锡林郭勒地区积雪时空变化规律研究

发布时间：2018-04-23 06:18

本文选题：积雪 + 变异分析　；参考：《内蒙古农业大学》2017年硕士论文

【摘要】：锡林郭勒地区属于我国北部边疆重要的生态屏障,同时也是我国三大积雪高值区之一。研究区地貌广阔,积雪分布差异较大。本文利用锡林郭勒地区15个气象观测站1971～2015年的逐日积雪资料,重点分析了研究区降雪量、积雪深度及积雪日数三大积雪指标的时空变化规律、时空变异特征及周期性特征,揭示了积雪日数与气象因子的相关性,并对积雪日数的未来变化趋势进行了预测分析。主要研究结果如下:1.锡林郭勒地区各站点降雪量、积雪深度和积雪日数随时间波动幅度较为剧烈,且各站点波动规律基本一致,整体无显著的增减趋势。从年内变化上看,降雪量呈现的是"双峰型"的波动特征,其中11月份的峰值最大,1月份最少,积雪深度和积雪日数则呈现的是"单峰型"的波动特征,最大值分别在2月份和1月份,最小值都出现在刚入冬的10月份。2.锡林郭勒地区降雪量、积雪深度及积雪日数空间分布差异性显著,基本呈现的是东多西少、南多北少的分布格局,高值区主要分布在乌拉盖、西乌旗、正镶白旗及太卜寺旗周围,少雪区主要出现在西部区。降雪量、积雪深度的极差将近4倍,积雪日数相差2倍以上。依据区划原则,将研究区划分为4种类型:一致偏高区、中值区、一少两多区、一致偏少区。在此基础上利用EOF分别对三个积雪指标做了进一步的空间异常分型。3.利用小波分析对锡林郭勒地区近45a的积雪周期进行分析,可知降雪量存在7a、11a和18a三个震荡周期,积雪日数存在7a,11a和22a三个周期变化,积雪深度存在5a和11a两个震荡周期。其中降雪量和积雪日数的主周期均为7a,积雪深度主周期为5a。通过突变检验分析可知,降雪量和积雪深度没有突变产生,而积雪日数在1996a附近发生了一次由多到少的突变。4.锡林郭勒积雪日数受多种气象因子共同作用,通过相关性分析得出降雪量、积雪深度、气温及湿度分别与积雪日数有较高的相关性。BP神经网络模型预测,未来十年间积雪日数呈逐渐减少的趋势。
[Abstract]:Xilingol area is an important ecological barrier in the northern frontier of China, and is also one of the three high snow cover areas in China. The landform of the study area is wide and the snow cover distribution is quite different. Based on the daily snow cover data of 15 meteorological observatories in Xilinguole region from 1971 to 2015, the temporal and spatial variation, temporal and spatial variation characteristics and periodic characteristics of snow fall, snow depth and snow days in the study area are analyzed in this paper. The correlation between snow days and meteorological factors is revealed, and the trend of snow days in the future is predicted and analyzed. The main results are as follows: 1. The snowfall amount, snow depth and snow days fluctuate sharply with time in Xilingole area, and the fluctuation law of each station is basically the same, and there is no significant increase or decrease trend on the whole. From the point of view of the change of the year, the snowfall is characterized by "double peak" fluctuation, in which the peak value in November is the highest and the minimum in January, and the snow depth and snow days show the fluctuation characteristics of "single peak". The maximum values were in February and January, respectively, and the minimum values appeared in October, just into winter. The spatial distribution of snowfall, snow depth and snow days in Xilinguole area is significant. It basically presents a pattern of less snow in the east and less in the west and less in the south and north. The high value areas are mainly distributed in the Wulagai and Xiwu Banner. Around Zhengxian White Banner and Taibusi Banner, Shaoxue area mainly appeared in the western region. Snowfall, snow depth of nearly 4 times, more than 2 times the number of snow days. According to the principle of regionalization, the study area is divided into four types: uniform high area, median region, one few, two more regions, and uniform less areas. On this basis, the further spatial anomaly classification. 3. 3 was made by using EOF for the three snow cover indexes. Wavelet analysis is used to analyze the snow cover periods in Xilinguole area in the last 45 years. The results show that there are three periods of snow fall: 7a, 11a, 18a, 7a, 11a, 22a, and the depth of snow, 5a and 11a, respectively. The main periods of snow fall and snow days are both 7a and 5a respectively. According to the analysis of sudden change test, there is no sudden change in snowfall and snow depth, and a mutation from more to less occurred in the snow days around 1996. The number of snow days in Xilinguole is affected by various meteorological factors. Through the correlation analysis, it is concluded that the snowfall amount, snow depth, temperature and humidity have a high correlation with snow days. BP neural network model is used to predict the snowfall days. The number of snow days will gradually decrease in the next ten years.
【学位授予单位】：内蒙古农业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P426.635

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