气象学报(英文版)2024,Vol.38Issue(1) :53-68.DOI:10.1007/s13351-024-3051-z

Why Are Arctic Sea Ice Concentration in September and Its Interannual Variability Well Predicted over the Barents-East Siberian Seas by CFSv2?

Yifan XIE Ke FAN Hongqing YANG
气象学报(英文版)2024,Vol.38Issue(1) :53-68.DOI:10.1007/s13351-024-3051-z

Why Are Arctic Sea Ice Concentration in September and Its Interannual Variability Well Predicted over the Barents-East Siberian Seas by CFSv2?

Yifan XIE 1Ke FAN 1Hongqing YANG1
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作者信息

  • 1. School of Atmospheric Sciences,Sun Yat-sen University,and Southem Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 519082
  • 折叠

Abstract

To further understand the prediction skill for the interannual variability of the sea ice concentration(SIC)in specific regions of the Arctic,this paper evaluates the NCEP Climate Forecast System version 2(CFSv2),in predicting the autumn SIC and its interannual variability over the Barents-East Siberian Seas(BES).It is found that CFSv2 presents much better prediction skill for the September SIC over BES than the Arctic as a whole at 1-6-month leads,and high prediction skill for the interannual variability of the SIC over BES is displayed at 1-2-month leads after removing the linear trend.CFSv2 can reasonably reproduce the relationship between the SIC over BES in September and such factors as the surface air temperature(SAT),200-hPa geopotential height,sea surface temperature(SST),and North Atlantic Oscillation.In addition,it is found that the prescribed SIC initial condition in August as an input to CFSv2 is also essential.Therefore,the above atmospheric and oceanic factors,as well as an accurate initial condition of SIC,all contribute to a high prediction skill for SIC over BES in September.Based on a statistical prediction method,the contributions from individual predictability sources are further identified.The high prediction skill of CFSv2 for the interannual variability of SIC over BES is largely attributable to its accurate predictions of the SAT and SST,as well as a better initial condition of SIC.

Key words

sea ice concentration/the Barents-East Siberian Seas/Climate Forecast System version 2(CFSv2)/pre-diction skill/predictability source/atmospheric and oceanic factors/initial condition

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基金项目

国家重点研发计划(2022YFE0106800)

国家自然科学基金(42230603)

Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021001)

出版年

2024
气象学报(英文版)
中国气象学会

气象学报(英文版)

CSTPCD
影响因子:0.57
ISSN:0894-0525
参考文献量55
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