测值,特别在北冰洋中部.总的来说,CICE6.0模拟的北极海冰在各方面都优于其他版本.
Advantages of the latest Los Alamos Sea-Ice Model (CICE): evaluation of the simulated spatiotemporal variation of Arctic sea ice
The Los Alamos Sea-Ice Model (CICE) is one of the most popular sea-ice models.All versions of it have been the main sea-ice module coupled to climate system models.Therefore,evaluating their simulation capability is an important step in developing climate system models.Compared with observations and previous versions (CICE4.0 and CICE5.0),the advantages of CICE6.0 (the latest version) are analyzed in this paper.It is found that CICE6.0 has the minimum interannual errors,and the seasonal cycle it simulates is the most consistent with observations.CICE4.0 overestimates winter sea-ice and underestimates summer sea-ice severely.Meanwhile,the errors of CICE5.0 in winter are larger than for the other versions.The main attention is paid to the perennial ice and the seasonal ice.The spatial distribution of root-mean-square errors indicates that the simulated errors are distributed in the Atlantic sector and the outer Arctic.Both CICE4.0 and CICE5.0 underestimate the concentration of the perennial ice and overestimate that of the seasonal ice in these areas.Meanwhile,CICE6.0 solves this problem commendably.Moreover,the decadal trends it simulates are comparatively the best,especially in the central Arctic sea.The other versions underestimate the decadal trend of the perennial ice and overestimate that of the seasonal ice.In addition,an index used to objectively describe the difference in the spatial distribution between the simulation and observation shows that CICE6.0 produces the best simulated spatial distribution.

Los Alamos Sea-Ice Model (CICE)spatiotemporal variationperennial iceseasonal icemodel evaluation

WANG Huazhao、ZHANG Lujun、CHU Min、HU Siyu

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School of Atmospheric Sciences, Nanjing University, Nanjing, China

University Corporation for Polar Research, Beijing Normal University,Beijing, China

Jiangsu Collaborative Innovation Center for Climate Change, Nanjing University, Nanjing, China

National Climate Center,China Meteorological Administration, Beijing, China

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海冰模式 海冰变化 多年冰 季节冰 模式评估

This research is supported jointly by the National Key R&D Program of China [This research is supported jointly by the National Key R&D Program of China [China Special Fund for Meteorological Research in the Public Interest [National Natural Science Foundation of China [

grant numbers 2016YFA06021002018YFC1407104]grant number GYHY201506011]grant number 41975134]

2020

大气和海洋科学快报(英文版)
中国科学院大气物理研究所

大气和海洋科学快报(英文版)

CSCD
影响因子：0.465
ISSN：1674-2834
年,卷(期)：2020.13(2)
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