Based on the reanalysis data fromNCEP/NCAR and other observational data, interannualvariability of Mascarene high (MH) and Australian high (AH) from 1970 to 1999 is examined. It is shown that interannual variability o...Based on the reanalysis data fromNCEP/NCAR and other observational data, interannualvariability of Mascarene high (MH) and Australian high (AH) from 1970 to 1999 is examined. It is shown that interannual variability of MH is dominated by the Antarctic oscillation (AAO), when the circumpolar low in the high southern lati-tudes deepens, the intensity of MH will be intensified. On the other hand, AH is correlated by AAO as well as El Nio and South Oscillation (ENSO), the intensity of AH will be inten-sified when El Nio occurs. Both correlation analysis andcase study demonstrate that summer rainfall over East Asia is closely related to MH and AH. When MH intensifies from boreal spring to summer (i.e. from austral autumn to winter)there is more rainfall over regions from the Yangtze Rivervalley to Japan, in contrast, less rainfall is found over south-ern China and western Pacific to the east of Taiwan, andmost of regions in mid-latitudes of East Asia. Compared with MH, the effect of AH on summer rainfall in East Asia is lim-ited to localized regions, there is more rainfall over southern China with the intensification of AH. The results in this study show that AAO is a strong signal on interannual time-scale, which plays an important role in summer rainfall over East Asia. This discovery is of real importance to revealing the physical mechanism of interannual variability of EastAsian summer monsoon and prediction of summer precipi-tation in China.展开更多
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, wh...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.展开更多
基金the National Key Basic Development Program (Grant No. G1998040900Part I) and the National Natural Science Foundation of China (Grant Nos. 40125014 and 40075020)
文摘Based on the reanalysis data fromNCEP/NCAR and other observational data, interannualvariability of Mascarene high (MH) and Australian high (AH) from 1970 to 1999 is examined. It is shown that interannual variability of MH is dominated by the Antarctic oscillation (AAO), when the circumpolar low in the high southern lati-tudes deepens, the intensity of MH will be intensified. On the other hand, AH is correlated by AAO as well as El Nio and South Oscillation (ENSO), the intensity of AH will be inten-sified when El Nio occurs. Both correlation analysis andcase study demonstrate that summer rainfall over East Asia is closely related to MH and AH. When MH intensifies from boreal spring to summer (i.e. from austral autumn to winter)there is more rainfall over regions from the Yangtze Rivervalley to Japan, in contrast, less rainfall is found over south-ern China and western Pacific to the east of Taiwan, andmost of regions in mid-latitudes of East Asia. Compared with MH, the effect of AH on summer rainfall in East Asia is lim-ited to localized regions, there is more rainfall over southern China with the intensification of AH. The results in this study show that AAO is a strong signal on interannual time-scale, which plays an important role in summer rainfall over East Asia. This discovery is of real importance to revealing the physical mechanism of interannual variability of EastAsian summer monsoon and prediction of summer precipi-tation in China.
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)
文摘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.
