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江苏四类低温事件致灾因子与基于影响的低温风险时空分布对比研究

汪宁 谢志清 高苹 李昕 张灵玲 苗茜

汪宁,谢志清,高苹,李昕,张灵玲,苗茜. 2023. 江苏四类低温事件致灾因子与基于影响的低温风险时空分布对比研究. 气象学报,81(1):1-14 doi: 10.11676/qxxb2023.20220058
引用本文: 汪宁,谢志清,高苹,李昕,张灵玲,苗茜. 2023. 江苏四类低温事件致灾因子与基于影响的低温风险时空分布对比研究. 气象学报,81(1):1-14 doi: 10.11676/qxxb2023.20220058
Wang Ning, Xie Zhiqing, Gao Ping, Li Xin, Zhang Lingling, Miao Qian. 2023. Differences in Spatiotemporal Variation and Risk Zoning of Four Types of Extreme Cold Events in Jiangsu Province. Acta Meteorologica Sinica, 81(1):1-14 doi: 10.11676/qxxb2023.20220058
Citation: Wang Ning, Xie Zhiqing, Gao Ping, Li Xin, Zhang Lingling, Miao Qian. 2023. Differences in Spatiotemporal Variation and Risk Zoning of Four Types of Extreme Cold Events in Jiangsu Province. Acta Meteorologica Sinica, 81(1):1-14 doi: 10.11676/qxxb2023.20220058

江苏四类低温事件致灾因子与基于影响的低温风险时空分布对比研究

doi: 10.11676/qxxb2023.20220058
基金项目: 国家重点研发计划项目(2022YFC3080500),国家自然科学基金项目(42075118、41505052),江苏省气象局面上项目(KM202202),江苏省自然科学基金面上项目(BK20211396)
详细信息
    作者简介:

    汪宁,主要从事气候变化和极端气候事件机理及影响研究。E-mail:ningwang0309@hotmail.com,电话:13770734504

    通讯作者:

    谢志清,Email:xiezhiqing9896@163.com

  • 中图分类号: P467

Differences in Spatiotemporal Variation and Risk Zoning of Four Types of Extreme Cold Events in Jiangsu Province

  • 摘要: 利用1961—2020年江苏省70个气象观测站数据,分析了4类低温事件(寒潮、霜冻、低温阴雨寡照和冰冻)的时空分布特征,建立4类低温灾害危险性评估指标和综合危险性指标,结合人口、经济(GDP)两类承灾体的暴露度和脆弱性指数,建立了低温灾害风险评估模型,评估了江苏省低温灾害影响人口和GDP的风险等级及其空间分布。结果表明:(1)1961—2020年江苏省寒潮、霜冻和低温阴雨寡照事件发生数较多,冰冻事件发生数较少;研究时段内四种低温事件发生日数呈交替出现或多灾种同期多发的特征,1961—1980年寒潮和霜冻事件发生日均较多,2001—2020年低温阴雨寡照和冰冻事件同期多发。(2)江苏省中、南部寒潮频次较多,年平均累积降温幅度较大;霜冻日数北多南少,极端最低气温北部明显较低;低温阴雨寡照日数从西南到东北递减,南部降水偏多,北部过程平均温度较低;江苏西北、西南地区冰冻日数均较多,与降水空间分布一致。(3)江苏北部为寒潮和霜冻灾害高危险区,霜冻危险性呈纬向带状分布,低温阴雨寡照高危险区域集中在西南部;冰冻高危险区在南部和北部均有出现。低温综合危险性在北部和西南部较高,中部和东南部较低。(4)低温对人口和GDP的风险等级具有空间差异,由于承灾体的空间非连续性打破了气象条件的连续性分布,导致低温灾害对不同承灾体所产生的可能风险在空间分布上产生差异。

     

  • 图 1  1961—2020年江苏省4种极端低温事件发生日数的年变化 (单位:d)

    Figure 1.  Annual occurrences of four types of cold events in Jiangsu Province during 1961—2020 (unit:d)

    图 2  1961—2020年江苏省4种极端低温事件的Morlet小波功率谱 (a. 寒潮,b. 霜冻,c. 低温阴雨寡照,d. 冰冻;左图为各年的小波功率谱,网状阴影代表通过95%信度水平检验,灰色V型阴影区域为边缘效应影响,右边曲线为全周期小波频率谱)

