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近40年内蒙古候平均气温变化趋势
引用本文:裴浩,Alex Cannon,Paul Whitfiel,郝璐.近40年内蒙古候平均气温变化趋势[J].应用气象学报,2009,20(4):443-450.
作者姓名:裴浩  Alex Cannon  Paul Whitfiel  郝璐
作者单位:1.中国农业大学资源与环境学院, 北京 100094)
基金项目:中国气象局气候变化专项项目(CCSF200617)与2007年中加气象局高级管理培训项目共同资助。
摘    要:基于1964—2003年内蒙古有关台站的逐日气温数据, 对前20年 (1964—1983年) 和后20年 (1984—2003年) 的候平均气温中值进行了对比, 并利用k-means方法进行了候平均气温变化趋势的聚类分析, 旨在阐明内蒙古气温变化的时空特点和规律。研究结果表明:内蒙古全境年平均气温普遍上升, 没有下降的现象。不同地区、不同季节气温变化格局不同, 北部变暖比南部更为明显, 冬季和夏末秋初变暖出现得更频繁。绝大部分地区大多数候平均气温都有所上升, 而且候平均气温变化存在纬向地带性。大多数台站四季里都有一些显著升温的候, 显著升温在冬季发生得更为频繁。同时, 有少数几个候出现气温下降的现象, 但未达到显著下降的程度。内蒙古绝大部分地区候最高、最低气温都有所升高, 但二者的差值在缩小。候最低气温出现时间有所提前, 候最高气温出现时间有提前也有推迟, 但总体上不同地区候最高、最低气温出现时间更加同步。因此, 候最高、最低气温的时空均一性有所增强。候最高气温出现时间与候最低气温出现时间的间隔有扩大迹象。总之, 全球气候变暖降低了气温的季节和地区差异。

关 键 词:气温变化    候平均气温    聚类分析    内蒙古
收稿时间:2008-10-29
修稿时间:3/6/2009 12:00:00 AM

Pentad Average Temperature Changes of Inner Mongolia During Recent 40 Years
Pei Hao,Alex Cannon,Paul Whitfield and Hao Lu.Pentad Average Temperature Changes of Inner Mongolia During Recent 40 Years[J].Quarterly Journal of Applied Meteorology,2009,20(4):443-450.
Authors:Pei Hao  Alex Cannon  Paul Whitfield and Hao Lu
Institution:1.College of Resources and Environmental Sciences, China Agricultural University, Beijing 100094)2.Inner Mongolian Meteorological Bureau, Huhhot 010051)3.Meteorological Services of Canada, Environment Canada, Vancouver, BC V6C 3S5)4.School of Geography and Remote Sensing, Beijing Normal University, Beijing 100875)
Abstract:In order to understand characteristics of the pentad average temperature changes from 1964 to 2003 in Inner Mongolia, daily temperature records of 47 meteorological stations are analyzed. According to the results of the jump point tests, this 40 years are divided into two 20-year periods, the first 20-year period is from 1964 to 1983, and the second is from 1984 to 2003. From these daily temperature data, the pentad (5 days) average temperature is calculated, and then the pentad average temperature of the second 20-year period is compared with that of the first 20-year period at 5-day interval (pentad). Then the cluster analysis is done. First, the stations are classified into 5 clusters using 4 optimal determining indices. Based on kmeans method and the pentad average temperature differences between the two periods, clustering analysis is conducted, so the spatial pattern of the pentad average temperature differences clusters are obtained. By analyzing the polar plots of the pentad average temperatures, it is clear that the patterns of the pentad average tem perature changes are different in different regions and seasons. The warming in north is more obvious than in south, and it happens more frequent in winter, late summer to early fall than in other seasons. The pentad average temperature in most of the stations rises most of the time, and the spatial distribution of the pentad temperature changes clusters shows that there is a zonation along the latitude. Significant warming most frequently appears in winter. Meanwhile, there are a few pentads that show cooling, but not quite significant. Both the maximum and minimum pentad temperature rise, but the differences betw een them decrease. The timings of the minim um temperature pentads are earlier in the second 20-year period, and the timings of the maximum temperature pentads are earlier or later, while the timings of the minim um and maximum temperature pentads are more synchronic, so the temporal and spatial evenness of the minimum and maximum temperature pentads enhances. In addition, most of the stations show that the durations between the maximum and minimum temperature pentads are longer in the second 20-year period than that in the first 20-year period. From these results, it can be concluded that the global warming may reduce the seasonal and regional temperature differences. The medians of the annual average temperatures of the first 20-year period and the second 20-year period are compared, indicating that the annual average temperatures rise all over Inner Mongolia, and no temperature decrease is found.
Keywords:temperature change    pentad average temperature    clustering analysis    Inner Mongolia
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