Please wait a minute...
Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

Postal Subscription Code 80-963

2018 Impact Factor: 1.205

Front. Earth Sci.    2022, Vol. 16 Issue (1) : 109-120    https://doi.org/10.1007/s11707-020-0856-7
RESEARCH ARTICLE
The impact of Typhoon Lekima (2019) on East China: a postevent survey in Wenzhou City and Taizhou City
Cong ZHOU1,2, Peiyan CHEN1,3,4(), Shifang YANG4,5, Feng ZHENG4,6, Hui YU1,3,4, Jie TANG1,3,4, Yi LU1,3,4, Guoming CHEN1, Xiaoqing LU1, Xiping ZHANG1, Jing SUN1
1. Shanghai Typhoon Institute of China Meteorological Administration, Shanghai 200030, China
2. Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai 200438, China
3. Key Laboratory of Numerical Modeling for Tropical Cyclones China Meteorological Administration, Shanghai 200030, China
4. The Joint Laboratory for Typhoon Forecasting Technique Applications between Shanghai Typhoon Institute and Wenzhou Meteorological Bureau, Wenzhou 325000, China
5. Taizhou Meteorological Bureau, Taizhou 318000, China
6. Wenzhou Meteorological Bureau, Wenzhou 325000, China
 Download: PDF(2392 KB)  
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

Typhoon Lekima (2019) struck Zhejiang Province on 10 August 2019 as a supertyphoon, which severely impacted Zhejiang Province. The typhoon killed 45 people and left three others missing, and the total economic loss reached 40.71 billion yuan. This paper reports a postdisaster survey that focuses on the storm precipitation, flooding, landslides, and weather services associated with Typhoon Lekima (2019) along the south-eastern coastline of Zhejiang Province. The survey was conducted by a joint survey team from the Shanghai Typhoon Institute and local meteorological bureaus from 26 to 28 August, 2019, approximately two weeks after the disaster. Based on this survey and subsequent analyses of the results, we hope to develop countermeasures to prevent future tragedies.

