海平面上升、强台风和风暴潮对厦门海域极值水位的影响及危险性预估

许炜宏; 蔡榕硕

doi:10.12284/hyxb2021081

海平面上升、强台风和风暴潮对厦门海域极值水位的影响及危险性预估

doi: 10.12284/hyxb2021081

许炜宏^1,,
蔡榕硕^1, ,

自然资源部第三海洋研究所，福建厦门 361005

基金项目: 国家重点研发计划 (2017YFA0604902，2017YFA0604903，2017YFA0604901）；自然资源部第三海洋研究所基本科研业务费专项资金资助项目（海三科2017030）

详细信息

作者简介:
许炜宏（1995—），男，福建省晋江市人，主要从事海洋环境研究。E-mail：xuweihong@tio.org.cn

通讯作者:
蔡榕硕，男，研究员，主要从事气候变化和海洋环境研究。E-mail：cairongshuo@tio.org.cn

中图分类号: P731.23
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出版历程
- 收稿日期: 2020-04-16
- 修回日期: 2020-05-20
- 网络出版日期: 2021-03-23
- 刊出日期: 2021-07-06

Impacts of sea level rise, strong typhoon and storm surge on extreme sea level in coastal waters of Xiamen and hazards estimation

Xu Weihong^1
,,
Cai Rongshuo^{1
, ,}

Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China

摘要

摘要: 气候变化背景下海平面上升、强台风和风暴潮对我国东南沿海地区的洪涝灾害影响日益严重，为应对气候变化的影响，本文以位于我国东南沿海的厦门地区为例，应用多种海洋大气观测资料和数理统计及模拟方法，分析了历史上9914号和1614号两次台风对厦门海域极端海面高度(极值水位)的影响，预估了未来海平面上升情景下厦门海域极值水位的变化及其危险性。结果表明：(1) 9914号台风期间，天文大潮、风暴增水和强降水的同时出现造成了厦门沿海地区超警戒极值水位(732 cm)的出现；(2) 风(向岸强风)、雨(强降水)、浪(巨浪)、潮(高潮位)、流(急流)等多致灾因子的共同作用是厦门沿海地区发生严重灾情的重要原因；(3) 在温室气体中等和高排放(RCP4.5和RCP8.5)情景下，到2050年(2100年)，当前百年一遇的极值水位将分别变为30年(2年)一遇(RCP4.5)和25年(低于1年)一遇(RCP8.5)的频繁极端事件。这表明未来厦门沿海极值水位的危险性将显著上升，应采取充分的适应措施降低洪涝灾害风险。
- 海平面上升 /
- 台风 /
- 风暴潮 /
- 极值水位 /
- 危险性
Abstract: Sea level rise, strong typhoon and storm surge have increasingly serious impacts on coastal flood disasters in the southeastern China in the context of climate change. To address the climate change and estimate the hazard of extreme sea level in the future, based on the multiple data of oceanographic and atmospheric observation and methods of mathematical statistics, the impact of historical strong typhoon No.9914 (Dan) and No.1614 (Meranti) on the extreme sea level in coastal waters of Xiamen and estimates the changes and return of extreme sea level at scenarios of future sea level rise under RCP4.5 and RCP8.5 was analyzed in this paper. The results show that: (1) astronomical tide, storm surges and heavy precipitation induced the extreme sea level event (732 cm) during the period of strong typhoon No.9914; (2) the combined impacts of multiple hazards such as wind (ashore gale), rainfall (heavy precipitation), waves (giant waves), tides (high tide) and current (torrents) is an important cause of serious disasters in coastland of Xiamen; (3) under the medium and high greenhouse gas emission scenarios (RCP4.5 and RCP8.5), by 2050 and 2100, recent 1-in-100-year extreme sea level event will become 1-in-30-year (1-in-2-year) and 1-in-25-year (1-in-less than 1-year). It shows that the hazards of extreme sea level on coastland of Xiamen will increase significantly, and high adaptation measures in Xiamen should be taken to reduce the risk on coastal flood hazards in the future.
- sea level rise /
- typhoon /
- storm surge /
- extreme sea level /
- hazards

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图 1 9914号、1614号台风全局路径(a)及其局部路径(b)

Fig. 1 The whole tracks (a) and the partial tracks (b) of typhoon No.9914 and No.1614

