基于百分位阈值法的洞庭湖流域高温热浪时空特征

doi:10.3969/j.issn.1673-503X.2025.01.008

摘要/Abstract

摘要： 基于洞庭湖流域110个地面气象站点1961—2022年逐日最高气温和最低气温观测资料,采用百分位阈值确定了流域内各个站点暖日阈值和暖夜阈值,分析了洞庭湖流域暖日日数、暖夜日数、复合高温及高温热浪(频次、日数、强度)的时空变化特征。结果表明:洞庭湖流域暖日阈值和暖夜阈值均呈现出自西南向东北逐渐增加,这显然受流域西南高东北低的地形影响。流域年均暖日和暖夜日数均呈显著增加趋势,前者气候倾向率为1.6 d/10 a,后者达到2.6 d/10 a,即暖夜日数增加更快。流域暖日日数及暖夜日数的变化趋势在空间均呈现出流域中心低,四周高。另外,流域复合高温日数以及强度也均呈显著增加(增强)的趋势,气候倾向率分别为1.3 d/10 a、3.2 ℃/10 a,2000年以来,两者均表现出增速(增强)加快。流域高温热浪频次、日数均呈由西南向东北增加,高温热浪强度则表现为由南向北增加。研究时段内,流域高温热浪频次、日数、强度均呈显著增加趋势,气候倾向率分别为0.2次/10 a、1.3 d/10 a、2.0 ℃/10 a。热浪频次及热浪强度的变化趋势均呈现北中南三个带的差异,南北两带均比中部增加(增强)明显。流域年均热浪日数的变化趋势大致由流域中心向四周增加,流域东北部的洞庭湖区增加最明显,气候倾向率高达3.0 d/10 a。

关键词: 高温热浪, 暖日阈值, 暖夜阈值

Abstract: Based on daily maximum and minimum temperature observation data from 110 surface meteorological stations in the Dongting Lake basin from 1961 to 2022,the percentile threshold was used to determine the warm day threshold and the warm night threshold for each station.The spatial-temporal variation characteristics of warm days,warm nights,compound high temperature,high temperature heat wave frequency,high temperature heat wave days,and high temperature heat wave intensity in the Dongting Lake basin were analyzed.The results show that the warm day threshold and the warm night threshold in the Dongting Lake basin are gradually increasing from southwest to northeast,which is obviously affected by the topography of high in southwest and low in northeast.The average annual warm days and warm night days in the basin show a significant increasing trend.The former has a climate tendency rate of 1.6 d per decade,while the latter reaches 2.6 d per decade,indicating that the number of warm night days increases faster than the number of warm day days.The trend of changes in the number of warm days and warm nights in the watershed shows a low center and a high surrounding area in space.In addition,the number and intensity of composite high temperature days in the watershed also show a significant increasing (enhancement) trend,with climate tendency rates of 1.3 d per decade and 3.2 ℃ per decade,respectively.Since 2000,the number and intensity of composite high temperature days have shown an accelerated growth (enhancement) trend.The frequency and number of days of high-temperature heat waves in the watershed show a spatial distribution pattern of increasing from southwest to northeast,while the intensity of high-temperature heat waves increases from south to north.During the study period,the frequency,number of days and intensity of high temperature heat waves in the Dongting Lake basin showed a significant increasing trend,and the climate tendency rates were 0.2 times per decade,1.3 d per decade and 2.0 ℃ per decade,respectively.The variation trend of heat wave frequency and heat wave intensity show differences in the three zones of north,middle,and south.The heat wave frequency and intensity in the two zones of north and south are significantly increased (enhanced) compared to those in the central region.The significantly increased stations are mostly distributed in the north and south,while there are fewer in the central region.The change trend of annual average heat wave days in the basin increases from the center of the basin to the surrounding areas,with the most pronounced increase in the northeastern Dongting Lake,and the climate tendency rate as high as 3.0 d per decade.

Key words: Heat wave, Warm day threshold, Warm night threshold

中图分类号:

P467

张秋锦, 黄一民, 郝丽婷, 李丽蓉, 杨梓琪. 基于百分位阈值法的洞庭湖流域高温热浪时空特征[J]. 气象与环境学报, 2025, 41(1): 66-73.

ZHANG Qiujin, HUANG Yimin, HAO Liting, LI Lirong, YANG Ziqi. Spatiotemporal characteristics of high temperature and heat wave in Dongting Lake Basin based on percentile threshold method[J]. Journal of Meteorology and Environment, 2025, 41(1): 66-73.

