Improved interannual predictability of winter North Atlantic Oscillation with a weakly coupled data assimilation scheme
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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，相关系数均至少通过了95%信度的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 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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图 1 基于全球大气资料的弱耦合资料同化系统
Figure 1. Weakly coupled data assimilation system of global atmospheric data
图 2 北大西洋地区 （20°—80°N，90°W—40°E） 1961—2005年冬季 （12月—次年2月） 海平面气压经验正交函数分解的第一模态（EOF1）（a、c、e、g. 空间型态，b、d、f、h. 时间系数）（a、b. NCEP／NCAR Reanalysis 1再分析资料，c、d. 对照试验，e、f. 同化试验，g、h. 后报试验；左下角的数字表示各试验的原始序列与NCEP／NCAR Reanalysis 1再分析资料的相关系数，右上角的数字表示EOF1的方差贡献，时间系数中黑线为11 a滑动平均的结果，*和**分别表示该相关系数通过了95%和99%信度的t检验）
Figure 2. Spatial patterns （a，c，e，g） and corresponding time coefficients （b，d，f，h） of EOF1 of winter （December to February） sea level pressure over the North Atlantic （20°—80°N，90°W—40°E） from 1961 to 2005. （a） and （b） represent NCEP/NCAR Reanalysis 1； （c） and （d） represent CTL； （e） and （f） represent ASSIM； （g） and （h） represent HCST （The correlation coefficients of the spatial pattern and time coefficients between these experiments and the reanalysis data are shown at the bottom left corner of each panel. The explained variance of each EOF1 mode is shown at the top right corner in a，c，e and g. The 11-year running averages of the time coefficients are represented by black lines. The correlation coefficients at the confidence levels above 0.05 and 0.01 t-test are marked by subscripts "*" and "**"，respectively）
图 3 1961—2005年标准化的冬季 （12月—次年2月） 亚速尔高压 （a—d） 和冰岛低压 （e—h） 指数随时间的变化（a、e. NCEP/NCAR再分析资料，b、f. 对照试验，c、g. 同化试验，d、h. 后报试验；图中的黑线为11 a滑动平均结果，左下角的数字表示各试验结果的原始序列与观测的相关系数，*和**分别表示相关系数通过了95%和99%信度的t检验（单位：hPa/σ））
Figure 3. Normalized time series of winter （December to February） Azores High （a—d） and Icelandic Low （e—h） indexes from 1961 to 2005 （a， c. NCEP/NCAR Reanalysis 1，b， f. CTL，c， g. ASSIM，d， h. HCST；The 11-year running averages of the time coefficients are represented by black lines. The correlation coefficients of the time series between these experiments and the reanalysis data are shown at the bottom left corner of individual panels. The correlation coefficients at the confidence levels above 0.05 and 0.01 t-test are marked by the subscripts "*" and "**"”，respectively （unit：hPa/σ））
图 4 1961—2005年标准化的冬季 （12月—次年2月） NAO指数与北半球陆地部分去趋势的冬季 （12月—次年2月） 2 m气温异常 （单位：K） 的回归场 （a. NCEP/NCAR 再分析资料，b. 对照试验，c. 同化试验，d. 后报试验；图中打点区域表示该区域的回归系数通过了95%的信度t检验）
Figure 4. Regression fields of detrended winter （December to February） 2 m temperature anomalies （unit：K） over the northern hemisphere land with the normalized winter （December to February） NAO index （a. NCEP/NCAR Reanalysis 1，b. CTL，c. ASSIM，d. HCST；the dotted areas indicate the regression coefficients over these areas are at/above the significance level of 0.05 t-test）
图 5 1961—2005年标准化的欧洲北部 （50°—70°N，5°—50°E） 冬季 （12月—次年2月） 去趋势的2 m气温异常的时间序列 （a. NCEP/NCAR再分析资料，b. 对照试验，c. 同化试验，d. 后报试验；图中的黑线为11 a滑动平均的结果，左下角的数字表示各试验结果的原始序列与观测的相关系数，*和**分别表示相关系数通过了95%和99%信度的t检验; 单位：K/σ）
Figure 5. Normalized time series of detrended winter （December to February） 2 m temperature anomalies （unit：K） over northern Europe （50°—70°N，5°—50°E） （a. NCEP/NCAR Reanalysis 1，b. CTL，c.ASSIM，d. HCST; the 11-year running averages of the time coefficients are represented by black lines; the correlation coefficients of the time series between these experiments and the reanalysis data are shown at the bottom left corner of each panel; the correlation coefficients at the significance levels above 0.05 and 0.01 t-test are marked by the subscripts "*" and "**"，respectively；unit：K/σ）
图 6 同图5，但为美国东部 （30°—40°N，75°—105°W）
Figure 6. Same as Fig. 5 but for the eastern USA （30°—40°N，75°—105°W）
图 7 1961—2005年冬季 （12月—次年2月） 北大西洋地区SST异常EOF分解第一模态的空间型态 （a—d） 及其时间序列 （e—h）（a、e. HadISST资料，b、f. 对照试验，c、g. 同化试验，d、h. 后报试验；a—d中右上角的数字表示方差贡献，e—h中的黑线为11 a滑动平均的结果，图中左下角的数字表示各试验结果的原始序列与观测的相关系数，*和**分别表示相关系数通过了95%和99%信度的t检验）
Figure 7. Spatial patterns （a—d） and the corresponding time coefficients （e—h） of the first EOF mode （EOF1） of winter （December to February） SST anomalies in the North Atlantic from 1961 to 2005 （a，e. HadISST analysis；b，f. CTL；c. g. ASSIM；d，h. HCST. The explained variance of each EOF1 mode is shown at the top right corner in each panel of a—d. The 11-year running averages of the time coefficients are represented by black lines in panels of e—h，and the correlation coefficients of the time coefficients between these experiments and the reanalysis data are shown at the bottom left corner of each panel. The correlation coefficients at the significance levels above 0.05 and 0.01 t-test are marked by the subscripts "*" and "**"，respectively）
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