Using a regional atmospheric model for Arctic climate simulation, two groups of numerical experiments were carried out to study the influence of changes in the underlying surface （land surface, sea surface, and sea ice （LS/SS/SI）） from mild ice years to severe ice years on Arctic climate. In each experiment in the same group, the initial values and lateral boundary conditions were identical. The underlying surface conditions were updated every six hours. The model was integrated for 10 a and monthly mean results were saved for analysis. Variations in annual mean surface air temperature were closely correlated with changes in LS/SS/SI, with a maximum change of more than 15 K. The impact of changes in LS/SS/SI on low-level air temperature was also evident, with significant changes seen over the ocean. However, the maximum change was less than 2 K. For air temperature above 700 hPa, the impact of LS/SS/SI changes was not significant. The distribution of annual mean sea level pressure differences was coincident with the distribution of annual mean sea ice concentration. The difference centers were located in the Barents Sea, the Kara Sea, and the East Siberian Sea, with the maximum value exceeding 3 hPa. For geopotential height, some results passed and some failed a t-test. For results passing the t-test, the area of significance did not decrease with height. There was a significant difference at high levels, with a value of 27 gpm in the difference center at 200 hPa.
发展了一个可分辨大气临近空间且采用谱元数值计算技术的大气数值模式SEMANS(Spectral Element Model with Atmospheric Near Space resolved),并对模式模拟能力进行检验.数值模式采用立方体球面投影坐标,每个投影面分解为81个局地元,在元内利用8次Gauss-Lobatto-Legendre插值多项式对变量进行谱离散;模式大气在铅直方向分为66层,大气顶气压取为4.5×10-6h Pa.进行了10年积分试验,利用ECMWF(European Center for Medium-Range Weather Forecasts)ERA-Interim再分析数据集和COSPAR(Committee on Space Research)国际参考大气1986对SEMANS模拟结果进行初步检验.结果表明,模式模拟出30 hPa等压面上北半球纬向2波特征及南半球纬向1波特征;模式能模拟出100 hPa和0.001 hPa等压面附近的低温区及1 hPa等压面附近和0.0001 hPa等压面高度之上的高温区;模式还模拟出0.001 hPa等压面高度以下1月及7月纬向平均纬向风随高度分布的主要特征.
对1979—2009年月平均的CFSR(The Climate Forecast System Reanalysis)海冰密集度(SIC)和海平面气压(SLP)资料进行多变量经验正交函数分解(MV-EOF),得出耦合主模态,并通过对温度、位势高度和风场的回归分析,进一步探寻海冰与大气环流的关系,第一模态SLP的特征为北极涛动(AO),SIC呈离散的正负中心分布但大体为东西反位相,AO正位相时,喀拉海、拉普捷夫海、东西伯利亚海和鄂霍次克海海冰减少,巴芬湾、波弗特海、楚科奇海和白令海海冰增加。耦合第二模态的SLP呈偶极子分布,负、正异常中心在巴伦支海和波弗特海,SIC在巴伦支海、弗拉姆海峡、格陵兰海、拉布拉多海和白令海,鄂霍次克海地区有正异常,在喀拉海、拉普捷夫海、东西伯利亚海、楚科齐海和波弗特海为负异常。耦合第三模态SLP在冰岛地区存在负异常中心,在拉普捷夫海地区有正异常中心,SIC在巴伦支海北部、弗拉姆海峡、格陵兰海为负异常,其余地区全为正异常。对SLP和SIC分别进行EOF分解,并与耦合模态进行比较,SLP的EOF主模态的时空分布与耦合模态中SLP的时空分布十分相似,SIC的EOF模态的时空分布则与耦合模态中SIC的时空分布有较大差别,说明耦合模态对SIC的分布影响较大,即大气环流对海冰分布的影响为主要的过程,海冰对大尺度的大气环流的模态的影响不明显。
