云南省丽江市1960-2017年极端气温变化特征

Variation characteristics of extreme temperature in Lijiang, Yunnan Province during 1960-2017

云南丽江市是位于南方且具有温带气候特点的地区,研究该区近58年极端气温变化对查明极端气温变化特点、规律和趋势具有重要科学意义,对极端气温引起的气象灾害的预防及减少气象灾害造成的损失有实际意义。利用丽江市气象站1960—2017年的日最高、最低气温和平均气温等气象数据,采用线性趋势分析法、累积距平值分析法、主成分分析法、Mann-Kendall突变检验法、Morlet复数小波变换系数及小波方差法,对选用的8个极端气温指数进行了研究。结果表明:丽江市的极端最高气温、极端最低气温、夏季日数、暖昼日数、暖夜日数等5个指数呈现上升趋势,冷昼日数、冷夜日数、霜冻日数等3个指数呈现下降趋势。主成分分析结果表明:丽江市的夏季日数、暖昼日数和暖夜日数的增加对气温升高起到了主要作用。突变分析表明:丽江各指数的突变年主要出现在21世纪初和1983年前后。Morlet小波分析表明:丽江市极端气温指数的主周期普遍为18年,个别指数有12年、30年的周期。初步认为,全球气温升高是导致研究区极端气温变化的主要原因,预测丽江市未来2—3年的气温仍会呈现上升趋势,且极端高温事件的发生频率呈现上升趋势。

Background,aim,and scope Since the 20th century,the global temperature is undergoing a general and significant increase,and the extreme temperature events have brought serious threats and shocks to many parts of the Earth in terms of temperature and precipitation.Under the background of global high temperature,China is also affected by extreme temperature.Based on the previous studies on the extreme climate changes in Yunnan Province,a more detailed and in-depth analysis is carried out,which may give us a deeper understanding of the process and reasons of the extreme temperature changes.Lijiang,located in the south of Yunnan Province,is a city with temperate characteristics.Studying the extreme temperature changes by analyzing the meteorological data in the recent 58 years of this area is of great scientific significance,which not only can help to identify the features,rules,and trends of extreme temperature changes,but also can prevent meteorological disasters and reduce the losses caused by extreme temperatures.Materials and methods The paper analyzes the meteorological data including daily maximum temperature,daily minimum temperature and the mean temperature during the period from 1960 to 2017 in Lijiang.The study was performed with diverse methods consisting of Linear Trend Analysis,Cumulative Annual Temperature Anomaly Analysis,Principal Component Analysis,Mann-Kendall Method,Morlet Complex Wavelet Transform Coefficients and Wavelet Variance Method.Results The results show that the five extreme indices such as extreme maximum temperature,extreme minimum temperature,summer days,warm days and warm nights in Lijiang have increasing trend,while the three indexes such as cool days,cool nights and frost days present decreasing.Discussion It can be found from principal component analysis of extreme temperature index of Lijiang during 1960 to 2017 that load values in summer days,warm days and warm nights were high.On this basis,these three indexes are determined as the main factors leading to the rise of temperature in Lijiang.Through Mann-Kendall abnormal analysis in Matlab software,the symbolic abnormal years in time series can be obtained from the intersection points of the extreme temperature positive and reverse sequence lines.The abnormal years of warmth index appeared in the early 21st century.According to the analysis of droughts and high temperature disasters possibly caused by changes in extreme temperature index,it can be learned that the extreme temperature increase will seriously affect the tourists’direct tourism experience,and will have adverse impact on propagandizing local tourism mainly featuring moderate climate.Conclusions The Principal Component Analysis suggests that the rise of the summer days,warm days and nights in Lijiang plays the main part of its growth in temperature.And according to the Mutation analysis,the abnormal change in Lijiang mainly occurred in the early 21st century and around 1983.Morlet Complex Wavelet Transform Coefficients and Wavelet Variance Method presents the primary period of the extreme temperatures in Lijiang is generally 18 years apart from exceptions of 12 years and 30 years.It is initially believed that the global warming is the main cause of extreme temperature changes in Lijiang.Recommendations and perspectives The authors predict that the temperature in Lijiang in the near two or three years will appear to be upward,and the frequency of extreme high temperature events will go up.