Variation characteristics of extreme temperature in Lijiang, Yunnan Province during 19602017
： 2018 - 05 - 10
： 2018 - 08 - 19
： 2018 - 08 - 27
541 3 0

Abstract & Keywords
Abstract: 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 night days 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.
Keywords:  extreme temperature; trend change; periodic law; abnormal change; drought; Lijiang

1   研究区概况

2   资料来源及研究方法
2.1   资料来源

2.2   极端气温指数的定义和分类

 指标分类 Classification 指标名称 Index name 缩写 定义 单位 Abbreviation Definition Unit 极值指数 Extreme Index 极端最高气温 TXx 日最高气温的每年最高值 ℃ Highest Tmax Monthly highest TX 极端最低气温 TNn 日最低气温的每年最低值 ℃ Lowest Tmin Monthly lowest TN 绝对指数 Absolute index 霜冻日数 FD 每年的日最低气温≤0℃的天数 d Frost days Annual count of days when TN < 0 °C 夏季日数 SU 每年的日最高气温≥25℃的天数 d Summer days Annual count when TX (daily maximum)>25ºC 相对指数 Relative index 冷夜日数 TN10 日最低气温小于1960—2017年阀值（10%）的日数 d Cold nights Count of days when TN<10th percentile of 1960—2017 冷昼日数 TX10 日最高气温小于1960—2017年阀值（10%）的天数 d Cold days Count of days when TX<10th percentile of 1960—2017 暖夜日数 TN90 日最低气温大于1960—2017年阀值（90%）的天数 d Warm nights Count of days when TN>90th percentile of 1960—2017 暖昼日数 TX90 日最高气温大于1960—2017年阀值（90%）的天数 d Warm days Count of days when TX>90th percentile of 1960—2017

2.3   研究方法

$$\mathrm{L}{\mathrm{P}}_{i}=\sum _{i}^{N}（\mathrm{R}\mathrm{i}-\overline{R}）$$ （1）

3   结果与分析
3.1   平均气温的年际、季节变化和年平均最高、最低气温变化

 指标 Index 年平均气温 Annual average temperature 年平均最高气温 Annual average maximum temperature 年平均最低气温 Average annual minimum temperature 春季气温 Spring temperature 夏季气温 Summer temperature 秋季气温 Autumn temperature 冬季气温 Winter temperature 倾向率/[℃·（10a）-1] Tendency rate 0.02 0.02 0.02 0.02 0.02 0.01 0.01 平均气温/℃ Average temperature 12.93 19.47 7.98 13.70 18.02 12.98 6.81 春季为3—5月；夏季为6—8月；秋季为9—11月；冬季为12月至第二年2月。
3.2   极端气温指数线性变化趋势

Fig.1 Trend of extreme maximum and extreme minimum temperatures from 1960 to 2017 in Lijiang

Fig.2 Trend of extreme temperature absolute index from 1960 to 2017 in Lijiang

Fig.3 Variation trend of the relative index of extreme temperature from 1960 to 2017 in Lijiang
3.3   极端指数的累积距平分析

Fig.4 Cumulative anomaly map of the extreme temperature index from 1960 to 2017 in Lijiang
3.4   极端气温指数的变化周期

Fig.5 Wavelet transform coefficients and variogram of extreme temperature extremes and absolute temperature index from 1960 to 2017 in Lijiang
a）、（b）极端最高气温；（c）、（d）极端最低气温；（e）、（f）夏季日数；（g）、（h）霜冻日数

Fig.6 Wavelet Transform Coefficients and Variance Diagrams of the Relative Air Temperature Index from 1960 to 2017in Lijiang
（a）、（b）暖昼日数；（c）、（d）暖夜日数；（e）（f）冷昼日数；（g）（h）冷夜日数
4   讨论
4.1   对气温升高起主要作用的气温指数

 指数 丽江主成分载荷 Main component load of Lijiang 1 2 3 4 5 6 极端最高气温TXx 0.57 0.58 0.24 -0.37 0.25 -0.29 极端最低气温TNn 0.46 -0.66 0.33 0.20 0.44 0.14 霜冻日数FD -0.70 0.64 0.03 0.20 0.19 0.01 夏季日数SU 0.79 0.55 -0.06 0.01 -0.02 0.24 暖昼日数TN10 0.79 0.55 -0.06 0.01 -0.02 0.24 冷昼日数TX10 -0.63 0.21 0.69 -0.11 -0.20 0.17 暖夜日数TN90 0.77 0.14 0.27 0.45 -0.23 -0.25 冷夜日数TX90 -0.68 0.64 -0.09 0.25 0.19 -0.03 方差贡献率 Variance contribution rate 46.68% 28.18% 9.09% 6.22% 5.30% 3.97%

 指数 Indices 极端最高气温 TXx 极端最低气温 TNn 霜冻日数 FD 夏季日数 SU 暖昼 TX90 冷昼 TN10 暖夜 TN90 极端最低气温TNn -0.044 霜冻日数FD -0.054 -0.603** 夏季日数SU 0.676** 0.005 -0.206 暖昼TX90 0.676** 0.005 -0.206 1.000** 冷昼TX10 -0.129 -0.287* 0.534** -0.384** -0.384** 暖夜TN90 0.430** 0.298* -0.398** 0.616** 0.616** -0.322* 冷夜TN10 -0.075 -0.628** 0.947** -0.191 -0.191 0.436** -0.377** ** 表示在 0.01 水平（双侧）上显著相关，* 表示在 0.05 水平（双侧）上显著相关。
4.2   极端气温指数的突变分析

Fig.7 Mann-Kendall test of extreme temperature extreme value index from 1960 to 2017 in Lijiang

Fig.8 Mann-Kendall test of absolute temperature absolute index from 1960 to 2017 in Lijiang

Fig.9 Mann-Kendall test of relative index of extreme temperature from 1960 to 2017 in Lijiang

4.3   极端气温变化可能造成的气象灾害与预测

5   结论

（1）近58年来，丽江的极端最高气温、极端最低气温、夏季日数、暖昼日数、暖夜日数都呈现上升趋势，冷昼日数、冷夜日数、霜冻日数呈现下降趋势，且暖指数上升趋势要较为明显，倾向率普遍大于冷指数倾向率绝对值，说明气温近58年云南省丽江地区发生极端高温事件的概率在增大。
（2）主成分分析可知，夏季日数和暖昼日数的增加对丽江地区气温升高起到了主要作用，暖夜日数增加对气温升高也起到了一定作用。
（3）突变分析表明，丽江地区暖指数的突变年主要出现在21世纪初，而冷指数的突变年主要出现在1983年与2003年前后。可以确定，云南丽江地区的极端气温变化主要表现为冷指数值突变减小与暖指数值突变升高。
（4）Morlet小波分析可知，丽江地区的各指数的明显主振荡周期普遍为18年，具有较好的对称性，极端最高气温与夏季日数也存在较显著12年、30年的周期。
（5）极端气温事件的增多使该区旱灾增多，高温天气增多，预测丽江市未来3—4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。此外，极端气温事件的增多会影响到游客的直观旅游感受，对该地区旅游业影响不利，应当加强对极端气温事件的预报和预防。

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JI Zhengxi

ZHAO Jingbo

extreme temperature; trend change; periodic law; abnormal change; drought; Lijiang

Journal of Earth Environment