洞庭湖流域高温热浪风险变化特征

doi:10.11870/cjlyzyyhj201510015

长江流域资源与环境 >> 2015, Vol. 24 >> Issue (10): 1729-1735.doi: 10.11870/cjlyzyyhj201510015

洞庭湖流域高温热浪风险变化特征

张晓艳¹, 刘梅先^2,3

1. 湖南第一师范学院教育科学系, 湖南长沙 410205;
2. 中国科学院亚热带农业生态过程重点实验室, 湖南长沙 410125;
3. 中国科学院环江喀斯特生态系统观测研究站, 广西环江 547100

收稿日期:2014-12-26 修回日期:2015-02-12 出版日期:2015-10-20
通讯作者: 刘梅先,E-mail:daodang2008@sina.com E-mail:daodang2008@sina.com
作者简介:张晓艳(1986~),讲师,博士,主要从事全球变化与生态系统响应研究.E-mail:hnfnuxyzhang@sina.com
基金资助:
中国科学院"西部之光"项目"西南喀斯特地区生态系统对极端天气气候的响应研究"(2060299)

TRENDS AND RISKS OF EXTREME HEAT EVENTS IN THE DONGTING LAKE CATCHMENT

ZHANG Xiao-yan¹, LIU Mei-xian^2,3

1. School of Education Science, Hunan First Normal University, Changsha 410205 China;
2. Key Laboratory for Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China;
3. Huanjiang Observation and Research Station for Karst Ecosystem, Chinese Academy of Sciences, Huanjiang 547100, China

Received:2014-12-26 Revised:2015-02-12 Online:2015-10-20

摘要/Abstract

摘要： 洞庭湖流域是我国高温热浪事件多发地区之一,严重威胁人体健康及农业生产,研究高温热浪特征和风险,对当地防暑减灾具有重要指导意义。基于气象站点气温数据(1960~2013年),综合利用MK检验、概率模型和Copula概率模型,以年最长热浪长度(HWL)、热浪平均高温(HWT)、高温天数(HDL)和高温天内平均高温(HDT)为指数,系统分析了洞庭湖流域高温、热浪的时空规律及风险变化特征。结果表明,流域平均4项高温指数表现出先下降后上升的趋势。总体上,流域东部和东南部高温、热浪强度较大,西部和西南部强度较小, 另外,流域高温、热浪的风险和强度变化有一定的空间差异,但总体上升。此外,基于Copula的分析结果表明,洞庭湖流域东大部地区发生高强度热浪和长期高温的风险上升,而西南部以及南部部分地区有所下降。

关键词: 高温天气, 热浪, 洞庭湖, 风险, copula

Abstract: Global warming has resulted in devastating hazards for human society, such as floods, droughts and heat waves. The Dongting Lake Basin is a region characterized by frequent heat waves and high temperatures in summer. Severe heat waves had brought enormous influences on human health and agriculture in this area. Take the 2013 heat wave as an example, it caused water shortage of more than 3 million people and 1.2 million animals, and resulted in loss of about $ 0.18 billion. In recent years, many researchers have focused on the warming characteristics. However, most of this studies focused on the trends of several single indices, while few studies have studied the probability, especially the joint probability of heat waves. On the other hand, duration and temperature are the two inherent characteristics of a heat events, hence, analysis of the joint probability of the two indices could improve our knowledge of severe heat events and for helpful hazards prevention in this region.Therefore, based on the ground surface observed daily temperature dataset (1960-2013), this study investigated the spatial-temporal characteristics and the risks of extreme heat events (EHE) in the Dongting Lake Catchment, by using MK test, probability distribution and copulas. Four indices, i.e. length of heatwaves (HWL), mean max temperature in heatwaves (HWT), hot days (HDL) and mean max temperature in hot days (HDT) were employed to reflect the extreme heat events. The results showed that, the four indices decreased first and then increased obviously after 1987. The amplitudes of EHE were relatively high in eastern and southeastern parts of the catchment, and were relatively lower in western and southwestern parts. Furthermore, though there existed heterogeneous patterns, the amplitude and risk of EHE after 1987 in this area overall increased compared to that in 1960-1987. In particular, the regional mean of 5-year return levels for HWL, HWT, HDL and HDT (HWL₅, HWT₅, HDL₅ and HDT₅) increased by 0.5 day, 0.2^oC, 2.0 day, and 0.2^oC, respectively. Moreover, the copula results indicated that the risks of serious heatwaves had increased in the major part of the basin, and decreased in southwestern and southern parts.

Key words: extreme heat events, heatwave, Dongting Lake catchment, risk, copula

中图分类号:

P467

张晓艳, 刘梅先. 洞庭湖流域高温热浪风险变化特征[J]. 长江流域资源与环境, 2015, 24(10): 1729-1735.