    Figure 2.  Morlet wavelets of frequencies of four types of extreme low temperature events (a. cold air outbreak,b. frost events,c. cold-rainy events,d. frozen events;The left column is the wavelet power spectrum for each year. The reticulation indicates the 95% confidence level against red noise and the cone of influence (COI). Areas where the edge effects might distort the picture are shown by light grey shading. The right column is the wavelet power spectrum of each period)

    图 3  1961—2020年江苏省 (a) 寒潮发生总日数 (单位:d)、(b) 年平均累积降温幅度 (单位:℃) 和 (c) 极端最低气温 (单位:℃) 的空间分布

    Figure 3.  Spatial distributions of (a) total occurrence (unit:d),(b) accumulative drop of temperature (unit:℃) and (c) extreme temperature (unit:℃) of cold air outbreaks in Jiangsu Province during 1961 to 2020

    图 4  1961—2020年江苏省 (a) 霜冻总日数 (单位:d)、(b)霜冻过程平均最低气温 (单位:℃) 和(c)霜冻过程极端最低气温 (单位:℃) 的空间分布

    Figure 4.  Spatial distributions of (a) total occurrence (unit:d),(b) average temperature (unit:℃) and (c) extreme temperature (unit:℃) of frost events in Jiangsu Province during 1961—2020

    图 5  1961—2020年江苏省 (a) 低温阴雨寡照总日数 (单位:d)、(b) 平均最低温度 (单位:℃) 和 (c) 累积降水量 (单位:mm) 的空间分布

    Figure 5.  Spatial distributions of (a) total occurrence (unit:days),(b) average temperature (unit:℃) and (c) accumulative precipitation (unit:mm) of cold and rainy events in Jiangsu Province during 1961—2020

    图 6  1961—2020年江苏省 (a) 冰冻总日数 (单位:d)、(b) 冰冻事件极端最低气温 (单位:℃) 和 (c) 冰冻过程累积降水量 (单位:mm) 的空间分布

    Figure 6.  Spatial distributions of (a) total occurrence (unit:d),(b) extreme cold temperature (unit:℃) and (c) accumulative precipitation (unit:mm) of frozen events in Jiangsu Province during 1961—2020

    图 7  江苏省 (a) 寒潮、(b) 霜冻、(c) 低温阴雨寡照、(d) 冰冻事件危险等级空间分布

    Figure 7.  Spatial distributions of dangerousness levels of (a) cold air outbreak events,(b) frost events,(c) cold and rainy events,(d) frozen events in Jiangsu Province

    图 8  江苏省极端低温灾害总体危险性等级空间分布

    Figure 8.  Spatial distribution of composite level of danger for four types of cold events in Jiangsu Province

    图 9  江苏省持续性低温灾害对人口 (a) 和GDP (b) 风险特征的空间分布

    Figure 9.  Risk levels of (a) population and (b) GDP caused by cold events in Jiangsu Province

    图 10  江苏省人口 (a,单位:人) 和GDP (b,单位:万元) 的空间分布

    Figure 10.  Spatial distributions of population (a) and GDP (b) in Jiangsu Province

    图 11  江苏省连续性低温事件危险性等级分布以及各地低温灾害造成损失的灾情次数

    Figure 11.  The level of danger for Jiangsu Province and the numbers of cold events that have caused damages in corresponding areas

    表  1  低温灾害危险性等级划分标准

    Table  1.   The standards for levels of danger for cold events

    等级值等级名称标准
    1HHave+σ
    2中高HaveHHave+σ
    3中低Have-σHHave
    4HHave+σ
    注:H为危险性指数,Have为区域内危险性指数平均值,σ为危险性指数标准差。
    下载: 导出CSV

    表  2  低温灾害风险等级划分标准

    Table  2.   The standards for levels of risk of cold events

    等级值等级名称标准
    1RRave+σ
    2中高Rave +0.5≤RRave +σ
    3Rave -0.5σRRave +0.5σ
    4中低Rave -σRRave -0.5σ
    5R<Rave -σ
    注:R为低温灾害风险值,Rave为区域内风险值平均值,σ为风险值标准差。
    下载: 导出CSV

    表  3  江苏省4种极端低温事件在不同时段的年平均发生日数 (单位:d)

    Table  3.   Annual average occurrences of four types of extreme cold events in Jiangsu Province during three periods (unit:days)

