中国春季沙尘暴年代际变化和季节预测

Interdecadal Variation of Spring Dust Storms in China and Its Seasonal Statistical Forecast

利用1954～2007年中国258个台站观测的月沙尘暴日数资料,北半球地表温度和美国NCAR/NCEP大气再分析资料,研究了中国春季沙尘暴日数年代际变化特征及其影响因子。研究发现:中国春季沙尘暴日数与贝加尔湖地表变暖存在显著的负相关,相关系数达到-0.8,该地区的地表温度变暖导致蒙古气旋活动和我国沙尘暴频率降低。利用该地区冬季对流层850 hPa温度与春季地表温度指数之间显著正相关关系,建立了冬季850 hPa温度指数预测中国春季沙尘暴频率的线性预报方程。通过22年回报检验发现,统计预报结果与多数台站观测的沙尘暴发生频率存在显著的正相关,最大相关系数达到+0.4。其中,近22年的预报场与观测之间空间相关系数平均达到+0.4以上,均方根误差在1～2之间,表明该统计预报模型具有一定的业务应用价值。

The interdecadal variation of spring dust storm frequency（SDSF） in China and its possible affecting factors are examined on the basis of land-surface air temperature（SAT） and NCEP/NCAR reanalyzed datasets from 1954 to 2007.The results suggest that SDSF is negatively correlated with the SAT significantly around Lake Baikal,where the maximum correlation coefficient is-0.8.The warming around Lake Baikal can reduce the frequency of Mongolian cyclones and resulted in the decrease of SDSF in China over the past decades.It is found that the winter temperature at 850 hPa is positively correlated with the spring SAT significantly around Lake Baikal;therefore,a linear regression model between averaged winter air temperature index over the region of 80°E to 140°E,40°N to 70°N and SDSF is constructed during a training period of 1954 to 1983.The verification for the hindcast period from 1984 to 2005 suggests that the forecasted DSF is positively correlated with the observation with a maximum correlation coefficient of ＋0.4;the average Anomaly Correlation Coefficient（ACC） is ＋0.4 with the root mean square error（RMS） being 1 to 2.Such a result implies that this statistical model has a potential capability in the operational seasonal forecasting of SDSF.