1960-2015年中国冬半年极端降温过程事件的时空演变特征

Spatial and temporal evolution features of cooling extremes in China during winter half year from 1960 to 2015

利用1960—2015年中国2474个站点的逐日最低气温资料,采用REOF方法将中国分为7个区域,通过对每个区域内所有站点降温阈值进行平均,得到了7个降温阈值。当某区域内测站单日降温幅度超过区域平均阈值时,认为该测站发生一次极端降温事件。7个区域降温平均阈值各异,总体呈北大南小特征,最大降温-10.6℃,最小-7.6℃。根据上述定义,研究了中国冬半年极端降温过程事件的时空演变特征。结果表明:极端降温事件发生频数呈北多南少的空间分布。北部地区存在多个频发中心,在42°N和35°N附近存在两个高频发生带。南部地区频数呈一定的带状分布,在25°N附近发生该事件的频率亦高于南部其他地区。近56 a来,极端降温事件频数变化总体呈减少趋势,前期较明显,中后期趋于稳定。各年代频数的空间分布基本一致,但前期总体表现为北部增多。而在1990s则转变为南负北正的空间分布,后期中部及沿海地区发生了趋势符号的年代际改变。进一步分析表明,各区域极端降温频数突变的年份均不一致且突变前后的频数存在较大差异。这些结果可为深刻认识极端低温事件的变化规律和气候预测提供线索。

Based on the daily minimum temperature of 2474 stations in China from 1960 to 2015,seven climatic regions were divided by REOF method.Regional averages of the thresholds of cooling extent of temperature over seven regions,seven cooling thresholds were obtained.The average temperature thresholds of the seven regions are different and get smaller from north to south,with a maximum decrease of 10.6℃and a minimum of 7.6℃.The Cooling Extremes(CE)were defined and the temporal and spatial features of extreme cooling events in winter half year were studied.The results show that there is a significant spatial difference in occurrences of cooling extremes in the half year of winter,presenting a spatial pattern of occurrences with more occurrences in the north whereas less occurrences in the south.There are multiple centers with high frequency in the northern and two high-frequency zones around 42°N and 35°N.The occurrence frequency near 25°N is higher than in other parts of the south.Over the past 56 years,the CE frequency has a decreasing trend,which is more clearly seen in the earlier period.The spatial distribution of frequencies in each decade looks similar to each other.The abrupt changes in frequency of CE events are not uniform in spatial.In some regions,the time when the abrupt changes occur is earlier but in other regions later.These results can provide clues for deep understanding of the law of extreme low temperature events and climate prediction.