    时段寒潮霜冻低温阴雨寡照冰冻
    1961—1980年71.1131.75**105.6*0.15*
    1981—2000年67.5125.05**119.15*2.75*
    2000—2020年69.55116.55**120.1*2.7*
    注:*表示通过95%信度检验,**为与另两个时段均通过检验,*为仅与另一个时段通过检验。
    下载: 导出CSV
  • 郭艳君, 朱勇, 吴贤云等. 2021. 低温灾害调查与风险评估技术规范(评估与区划类). 中国气象局. Guo Y J, Zhu Y, Wu X Y. et al. 2021. Specification of investigation and risk assessment of cold disasters (assessment and zoning). China Meteorological Administration (in Chinese)
    姜彤,王艳君,翟建青. 2018. 气象灾害风险评估技术指南. 北京:气象出版社,298pp

    Jiang T,Wang Y J,Zhai J Q. 2018. Technical Guide for Risk Assessment of Meteorological Disasters. Beijing:China Meteorological Press,298pp (in Chinese)
    李刚,马继望,梁湘三. 2020. 2008年1月中国南方低温雨雪期间异常阻塞高压事件的多尺度动力过程分析. 气象学报,78(1):18-32

    Li G,Ma J W,Liang X S. 2020. A study of the multiscale dynamical processes underlying the blocking high that caused the January 2008 freezing rain and snow storm in southern China. Acta Meteor Sinica,78(1):18-32 (in Chinese)
    李尚锋,姜大膀,廉毅等. 2018. 冬季中国东北极端低温事件环流背景特征分析. 大气科学,42(5):963-976

    Li S F,Jiang D B,Lian Y,et al. 2018. Circulation characteristics of extreme cold events in Northeast China during wintertime. Chinese J Atmos Sci,42(5):963-976 (in Chinese)
    梁平,白慧,田楠等. 2009. 黔东南州2008年低温雨雪冰冻灾害气象因素影响定量评价. 气象科技,37(4):496-502 doi: 10.3969/j.issn.1671-6345.2009.04.023

    Liang P,Bai H,Tian N,et al. 2009. Quantitative impact evaluation of low-temperature,rain/snow and freezing disasters in southeastern Guizhou in 2008. Meteor Sci Technol,37(4):496-502 (in Chinese) doi: 10.3969/j.issn.1671-6345.2009.04.023
    彭贵芬,段旭,舒康宁. 2010. 云南2008年冰冻灾害评估. 气象,36(10):72-77 doi: 10.7519/j.issn.1000-0526.2010.10.012

    Peng G F,Duan X,Shu K N. 2010. An estimate of the 2008 freezing disaster in Yunnan. Meteor Mon,36(10):72-77 (in Chinese) doi: 10.7519/j.issn.1000-0526.2010.10.012
    彭勇刚,黄肖寒,莫益江等. 2018. 基于层次分析法的农业气象灾害风险区划指标权重分析. 气象研究与应用,39(1):70-72 doi: 10.3969/j.issn.1673-8411.2018.01.016

    Peng Y G,Huang X H,Mo Y J,et al. 2018. Index weight analysis of agrometeorological disaster risk zoning based on AHP. J Meteor Res Appl,39(1):70-72 (in Chinese) doi: 10.3969/j.issn.1673-8411.2018.01.016
    石晨,廉毅,杨旭等. 2020. 东北亚和北半球冬季高空切断冷涡与中国极端低温事件的联系. 气象学报,78(5):778-795 doi: 10.11676/qxxb2020.049

    Shi C,Lian Y,Yang X,et al. 2020. The relationship between winter cut-off cold vortexes in Northeast Asia and northern hemisphere as well as their connections with extreme low temperature events in China. Acta Meteor Sinica,78(5):778-795 (in Chinese) doi: 10.11676/qxxb2020.049
    王春玲,郭文利,李迅等. 2018. 京津冀地区高速公路冰冻灾害风险区划. 气象与环境学报,34(1):45-51 doi: 10.3969/j.issn.1673-503X.2018.01.006

    Wang C L,Guo W L,Li X,et al. 2018. Risk zoning of freezing disaster at motorway in Beijing-Tianjin-Hebei region. J Meteor Environ,34(1):45-51 (in Chinese) doi: 10.3969/j.issn.1673-503X.2018.01.006
    王颖,王晓云,江志红等. 2013. 中国低温雨雪冰冻灾害危险性评估与区划. 气象,39(5):585-591 doi: 10.7519/j.issn.1000-0526.2013.05.006