下载: 全尺寸图片幻灯片

图 2 9914号台风“丹恩”期间厦门海域的天文潮位、风暴增水和降水过程

Fig. 2 The astronomical tide, storm surge and precipitation in coastal waters of Xiamen during the period of No.9914 Typhoon Dan

下载: 全尺寸图片幻灯片

图 3 1999年10月9日9914号台风“丹恩”登陆前后厦门海域海平面气压和地面10 m风场的变化（资料源自ERA-5）

Fig. 3 The change of sea level pressure and the 10 m wind field in coastal waters of Xiamen during the landing time of No.9914 Typhoon Dan on October 9, 1999 (data from ERA-5)

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图 4 1999年10月9日9914号台风“丹恩”期间厦门岛周边海域的表层潮流场

a. 低潮（06时）；b. 涨急（10时）；c. 高潮（12时）；d. 落急（15时）

Fig. 4 Surface flow field in coastal waters of Xiamen during the period of No.9914 Typhoon Dan on October 9, 1999

a. Low tide (06:00); b. flood peak (10:00); c. high tide (12:00); d. ebb peak (15:00)

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图 5 1999年10月9日9914号台风“丹恩”期间厦门附近海域平均波浪方向和有效波高（资料源自ERA-5）

Fig. 5 Wave direction and significant wave height in coastal waters of Xiamen during the period of No.9914 Typhoon Dan on October 10, 1999 (data from ERA-5)

下载: 全尺寸图片幻灯片

图 6 1614号台风“莫兰蒂”影响期间厦门海域天文潮位、风暴增水和降水过程

Fig. 6 The astronomical tide, storm surge and precipitation in coastal waters of Xiamen during the period of No.1614 Typhoon Meranti

下载: 全尺寸图片幻灯片

图 7 2016年9月14−15日1614号台风“莫兰蒂”登陆前后厦门附近海域海平面气压和10 m风场的变化（资料源自ERA-5）

Fig. 7 The change of sea level pressure and the 10 m wind field in coastal waters of Xiamen during the landing time of No.1614 Typhoon Meranti from September 14, 2016 to September 15, 2016 (data from ERA-5)

下载: 全尺寸图片幻灯片

图 8 2016年9月14−15日1614号台风“莫兰蒂”期间厦门岛周边海域平均波浪方向和有效波高（资料源自ERA-5）

Fig. 8 Wave direction and significant wave height in coastal waters of Xiamen during the period of No.1614 Typhoon Meranti from September 14, 2016 to September 15, 2016 (data from ERA-5)

下载: 全尺寸图片幻灯片

图 9 在RCP4.5(a)和RCP8.5(b)情景下未来厦门验潮站的极值水位事件和重现期（相对于1954−1999年平均海平面）的变化

Fig. 9 The relation between expected extreme sea level events and return period at Xiamen tidal gauge station, references to 1954−1999 mean sea level and future conditions for RCP 4.5 (a) and RCP 8.5 (b) scenarios

下载: 全尺寸图片幻灯片

表 1 1989−2018年我国沿海各省因风暴潮造成损失情况

Tab. 1 The losses caused by storm surges in each coastal provinces of China from 1989 to 2018

省份	死亡及失踪人数	直接经济损失/亿元
辽宁	3	22.33
河北	2	41.92
天津	9	3.43
山东	170	102.86
江苏	53	103.19
上海	22	39.92
浙江	1942	691.16
福建	1291	983.97
广东	487	990.56
广西	160	94.83
海南	221	371.48

下载: 导出CSV

表 2 不同气候（RCP4.5、RCP8.5）情景下厦门验潮站50年一遇和100年一遇的极值水位的变化（相对于1954−1999年）

Tab. 2 1-in-50-year and 1-in-100-year extreme sea level events at Xiamen tidal gauge station, referenced to 1954−1999 for RCP (4.5, 8.5) scenarios

气候情景	时间	重现期/a	对应极值水位高度/cm
	当前	50	737
	当前	100	751
RCP4.5	2030年	50	750
	2030年	100	764
	2050年	50	762
	2050年	100	776
	2100年	50	798
	2100年	100	812
RCP8.5	2030年	50	751
	2030年	100	765
	2050年	50	765
	2050年	100	779
	2100年	50	822
	2100年	100	836

