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较多,冰冻事件发生较少;研究时段内4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,年平均累计降温幅度较大;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。Abstract: Based on observations collected at 70 stations in Jiangsu province from 1961 to 2020, spatial and temporal variations of four types of cold events are investigated first. A total of 14 evaluation indicators related to cold damages are selected to build the dangerousness index. Using the population and GDP data, the dangerous level and risk-zoning of cold events are then assessed. The results are as follows: (1) Cold air outbreaks, frost events and cold-rainy events frequently occur in Jiangsu province during 1961—2020, while the frozen events have a small total number of occurrence days. Cold air outbreaks and frost events have the maximum number of occurrence days during 1961—1980, while cold-rainy events and frozen events reach the maximum occurrence in 2001—2020. (2) Cold air outbreaks occur frequently in central and southern Jiangsu province during 1961—2020. Correspondingly, frost events occur more frequently over the northern areas than over the southern part of Jiangsu province. The number of days with cold-rainy events shows a decreasing tendency from southwest to northeast of Jiangsu province. Frozen events frequently occur in the southwest and northwest of Jiangsu province, where frozen events have a spatial distribution similar to that of precipitation. (3) High level of danger for cold air outbreak and frost events is located in the north of Jiangsu province, while the high level of danger for cold-rainy events is found in the southwestern areas of Jiangsu province. The high level of danger for frozen events appears in both south and north of Jiangsu province. The composite dangerousness of the four types of cold events shows that the high level of danger is located in the north and southwest of Jiangsu province and the low level appears in central and southeastern areas. (4) There exist notable differences in the spatial distribution and area of high risk between the population and GDP, which are mainly resulted from the spatially discontinuous hazard-bearing body under the condition of a similar meteorological environment in Jiangsu province.
-
Key words:
- Cold events /
- Cold air outbreak /
- Cold-rainy events /
- Dangerousness /
- Risk zoning
-
-
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
-
计量
- 文章访问数:
- PDF下载数:
- 施引文献: 0