    Wang Y,Wang X Y,Jiang Z H,et al. 2013. Assessment and zoning of low-temperature,rain/snow and freezing disasters in China. Meteor Mon,39(5):585-591 (in Chinese) doi: 10.7519/j.issn.1000-0526.2013.05.006
    汪子琪,张文君,耿新. 2017. 两类ENSO对中国北方冬季平均气温和极端低温的不同影响. 气象学报,75(4):564-580

    Wang Z Q,Zhang W J,Geng X. 2017. Different influences of two types of ENSO on winter temperature and cold extremes in northern China. Acta Meteor Sinica,75(4):564-580 (in Chinese)
    Bueh C,Peng J B,Lin D W,et al. 2022. On the two successive supercold waves straddling the end of 2020 and the beginning of 2021. Adv Atmos Sci,39(4):591-608 doi: 10.1007/s00376-021-1107-x
    Charlton A J,O’Neill A,Lahoz W A,et al. 2004. Sensitivity of tropospheric forecasts to stratospheric initial conditions. Quart J Roy Meteor Soc,130(600):1771-1792 doi: 10.1256/qj.03.167
    Chen T C,Yen M C,Huang W R,el al. 2002. An East Asian cold surge:case study. Mon Wea Rev,130(9):2271-2290 doi: 10.1175/1520-0493(2002)130<2271:AEACSC>2.0.CO;2
    Cohen J,Screen J A,Furtado J C,et al. 2014. Recent Arctic amplification and extreme mid-latitude weather. Nat Geosci,7(9):627-637 doi: 10.1038/ngeo2234
    Dai G K,Li C X,Han Z,et al. 2022. The nature and predictability of the East Asian extreme cold events of 2020/21. Adv Atmos Sci,39(4):566-575 doi: 10.1007/s00376-021-1057-3
    Dalle B,Admirat P. 2011. Wet snow accretion on overhead lines with French report of experience. Cold Reg Sci Technol,65(1):43-51 doi: 10.1016/j.coldregions.2010.04.015
    Jia X L,Liang X Y. 2013. Possible impacts of Madden-Julian oscillation on the severe rain-snow weather in China during November 2009. J Trop Meteor,19(3):233-241
    Jiang Z H,Wu Y Z,Liu Z Y,et al. 2015. A diagnostic analysis of air temperature anomaly mode over China in 2009/2010 winter based on generalized equilibrium feedback assessment (Gefa) Method. J Trop Meteor,21(2):121-130
    Luo D H, Xiao Y Q, Yao Y, et al. 2016: Impact of Ural blocking on winter warm Arctic-cold Eurasian anomalies. Part I: Blocking-induced amplification. J Climate, 29(11): 3925-3947
    Overland J,Francis J A,Hall R,et al. 2015. The melting Arctic and midlatitude weather patterns:are they connected. J Climate,28(20):7917-7932 doi: 10.1175/JCLI-D-14-00822.1
    Park T W,Ho C H,Jeong S J,et al. 2011. Different characteristics of cold day and cold surge frequency over East Asia in a global warming situation. J Geophys Res,116(D12):D12118 doi: 10.1029/2010JD015369
    Petoukhov V,Semenov V A. 2010. A link between reduced Barents-Kara sea ice and cold winter extremes over northern continents. J Geophys Res,115(D21):D21111 doi: 10.1029/2009JD013568
    Yao Y,Zhang W Q,Luo D H,et al. 2022. Seasonal cumulative effect of Ural blocking episodes on the frequent cold events in China during the early winter of 2020/21. Adv Atmos Sci,39(4):609-624 doi: 10.1007/s00376-021-1100-4
    Zhang X D,Fu Y F,Han Z,et al. 2022a. Extreme cold events from East Asia to North America in winter 2020/21:comparisons,causes,and future implications. Adv Atmos Sci,39(4):553-565 doi: 10.1007/s00376-021-1229-1
    Zhang Y X,Si D,Ding Y H,et al. 2022b. Influence of major stratospheric sudden warming on the unprecedented cold wave in East Asia in January 2021. Adv Atmos Sci,39(4):576-590 doi: 10.1007/s00376-022-1318-9
    Zheng F,Yuan Y,Ding Y H,et al. 2022. The 2020/21 extremely cold winter in China influenced by the synergistic effect of La Niña and warm Arctic. Adv Atmos Sci,39(4):546-552 doi: 10.1007/s00376-021-1033-y
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  • 收稿日期:  2022-04-06
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