资源环境科技发展态势分析平台

Atmospheric blocking is a major producer of extreme weather events in midlatitudes that have profound socioeconomic impacts. However, few strides toward seasonal prediction of atmospheric blocking have been made. Here, we developed a new statistical model for prediction of the winter seasonal blocking frequency over Eurasia 1 month in advance using sea surface temperature, geopotential height at 70-hPa, and sea ice concentration as predictors, and the model captures more than 65% of the interannual variance. Furthermore, we applied the same predictors used for blocking prediction to predict the seasonal occurrence of winter extreme hot and cold days, and skillful prediction was achieved over Greenland and large portions of Eurasia. The predictive models provide insight into the seasonal predictability of atmospheric blocking and extreme temperature and also aide in valuable decisions across a variety of sectors.