下载: 导出CSV

表 3 不同气候（RCP4.5、RCP8.5）情景下厦门验潮站当前50年一遇和100年一遇极值水位的重现期的变化（相对于1954−1999年）

Tab. 3 The return period of recent 1-in- 50-year and 1-in-100-year extreme sea level events at Xiamen tidal gauge station, referenced to 1954−1999 for RCP (4.5,8.5) scenarios

气候情景	当前重现期/a	时间	相同高度未来重现期/a
RCP4.5	50	2030年	26
		2050年	10
		2100年	<1
	100	2030年	55
		2050年	30
		2100年	2
RCP8.5	50	2030年	25
		2050年	8
		2100年	<1
	100	2030年	53
		2050年	25
		2100年	<1

下载: 导出CSV

参考文献(35)

[1]	Rhein M, Rintoul S R, Aoki S, et al. Observations: Ocean[M]//Stocker T F, Qin D, Plattner G K, et al. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. United Kingdom and New York, NY, USA: Cambridge University Press, 2014: 255−316.
[2]	Oppenheimer M, Glavovic B, Hinkel J, et al. Sea level rise and implications for low-lying islands, coasts and communities[R/OL]//Pörtner H O, Roberts D C, Masson-Delmotte V, et al. IPCC Special Report on the Ocean and Cryosphere in a Changing Climate. [2019−09−24]. https://www.ipcc.ch/srocc/chapter/chapter-4-sea-level-rise-and-implications-for-low-lying-islands-coasts-and-communities/.
[3]	蔡榕硕, 谭红建. 海平面加速上升对低海拔岛屿、沿海地区及社会的影响和风险[J]. 气候变化研究进展, 2020, 16(2): 163−171. Cai Rongshuo, Tan Hongjian. Impacts and risks of accelerating sea level rise on low lying islands, coasts and communities[J]. Climate Change Research, 2020, 16(2): 163−171.
[4]	Hu Pan, Zhang Qiang, Shi Peijun, et al. Flood-induced mortality across the globe: spatiotemporal pattern and influencing factors[J]. Science of the Total Environment, 2018, 643: 171−182. doi: 10.1016/j.scitotenv.2018.06.197
[5]	Beven II J L, Avila L A, Blake E S, et al. Atlantic hurricane season of 2005[J]. Monthly Weather Review, 2008, 136(3): 1109−1173. doi: 10.1175/2007MWR2074.1
[6]	于福江, 董剑希, 叶琳, 等. 中国风暴潮灾害史料集1949−2009[M]. 北京: 海洋出版社, 2015. Yu Fujiang, Dong Jianxi, Ye Lin, et al. Collection of Storm Surge Disasters Historical Data in China 1949−2009[M]. Beijing: China Ocean Press, 2015.
[7]	自然资源部. 1989年−2018年中国海洋灾害公报[EB/OL]. [2019−09−24]. http://www.mnr.gov.cn/sj/sjfw/hy/gbgg/zghyzhgb/ Ministry of Natural Resources of the People's Republic of China. 1989−2018 Chinese marine disaster bulletin[EB/OL]. [2019−09−24]. http://www.mnr.gov.cn/sj/sjfw/hy/gbgg/zghyzhgb/
[8]	Fang Jiayi, Liu Wei, Yang Saini, et al. Spatial-temporal changes of coastal and marine disasters risks and impacts in Mainland China[J]. Ocean & Coastal Management, 2017, 139: 125−140.
[9]	李夏火, 陈美娜, 蓝虹, 等. 9914号台风风暴潮、巨浪特点分析及其预报[J]. 海洋预报, 2000, 17(2): 25−33. doi: 10.3969/j.issn.1003-0239.2000.02.004 Li Xiahuo, Chen Meina, Lan Hong, et al. The analysis and forecast of storm surges and mountainous waves caused by Typhoon 9914[J]. Marine Forecasts, 2000, 17(2): 25−33. doi: 10.3969/j.issn.1003-0239.2000.02.004
[10]	Kossin J P, Emanuel K A, Camargo S J. Past and projected changes in western North Pacific tropical cyclone exposure[J]. Journal of Climate, 2016, 29(16): 5725−5739. doi: 10.1175/JCLI-D-16-0076.1