ZHANG Xiao-yan, LIU Mei-xian. TRENDS AND RISKS OF EXTREME HEAT EVENTS IN THE DONGTING LAKE CATCHMENT[J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2015, 24(10): 1729-1735.

参考文献

[1] HOU W.Climatic characteristics over China in 2013[J].Meteorol Mon,2014,40:491-501.
[2] BASU R,SAMET J M.Relation between elevated ambient temperature and mortality:A review of the epidemiologic evidence[J].Epidemiologic Reviews,2002,24(2):190-202.
[3] SMOYER K E,RAINHAM D G C,HEWKO J N.Heat-stress-related mortality in five cities in Southern Ontario:1980-1996[J].International Journal of Biometeorology,2000,44(4):190-197.
[4] 王丽荣,雷隆鸿.天气变化对人口死亡率的影响——以广州市和上海市为例[J].生态科学,1997,16(2):83-88.
[5] 吴凡.南京市高温热浪对天气敏感性疾病的影响研究[D].南京信息工程大学,2013.
[6] 张剑明,黎祖贤,章新平,等.湖南省近46年来降水时空分布特征及趋势分析[J].水文,2009,29(4):73-78.
[7] 罗伯良,张超,林浩.近40年湖南省极端强降水气候变化趋势与突变特征[J].气象,2008,34(1):80-85.
[8] 王国杰,姜彤,王艳君,等.洞庭湖流域气候变化特征(1961-2003)[J].湖泊科学,2006,18(5):470-475.
[9] 覃鸿,黄菊梅,闫雍,等.1961-2013年洞庭湖区夏季高温热浪的时空分布特征[C].第31届中国气象学会年会S4 极端气候事件和灾害风险管理,2014.
[10] 叶殿秀,尹继福,陈正洪,等.1961-2010 年我国夏季高温热浪的时空变化特征[J].气候变化研究进展,2013,9(1):015-020.
[11] SUN Y,ZHANG X B,ZWIERS F W,et al.Rapid increase in the risk of extreme summer heat in Eastern China[J].Nature climate change,2014,DOI:10.1038/NCLIMATE2410.
[12] 董思言,徐影,周波涛,等.基于CMIP5模式的中国地区未来高温灾害风险预估[J].气候变化研究进展,2014,10(5):365-369.
[13] 李景刚,黄诗峰,李纪人,等.1960-2008年间洞庭湖流域降水变化时空特征分析[J].中国水利水电科学研究院学报,2010,8(4):275-280.
[14] 薛联青,张竞楠,刘晓群,等.基于改进的综合气象干旱指数的洞庭湖流域干旱时空特征[J].河海大学学报(自然科学版),2014,42(1):1-6.
[15] DING T,QIAN W H,YAN Z W.Changes in hot days and heatwaves in China during 1961-2007[J].International Journal of Climatology,2010,30:1452-1462.
[16] YUE S,WANG C Y.Applicability of prewhitening to eliminate the influence of serial correlation on the Mann-Kendall test[J].Water Resources Research,2002,38(6) 4-1-4-7.
[17] STERN R D.The Calculation of Probability-Distributions for Models of Daily Precipitation[J].Archiv Fur Meteorologie Geophysik Und Bioklimatologie Serie B-Klimatologie Umweltmeteorologie Strahlungsforschung,1980,28(1-2):137-147.
[18] ZHANG Q,LI J F,SINGH V P,et al.Copula-based spatio-temporal patterns of precipitation extremes in China[J].International Journal of Climatology,2013,33(5):1140-1152.
[19] ZHANG L,SINGH V P.Bivariate rainfall frequency distributions using Archimedean copulas[J].Journal of Hydrology,2007,332(1-2):93-109.
[20] YUSOF F,HUI-MEAN F,SUHAILA J,et al.Characterisation of Drought Properties with Bivariate Copula Analysis[J].Water Resources Management,2013,27(12):4183-4207.
[21] TRIVEDI P K,ZIMMER D M.Copula modeling:an introduction for practitioners[J].Foundations and Trends in Econometrics 1(1),Now Publishers.,2007.
[22] LIU M X,XU X L,SUN A,et al.Is southwestern China experiencing more frequent precipitation extremes?[J].Environ.Res.Lett.,2014,9:064002(14p).
[23] 李国琛.全球气候变暖成因分析[J].自然灾害学报,2005,14(5):38-42.
[24] 张强,万素琴,毛以伟,等.三峡库区复杂地形下的气温变化特征[J].气候变化研究进展,2005,1(4):164-167.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed