李斐斐,徐彩艳. 2023. 基于弱耦合资料同化的冬季北大西洋涛动年际变率预测. 气象学报,81(1):124-136. DOI: 10.11676/qxxb2023.20220062
引用本文: 李斐斐,徐彩艳. 2023. 基于弱耦合资料同化的冬季北大西洋涛动年际变率预测. 气象学报,81(1):124-136. DOI: 10.11676/qxxb2023.20220062
Li Feifei, Xu Caiyan. 2023. Improved interannual predictability of winter North Atlantic Oscillation with a weakly coupled data assimilation scheme. Acta Meteorologica Sinica, 81(1):124-136. DOI: 10.11676/qxxb2023.20220062
Citation: Li Feifei, Xu Caiyan. 2023. Improved interannual predictability of winter North Atlantic Oscillation with a weakly coupled data assimilation scheme. Acta Meteorologica Sinica, 81(1):124-136. DOI: 10.11676/qxxb2023.20220062

基于弱耦合资料同化的冬季北大西洋涛动年际变率预测

Improved interannual predictability of winter North Atlantic Oscillation with a weakly coupled data assimilation scheme

  • 摘要: 北大西洋涛动作为冬季北大西洋地区大气环流的主模态之一,其年际变率对全球许多地区气候变率具有重要影响,但目前其预测技巧并不高。采用降维投影四维变分同化方法,在耦合模式中建立了基于全球大气资料的弱耦合资料同化系统,直接同化月平均再分析资料,并进行了年代际后报试验。结果表明,通过耦合资料同化的手段,可以显著提升耦合模式对冬季北大西洋涛动年际变率及其相关的欧洲北部、美国东部、欧亚大陆北部的冬季近地面温度年际变率的后报效果,相关系数均超过0.05显著水平t检验。该后报效果的改进主要与在耦合同化过程中通过耦合模式中自由发展的海-气相互作用将大气的观测信息储存在耦合模式的海洋分量中,改进了冬季北大西洋地区海表温度“三极”型分布的时空变率及其时间序列的后报效果有关。该研究强调了耦合模式初始状态的准确度对提升冬季北大西洋涛动年际变率的后报技巧具有重要作用。

     

    Abstract: The North Atlantic Oscillation (NAO) is one of the major modes of atmospheric circulation over the North Atlantic in winter, and its interannual variabilities play an important role in climate variabilities over many regions of the world. However, the skills for its prediction are not good enough at present. In this paper, a weakly coupled data assimilation system based on global observational atmospheric data is established using the Dimensional-Reduced Projection Four-Dimensional Variation (DRP-4DVar) assimilation method, which can directly assimilate monthly mean reanalysis data. The results of decadal hindcast experiments indicate that this system can significantly improve the hindcast effects of interannual variabilities in wintertime NAO and interannual variabilities of related winter surface temperature over northern Europe, the eastern United States and northern Eurasia, and the correlation coefficients are all above the 0.05 significance level t-test at least. These improvements are mainly attributed to the freely developed air-sea coupling in the coupled model that can store atmospheric observations in its ocean component, and thus improve the spatial and temporal variabilities in the "tripole" pattern of the Sea Surface Temperature (SST) distribution over the North Atlantic and related "tripole" SST temporal variabilities. This study emphasizes the importance of the accuracy of initial states of the coupled model in improving the hindcast abilities of the coupled model on the simulation of wintertime NAO interannual variabilities.

     

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