[11]	Hallegatte S, Green C, Nicholls R J, et al. Future flood losses in major coastal cities[J]. Nature Climate Change, 2013, 3(9): 802−806. doi: 10.1038/nclimate1979
[12]	自然资源部. 2018年中国海平面公报[EB/OL]. [2019−04−28]. http://gi.mnr.gov.cn/201905/t20190510_2411195.html. Ministry of Natural Resources of the People's Republic of China. 2019 report on China’s sea level[EB/OL]. [2019−04−28]. http://gi.mnr.gov.cn/201905/t20190510_2411195.html.
[13]	自然资源部. 2019年中国海平面公报[EB/OL]. [2020−04−30]. http://gi.mnr.gov.cn/202004/t20200430_2510978.html. Ministry of Natural Resources of the People's Republic of China. 2019 report on China’s sea level[EB/OL]. [2020−04−30]. http://gi.mnr.gov.cn/202004/t20200430_2510978.html.
[14]	Hartfield G, Blunden J, Arndt D S. State of the climate in 2017[J]. Bulletin of the American Meteorological Society, 2018, 99(8): S1−S310.
[15]	Dieng H B, Cazenave A, Meyssignac B, et al. New estimate of the current rate of sea level rise from a sea level budget approach[J]. Geophysical Research Letters, 2017, 44(8): 3744−3751. doi: 10.1002/2017GL073308
[16]	袁方超, 张文舟, 杨金湘, 等. 福建近海海平面变化研究[J]. 应用海洋学学报, 2016, 35(1): 23−35. Yuan Fangchao, Zhang Wenzhou, Yang Jinxiang, et al. Study on sea level variability in off shore Fujian[J]. Journal of Applied Oceanography, 2016, 35(1): 23−35.
[17]	陈特固, 黄博津, 汤超莲, 等. 广东省海平面变化的过去和未来[J]. 广东气象, 2013, 35(2): 8−13. doi: 10.3969/j.issn.1007-6190.2013.02.002 Chen Tegu, Huang Bojin, Tang Chaolian, et al. The past and future of sea level variations in Guangdong Province[J]. Guangdong Meteorology, 2013, 35(2): 8−13. doi: 10.3969/j.issn.1007-6190.2013.02.002
[18]	潘玉萍, 张晓强, 赵曼. 近六十年东南沿海地区热带气旋的周期特征分析及气象保障对策研究[C]//第28届中国气象学会年会. 厦门: 中国气象学会, 2011. Pan Yuping, Zhang Xiaoqiang, Zhao Man. Southeast coastal area for nearly 60 years cycle analysis of the characteristics of tropical cyclones and weather protection countermeasures[C]// Proceedings of the 28th Annual Meeting of the Chinese Meteorological Society. Xiamen: China Meteorological Society, 2011.
[19]	殷克东, 孙文娟. 风暴潮灾害经济损失评估指标体系研究[J]. 中国渔业经济, 2011, 29(3): 87−90. doi: 10.3969/j.issn.1009-590X.2011.03.013 Yin Kedong, Sun Wenjuan. Research on the index system of the storm surge disaster economic loss assessment[J]. Chinese Fisheries Economics, 2011, 29(3): 87−90. doi: 10.3969/j.issn.1009-590X.2011.03.013
[20]	丁骏, 江海东, 应岳. 舟山市沿海海平面上升预测和淹没分析[J]. 杭州师范大学学报(自然科学版), 2013, 12(4): 373−378. Ding Jun, Jiang Haidong, Ying Yue. Sea level rise prediction and submerging analysis of Zhoushan coastal area[J]. Journal of Hangzhou Normal University (Natural Sciences Edition), 2013, 12(4): 373−378.
[21]	Kopp R E, Horton R M, Little C M, et al. Probabilistic 21st and 22nd century sea-level projections at a global network of tide-gauge sites[J]. Earth’s Future, 2014, 2(8): 383−406. doi: 10.1002/2014EF000239
[22]	米伟亚. Excel在水文皮尔逊Ⅲ型分布多样本参数估计中的应用研究[J]. 农业与技术, 2005, 25(5): 93−95, 112. doi: 10.3969/j.issn.1671-962X.2005.05.037 Mi Weiya. Study on the application of excel to Pearson type Ⅲ distribution multi-samples parameter estimation in hydrology[J]. Agriculture & Technology, 2005, 25(5): 93−95, 112. doi: 10.3969/j.issn.1671-962X.2005.05.037
