1961-2016年吉林省积雪增量与积雪日数时空变化特征

摘要

Using the daily snow depth observations at 45 meteorological stations in Jilin province from 1961 to 2016,the spatial and temporal characteristics of snow cover increment and the number of days were analyzed based on the empirical orthogonal function(EOF),ensemble empirical mode decomposition(EEMD)and linear fitting methods.The results show that there are significant differences in the spatial distributions of the snow cover incre-ment and the number of days.The higher values of them mostly present around Changbai Mountain located in the eastern part of Jilin province.The lower ones present in the mid-west plain of Jilin province.The amount of snow cover tightly connects with the geographical location of observations.In the higher altitudes and lower latitudes re-gions,more of snow cover is observed;while less is observed in the lower altitudes and higher latitudes.From the 1960s to the end of 1980s,the amount of snow cover increases with time,but it decreases in the 1990s.After 2000, it increases rapidly.Three typical spatial patterns of snow cover increment and days are found.The first pattern is a consistently more or less than the normal one over the whole region.The second pattern is a reverse phase one be-tween the eastern and western parts,and the third pattern is a seesaw one between the central regions and other re-gions.Both of the traditional linear fitting and the EEMD non-linear trend methods illustrate an increasing tendency in the amounts snow cover increment and the number of the days,but the former amplifies the increasing rates.%利用1961-2016年吉林省45个气象站逐日积雪观测资料,采用经验正交函数(Empirical Orthogonal Function, EOF)分解、集合经验模态(Ensemble Empirical Mode Decomposition,EEMD)分解及线性拟合等方法,研究吉林省积雪增量和积雪日数的时空变化特征.结果表明:1961-2016年吉林省积雪增量和积雪日数的空间差异显著,二者高值区集中分布在吉林省东部长白山一带,低值区多集中分布在吉林省中西部平原区.积雪量与气象观测站的地理位置有关,高海拔和低纬度地区积雪偏多,低海拔和高纬度地区积雪偏少.积雪增量和积雪日数阶段变化特征明显,60-80年代末期以增加趋势为主;90年代积雪有所减少,2000年以后积雪迅速增多.吉林省积雪增量和积雪日数包括3个主要分布型,第1个类型为全区一致偏多(偏少)型,第2个类型为东部地区偏多(少)、西部地区偏少(多)的东西反相型,第3个类型为中部地区偏多(少)、东部和西部地区偏少(多)型.传统回归线性趋势与EEMD非线性趋势法均可以反映出近56 a吉林省积雪增量和积雪日数呈增加的趋势,但线性趋势法放大了积雪增量和积雪日数的增加速率.