参考文献

[1] Legg S.IPCC,2021:Climate Change 2021:The Physical Science Basic[J].Interaction(Melbourne),2021,49(4).
[2] Corey L,Pedram R,Navin R.Influence of extreme weather disasters on global crop production[J].Nature,2016,529(7584):84-87.
[3] 张可慧,李正涛,刘剑锋,等.河北地区高温热浪时空特征及其对工业、交通的影响研究[J].地理与地理信息科学,2011,27(6):90-95.
[4] Darryn M,Ahmed I,Mullett J.The impact of the 2009 heat wave on Melbourne's critical infrastructure[J].Local Environment,2012,17(8):783-796.
[5] Colombo A F,Etkin D,Karney B W.Climate Variability and the Frequency of Extreme Temperature Events for Nine Sites across Canada:Implications for Power Usage[J].Journal of Climate,1999,12(8):2490-2502.
[6] Garcell H G.COVID-19.A challenge for healthcare professionals COVID-19[J],Revista Habanera de Ciencias Médicas,2020,19(2).
[7] Barriopedro D,Fischer E M,Luterbacher J,et al.The hot summer of 2010:redrawing the temperature record map of Europe[J].Science,2011,332(6026):220-224.
[8] 贾佳,胡泽勇.中国不同等级高温热浪的时空分布特征及趋势[J].地球科学进展,2017,32(5):546-559.
[9] 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(1):15-20.
[10] Zheng Z,Xu G,Wang Y,et al.Characteristics and main influence factors of heat waves in Beijing-Tianjin-Shijiazhuang cities of northern China in recent 50 years[J].Atmospheric Science Letters,2020,21(11).
[11] 王秀萍,李燕,张悦,等.2018 年盛夏大连地区极端高温干旱天气环流特征及成因分析[J].气象与环境学报,2021,37(4):70-77.
[12] 郑雪梅,王怡,吴小影,等.近20年福建省沿海与内陆城市高温热浪脆弱性比较[J].地理科学进展,2016(10):1197-1205.
[13] Inostroza L,Palme M,Barrera F D L.A Heat Vulnerability Index:Spatial Patterns of Exposure,Sensitivity and Adaptive Capacity for Santiago de Chile[J].Plos One,2016,11(9):e0162464.
[14] 鹿文涵,谷少华,孙仕强,等.2013—2019年宁波市高温热浪对中暑的滞后影响[J].气象与环境学报,2022,38(1):106-112.
[15] 卜凡蕊,孙鹏,姚蕊,等.淮河流域高温热浪时空演变规律及成因分析[J].地理科学,2021,41(4):705-716.
[16] 邢佩,杨若子,杜吴鹏,等.1961—2017年华北地区高温日数及高温热浪时空变化特征[J].地理科学,2020,40(8):1365-1376.
[17] Im E-S,Pal J S,Eltahir E A B.Deadly heat waves projected in the densely populated agricultural regions of South Asia[J].Science Advances,2017,3(8).
[18] 王文,胡彦君,徐川怡.1961—2018年淮河流域热浪事件时空变化特征[J].地理科学,2021,41(5):911-921.
[19] 杨溟鋆,杜钦,王咏薇,等.重庆市1959—2018年夏季高温热浪及湿度影响特征分析[J].长江流域资源与环境,2021(030-010).
[20] Xie W,Zhou B,Han Z,et al.Substantial increase in daytime-nighttime compound heat waves and associated pop ulation exposure in China projected by the CMIP6 multimodal ensemble[J].Environmental Research Letters,2022,17(4):045007.
[21] Wang X,Lang X,Jiang D.Detectable anthropogenic influence on summer compound hot events over China from 1965 to 2014[J].Environmental Research Letters,2022,17(3):034042.
[22] Szentimrey T.Multiple analysis of series for homogenization(MASH) [C]//Proceedings of the Second Seminar for Homogenization of Surface Climatological Data.Geneva:WMO,1999:27-46.
[23] Choi N,Lee M I,Cha D H,et al.Decadal Changes in the Interannual Variability of Heat Waves in East Asia Caused by Atmospheric Teleconnection Changes[J].Journal of Climate,2019,33(4):1505-1522.
[24] 唐亚宁,周丙常,谢文贤.一元线性回归方程的三种显著性检验的等价性分析[J].高等数学研究,2022,25(6):76-78.
[25] 孔锋.1961-2018年中国极端冷暖事件变化及其空间差异特征[J].水利水电技术,2020,51(9):34-44.
[26] 符淙斌,王强.气候突变的定义和检测方法[J].大气科学,1992,16(4):482-493.
[27] 张曦,黎鑫.湖南省夏季高温热浪时空分布特征及其成因[J].气候与环境研究,2017,22(6):747-756.
[28] 傅帅,蒋勇,张小泉,等.近64年长沙市高温热浪事件统计分析[J].气象科技,2016,44(6):991-997.
[29] 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.
[30] 刘婷婷,朱秀芳,孙劭,等.阈值选择对高温时空变化特征的影响[J].地理科学,2023,43(4):726-736.
[31] 马双梅,祝从文,刘伯奇.2019年4—6月云南持续性高温天气的大气环流异常成因[J].大气科学,2021,45(1):165-180.