[23]	喻国良, 李艳红, 庞红犁, 等. 海岸工程水文学[M]. 上海: 上海交通大学出版社, 2009: 68−79. Yu Guoliang, Li Yanhong, Pang Hongli, et al. Hydrology of Coastal Engineering[M]. Shanghai: Shanghai Jiao Tong University Press, 2009: 68−79.
[24]	Kendall M G. A new measure of rank correlation[J]. Biometrika, 1938, 30(1/2): 81−93. doi: 10.2307/2332226
[25]	Xu Lilai, He Yuanrong, Huang Wei, et al. A multi-dimensional integrated approach to assess flood risks on a coastal city, induced by sea-level rise and storm tides[J]. Environmental Research Letters, 2016, 11(1): 014001. doi: 10.1088/1748-9326/11/1/014001
[26]	中国气象局. 中国气象灾害年鉴（2017）[M]. 北京: 气象出版社, 2018. China Meteorological Administration. Yearbook of Meteorological Disasters in China (2017)[M]. Beijing: China Meteorological Press, 2018.
[27]	Wahl T, Jain S, Bender J, et al. Increasing risk of compound flooding from storm surge and rainfall for major US cities[J]. Nature Climate Change, 2015, 5(12): 1093−1097. doi: 10.1038/nclimate2736
[28]	王蓉, 姚小娟, 肖瑜璋, 等. 1208号台风“韦森特”特征分析[J]. 海洋预报, 2013, 30(6): 13−20. doi: 10.11737/j.issn.1003-0239.2013.06.003 Wang Rong, Yao Xiaojuan, Xiao Yuzhang, et al. Analysis of the characteristic of typhoon “Vicente” (1208)[J]. Marine Forecasts, 2013, 30(6): 13−20. doi: 10.11737/j.issn.1003-0239.2013.06.003
[29]	林翩然, 温生辉, 汤军健. 厦门海域二维潮流数值计算[J]. 应用海洋学学报, 2008, 27(4): 526−532. doi: 10.3969/j.issn.1000-8160.2008.04.019 Lin Pianran, Wen Shenghui, Tang Junjian. Numerical simulation of two-dimensional tidal current filed in Xiamen waters[J]. Journal of Oceanography in Taiwan Strait, 2008, 27(4): 526−532. doi: 10.3969/j.issn.1000-8160.2008.04.019
[30]	杨顺良, 欧寿铭. 9914号台风对厦门岛东南部岸滩的环境效应[J]. 台湾海峡, 2001, 20(1): 115−122. Yang Shunliang, Ou Shouming. Environmental impact southeastern coast and beach of Xiamen Island during typhoon No.9914[J]. Journal of Oceanography in Taiwan Strait, 2001, 20(1): 115−122.
[31]	张延廷, 王以娇. 渤海风暴潮与天文潮耦合作用的数值模拟[J]. 海洋学报, 1990, 12(4): 426−431. Zhang Yanting, Wang Yijiao. Coupled numerical simulation on wave and storm surge in Bohai Sea[J]. Haiyang Xuebao, 1990, 12(4): 426−431.
[32]	林双毅, 周锦业, 秦一芳, 等. 莫兰蒂台风对厦门市主要道路绿化树种的影响[J]. 中国园林, 2018, 34(5): 83−87. doi: 10.3969/j.issn.1000-6664.2018.05.016 Lin Shuangyi, Zhou Jinye, Qin Yifang, et al. The influence of typhoon Meranti on the greening tree species for urban road in Xiamen[J]. Chinese Landscape Architecture, 2018, 34(5): 83−87. doi: 10.3969/j.issn.1000-6664.2018.05.016
[33]	Wang Meiya, Xu Hanqiu. Remote sensing-based assessment of vegetation damage by a strong typhoon (Meranti) in Xiamen Island, China[J]. Natural Hazards, 2018, 93(3): 1231−1249. doi: 10.1007/s11069-018-3351-7
[34]	Emanuel K. Will global warming make hurricane forecasting more difficult?[J]. Bulletin of the American Meteorological Society, 2017, 98(3): 495−501. doi: 10.1175/BAMS-D-16-0134.1
[35]	Kossin J P. A global slowdown of tropical-cyclone translation speed[J]. Nature, 2018, 558(7708): 104−107. doi: 10.1038/s41586-018-0158-3