Keywords Typhoon Lekima (2019)      Zhejiang Province      disaster assessment      postdisaster survey     
Corresponding Author(s): Peiyan CHEN   
Online First Date: 13 July 2021    Issue Date: 04 March 2022
 Cite this article:   
Cong ZHOU,Peiyan CHEN,Shifang YANG, et al. The impact of Typhoon Lekima (2019) on East China: a postevent survey in Wenzhou City and Taizhou City[J]. Front. Earth Sci., 2022, 16(1): 109-120.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-020-0856-7
https://academic.hep.com.cn/fesci/EN/Y2022/V16/I1/109
1 P Chen, X Lei, M Ying (2013). Introduction and application of a new comprehensive assessment index for damage caused by tropical cyclones. Trop Cyclone Res Rev, 2: 176–183
2 P Chen, H Y Yu, T L Xiao, Z Q Yan (2009). Cause analysis and preliminary hazard estimate of typhoon disaster in China. J Nat Disast, 18: 64–73 (in Chinese)
3 P Chen, H Yu, M Xu, X Lei, F Zeng (2019). A simplified index to assess the combined impact of tropical cyclone precipitation and wind on China. Front Earth Sci, 13(4): 672–681
https://doi.org/10.1007/s11707-019-0793-5
4 D Cox, T Arikawa, A Barbosa, G Guannel, D Inazu, A Kennedy, Y Li, N Mori, K Perry, D Prevatt (2019). Hurricanes Irma and Maria postevent survey in US Virgin Islands. Coast Eng J, 61(2): 121–134
https://doi.org/10.1080/21664250.2018.1558920
5 D P Eisenman, K M Cordasco, S Asch, J F Golden, D Glik (2007). Disaster planning and risk communication with vulnerable communities: lessons from Hurricane Katrina. Am J Public Health, 97(Suppl 1): S109–S115
https://doi.org/10.2105/AJPH.2005.084335 pmid: 17413069
6 J R Elliott, J Pais (2006). Race, class, and Hurricane Katrina: Social differences in human responses to disaster. Soc Sci Res, 35(2): 295–321
https://doi.org/10.1016/j.ssresearch.2006.02.003
7 K Emanuel, S Ravela, E Vivant, C Risi (2006). A statistical deterministic approach to hurricane risk assessment. Bull Am Meteorol Soc, 87(3): S1–S5
https://doi.org/10.1175/BAMS-87-3-Emanuel
8 W Fang, W Lin (2013). A review on typhoon wind field modeling for disaster risk assessment. Prog Geogr, 32: 852–867
9 W Fang, X Shi (2012). A review of stochastic modeling of tropical cyclone track and intensity for disaster risk assessment. Adv in Earth Sci, 27: 866–875 (in Chinese)
10 K Hugelius, M Gifford, P Örtenwall, A Adolfsson (2017). Health among disaster survivors and health professionals after the Haiyan Typhoon: a self-selected Internet-based web survey. Int J Emerg Med, 10(1): 13
https://doi.org/10.1186/s12245-017-0139-6 pmid: 28357722
11 X T Lei, P Y Chen, Y H Yang, Y Z Qian (2009). Characters and objective assessment of disasters caused by typhoons in China. Acta Meteorol Sin, 67: 875–883
12 C J Li, Y J Wang, X H Shen, J Q Ye (2004). Remote Sensing Survey and Integrated Investigation of Land and Resources in Zhejiang Province. Beijing: Geological Publishing House
13 H C Li, L S Hsieh, L C Chen, L Y Lin, W S Li (2014). Disaster investigation and analysis of Typhoon Morakot. J Chin Inst Eng, 37(5): 558–569
https://doi.org/10.1080/02533839.2012.736771
14 C Y Lin, T C Chen, C Y Dai, M L Yu, P L Lu, J H Yen, Y H Chen (2015). Serological investigation to identify risk factors for post-flood infectious diseases: a longitudinal survey among people displaced by Typhoon Morakot in Taiwan, China. BMJ Open, 5(5): e007008
https://doi.org/10.1136/bmjopen-2014-007008 pmid: 25976763
15 N Lin, K Emanuel, M Oppenheimer, E Vanmarcke (2012). Physically based assessment of hurricane surge threat under climate change. Nat Clim Chang, 2(6): 462–467
https://doi.org/10.1038/nclimate1389
16 Y Lu, F Ren, W Zhu (2018). Risk zoning of typhoon disasters in Zhejiang Province, China. Nat Hazards Earth Syst Sci, 18(11): 2921–2932
https://doi.org/10.5194/nhess-18-2921-2018
17 Y Lu, H Yu, Q Yang, M Xu, F Zheng, J Zhu (2017). Post-disaster survey of Typhoon Megi in Wenzhou City. Trop Cyclone Res Rev, 6: 34–39
18 X Q Lu, B K Zhao (2013). Analysis of the climatic characteristics of landing tropical cyclones in East China. J Trop Meteorol, 19: 145–153
19 T Ma, C Li, Z Lu, Q Bao (2015). Rainfall intensity–duration thresholds for the initiation of landslides in Zhejiang Province, China. Geomorphology, 245: 193–206
https://doi.org/10.1016/j.geomorph.2015.05.016
20 T MellmanA, David D, Kulick-Bell R, Hebding J, Nolan B (1995). Sleep disturbance and its relationship to psychiatric morbidity after Hurricane Andrew. Am J Psychiatry, 152(11): 1659–1663
https://doi.org/10.1176/ajp.152.11.1659
21 Y Tajima, Y Tomohiro, M P Benito, C Eric, K Koji, N Hisamichi, M Mamoru, A Yuji, A Taro, M O Noel, A Ronwaldo, M William, V Justin, B Ferdinand (2014). Initial report of JSCE-PICE joint survey on the storm surge disaster caused by Typhoon Haiyan. Coast Eng J, 56(1): 1450006-1–1450006-12
https://doi.org/10.1142/S0578563414500065
22 Y Tajima, P L John, C Jeane, S Mizuka, M Yoshinao, S Takenori, B Dominic, T Marjorie, C Eric (2017 ).Post-disaster survey of storm surge and waves along the coast of Batanes, the Philippines, caused by Super Typhoon Meranti/Ferdie. Coast Eng J, 59(1): 1750009-1–1750009-11
https://doi.org/10.1142/S0578563417500097
23 P J Vickery, F J Masters, M D Powell, D Wadhera (2009). Hurricane hazard modeling: the past, present, and future. J Wind Eng Ind Aerodyn, 97(7–8): 392–405
https://doi.org/10.1016/j.jweia.2009.05.005
24 H E Willoughby, P G Black (1996). Hurricane Andrew in Florida: dynamics of a disaster. Bull Am Meteorol Soc, 77(3): 543–549
https://doi.org/10.1175/1520-0477(1996)077<0543:HAIFDO>2.0.CO;2
25 Q Zhang, L Wu, Q Liu (2009). Tropical cyclone damages in China 1983–2006. Bull Am Meteorol Soc, 90(4): 489–496
https://doi.org/10.1175/2008BAMS2631.1
[1] Guomin CHEN, Xiping ZHANG, Qing CAO, Zhihua ZENG. Evaluation of forecast performance for Super Typhoon Lekima in 2019[J]. Front. Earth Sci., 2022, 16(1): 17-33.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed