| 1951—2020年广州地区极端气温指数年月尺度变化研究 |
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| 引用本文： | 江铭诺,李冠毅,何婉文,王沛东,李舒文.1951—2020年广州地区极端气温指数年月尺度变化研究[J].热带气象学报,2022,38(2):239-252. |
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| 作者姓名： | 江铭诺 李冠毅 何婉文 王沛东 李舒文 |
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| 作者单位： | 1.广东省气象探测数据中心，广东 广州 510641 |
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| 基金项目： | 广东省气象探测数据中心科研项目2021A07 |
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| 摘 要： | 根据广州国家基本气象站1951—2020年的逐日气温资料，采用线性趋势法、距平及累积距平法和Mann-Kendall检验法，对WMO推荐的16种极端气温指数中的13种以及2种结合本地实际的新的极端气温指数共计15种指数进行计算，从月尺度和年尺度分析广州地区各极端气温指数随时间变化的趋势和突变年份，并对以往研究中较少探究的基期的选择对相对极端气温指数的结果影响进行了对比分析。(1) 从年尺度看，广州地区近70 a的夏日日数SU25、酷热日数SU35、热夜日数TR20、非常热夜日数TR26、最高气温TXx、最低气温TNn、最低气温最大值TNx、相对暖夜日数TN90p、暖昼日数TX90p、显著偏暖持续指数WSDI均呈现明显的上升趋势，相对冷夜日数TN10p、冷昼日数TX10p和偏冷持续指数CSDI呈现下降趋势，气温日较差DTR和最高气温最小值TXn变化趋势不明显；(2) 新的极端气温指数SU35和TR26的上升速率明显大于SU25和TR20的上升速率，能更好地反映近70 a昼夜体感炎热日数呈现极显著的上升趋势，更加符合评估气候变化对当地生产生活的影响；(3) 从月尺度来看近70 a广州地区的暖系列极值气温指数TXx和TNx在夏季出现了明显的上升；相对极端气温指数TX90p在广州地区气候学意义的夏季(4—10月)的上升趋势除了5月以外均达到极显著水平；广州地区夏季相对暖(热)昼的上升是导致全年相对暖(热)昼上升的主要因素, 这与国内大部分地区冬季升温较为明显的结论有所不同；(4) 以三个不同基期(1961—1990年/1971—2000年/1981—2010年)的选择对相对极端气温指数的计算结果影响发现，基期的不同选择对相对极端气温指数的计算结果有一定影响，但不影响其变化趋势；(5) 突变分析显示广州地区近70 a的SU25、SU35、TMAXmean(平均最高气温)、TXx和TX90p的突变发生在1997年前后；TR20、TR26、TMINmean(平均最低气温)、TNn、TNx、TN10p、TX10p和TN90p的突变发生在1985年前后；结果符合全球气候变化的大趋势，可以为广州地区应对气候变化和预防极端天气灾害提供科学的理论依据和参考。
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| 关 键 词： | 广州 极端气温指数 年月尺度 变化趋势 |
| 收稿时间： | 2020-12-15 |
A STUDY ON THE ANNUAL AND MONTHLY VARIATIONS OF THE EXTREME TEMPERATURE INDEX IN GUANGZHOU FROM 1951 TO 2020 |
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| JIANG Mingnuo,LI Guanyi,HE Wanwen,WANG Peidong,LI Shuwen.A STUDY ON THE ANNUAL AND MONTHLY VARIATIONS OF THE EXTREME TEMPERATURE INDEX IN GUANGZHOU FROM 1951 TO 2020[J].Journal of Tropical Meteorology,2022,38(2):239-252. |
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| Authors: | JIANG Mingnuo LI Guanyi HE Wanwen WANG Peidong LI Shuwen |
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| Institution: | 1.Guangdong Meteorological Observation Data Center, Guangzhou 510641, China2.Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China3.Nanxiong Meteorological Bureau, Shaoguan 512000, China |
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| Abstract: | Based on the daily maximum and minimum temperature data from the Guangzhou National Basic Weather Station from 1951 to 2020, the study calculates 13 kinds of extreme temperature indices recommended by the World Meteorological Organization and two new integrated extreme temperature indices with local conditions considered. Then the study analyzes how they change monthly and annually by using linear trend method, anomaly and cumulative anomaly method and Mann-Kendall test. Moreover, the study examines the influence of the choice of base period which was rarely explored in previous studies. The results show that: (1) On an annual scale, SU25, SU35, TR20, TR26, TXx, TNx, TNx, TN90p, TX90p and WSDI in Guangzhou increased, while TN10p, TX10p and CSDI decreased, and DTR and TXn had no significant change. (2) The rising rate of the new extreme temperature indices SU35 and TR26 is significantly higher than that of SU25 and TR20, which can better reflect the significant increase in the number of days that are extremely hot both in the daytime and at night in recent 70 years. The annual largest rising rate of extreme temperature indices is that of TX90p which has reached 8.18 d/(10 a). (3) In the past 70 years, the monthly warm series extreme temperature indices TXx and TNx increased significantly in summer in Guangzhou and June and July witnessed the most substantial increase. TX90p reached an extremely significant level (P < 0.001) in local climatological summer (from April to October) except for May. The rise of warm (hot) days in summer (especially in June) is the main reason for the rise of warm (hot) days in the whole year in Guangzhou. (4) Based on the results of three different base periods (1961—1990/1971—2000/ 1981—2010), it is found that different base periods affect the statistical results of extreme temperature indices but do not affect the trends of extreme temperature indices. (5) Mann-Kendall test shows that the mutations of SU25, SU35, TMAXmean, TX90p and TXx occurred around 1997; while those of TR20, TR26, TNn, TN10p, TMINmean, TNx, TX10p and TN90p occurred around 1985. The results of this study are the same with the general trend of global climate change and thus can provide scientific reference for people in Guangzhou to respond to climate change and prevent extreme weather disasters. |
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| Keywords: | Guangzhou extreme temperature indices monthly and annual scales variation trend |
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