摘要
In Northeast China during the winter, severe snowstorms can occur resulting in both societal and economic damage. In this paper, we explore an effective technique for the seasonal prediction of heavy snow activity, where previous synoptic studies have failed. We employ a year-to-year increment approach and ultimately identify four predictors, x1 to x4 . x1 is the area-averaged soil moisture over the northern part of Northeast China in the preceding month of September and represents the role of land processes. x2 represents the role of sea-air interactions in winter, x3 the preceding summer Mascarene High related to the winter SST over the tropical western Pacific, and x4 is the low-level the thermal condition over Northeast China from the previous year that oppose current year. Cross-validation tests for both 1963-2011 and independent hindcasts between 1983-2010 are performed to validate the prediction ability of our technique. The cross validation test results for 1963-2011 reveal a high correlation coefficient of 0.86 (0.77) between the predicted and observed year-to-year increment of the number of snow days. The model also predicts well the independent hindcast for the years 1983-2011. Therefore, this study provides an effective climate prediction model for Northeast China's heavy snow activities and thus requires preliminary application in operational settings.
In Northeast China during the winter, severe snowstorms can occur resulting in both societal and economic damage. In this paper, we explore an effective technique for the seasonal prediction of heavy snow activity, where previous synoptic studies have failed. We employ a year-to-year increment approach and ultimately identify four predictors,X1 to X4. X1 is the area-averaged soil moisture over the northern part of Northeast China in the preceding month of September and represents the role of land processes, X2 represents the role of sea-air interactions in winter, X3 the preceding summer Mascarene High related to the winter SST over the tropical western Pacific, and X4 is the low-level the thermal condition over Northeast China from the previous year that oppose current year. Cross-validation tests for both 1963-2011 and independent hindcasts between 1983-2010 are performed to validate the prediction ability of our technique. The cross validation test results for 1963-2011 reveal a high correlation coefficient of 0.86 （0.77） between the predicted and observed year-to-year increment of the number of snow days. The model also predicts well the independent hindcast for the years 1983-2011. Therefore, this study provides an effective climate prediction model for Northeast China＇ s heavy snow activities and thus requires preliminary application in operational settings.
基金
supported by the National Basic Research Program of China (2009CB421406)
the Knowledge Innovation Key Program of the Chinese Academy of Sciences (KZCX2-YW-QN202)
Strategic Technological Program of Chinese Academy of Sciences (XDA05090426)
