热带气旋是我国沿海区域发生频率最高的自然灾害之一，伴随气旋登陆或过境时的集中降水、风暴潮和波浪增水等会引起沿海地区水位的显著增高和大范围淹水，给当地带来巨大的生命、财产损失。如这几年登陆东南沿海的台风天鸽（2017）、玛莉亚（2018）和山竹（2018）给我国带来的经济损失分别在289亿元(ESCAP/WMO Typhoon Committe 2018)、30亿元和52亿元人民币，死亡人数共约30人。在全球变暖的气候变化背景下，全球海平面以1.7±0.3 mm/yr (Church and White 2006; Holgate 2007)的平均速率上升，而热带气旋则呈现强度增强、尺寸增大(Webster et al., 2005; Sun et al., 2017)、高强度气旋发生频率增加(Webster et al. 2005; Elsner et al. 2008; Song et al. 2018)等趋势。这些变化趋势使沿海区域面临更大风暴潮、更大淹没面积以及更多受灾人数的风险。
近岸淹水过程与风暴潮的产生与传播机制密切相关，其中关键气象因子的影响研究主要基于人工台风的参数试验，包括台风强度、方向角、行进速度等(如Peng et al. 2006; Rego and Li 2009; Thomas et al. 2019)。而台风大小对风暴潮灾害的重要性直到飓风Katrina (2005)之后才为学者所关注，但尚未有基于实际台风事件的数值模拟研究。最近河海大学海岸灾害及防护教育部重点实验室杨洁老师与包括Philip L-F. Liu教授在内的知名学者在JGR-Oceans上合作发表了风暴潮引起的淹水过程比较研究。该研究对1925年以来给澳门带来最严重淹水灾害的两场台风（2017年“天鸽”和2018年“山竹”）风暴潮进行了动力影响机制研究。基于在澳门和珠海等地开展的针对台风“天鸽”和“山竹”的灾后现场勘测，首次给出了台风“山竹”的风暴潮淹水数据，同时采用天文潮-风暴潮-波浪的耦合数学模型，对引起淹水的气象（如台风路径、大小）、降水和波浪等物理因素进行了探讨，并构建了全面的包含淹水深度、范围、历时、流速和波峰抵达时间等信息的淹水灾害图，有助于进一步对行人安全、建筑物损伤等进行风险评估。该研究对于沿海城市的风暴潮灾害预防和管理提供了重要的理论和数据支撑。
(Yang, J., Li, L., Zhao, K., Wang, P., Wang, D., Sou, I.M., Yang, Z., Hu, J., Tang, X., Mok, K.M., Liu, P.L., 2019. A Comparative Study of Typhoon Hato (2017) and Typhoon Mangkhut (2018)—Their Impacts on Coastal Inundation in Macau. Journal of Geophysical Research: Oceans, 124(12): 9590–9619. https://doi.org/10.1029/2019JC015249)
图1 台风“山竹”期间天文潮潮位、台风路径和大小对最大增水分布的影响
图2 台风“天鸽”和“山竹”期间风暴潮波峰抵达时间与淹水流场变化
参考文献：
Church, John A., and Neil J. White. 2006. A 20th century acceleration in global sea-level rise. Geophysical Research Letters 33: L01602. https://doi.org/10.1029/2005GL024826.
Elsner, James B., James P. Kossin, and Thomas H. Jagger. 2008. The increasing intensity of the strongest tropical cyclones. Nature 455: 92–95. https://doi.org/10.1038/NATURE07234.
ESCAP/WMO Typhoon Committe. 2018. Replacement Names of HAIMA, SARIKA, NOCK-TEN and MERANTI in the Tropical Cyclone Name List.
Holgate, S. J. 2007. On the decadal rates of sea level change during the twentieth century. Geophysical Research Letters 34: L01602. https://doi.org/10.1029/2006GL028492.
Peng, Machuan, Lian Xie, and Leonard J. Pietrafesa. 2006. A numerical study on hurricane-induced storm surge and inundation in Charleston Harbor, South Carolina. Journal of Geophysical Research 111: C08017. https://doi.org/10.1029/2004JC002755.
Rego, João Lima, and Chunyan Li. 2009. On the importance of the forward speed of hurricanes in storm surge forecasting: A numerical study. Geophysical Research Letters 36: L07609. https://doi.org/10.1029/2008GL036953.
Song, Jinjie, Philip J. Klotzbach, Jianping Tang, and Yuan Wang. 2018. The increasing variability of tropical cyclone lifetime maximum intensity. Scientific Reports 8: 16641. https://doi.org/10.1038/s41598-018-35131-x.
Sun, Yuan, Zhong Zhong, Tim Li, Lan Yi, Yijia Hu, Hongchao Wan, Haishan Chen, Qianfeng Liao, Chen Ma, and Qihua Li. 2017. Impact of Ocean Warming on Tropical Cyclone Size and Its Destructiveness. Scientific Reports 7: 1–10. https://doi.org/10.1038/S41598-017-08533-6.
Thomas, Ajimon, JC Dietrich, TG Asher, M Bell, BO Blanton, JH Copeland, AT Cox, CN Dawson, JG Fleming, and RA Luettich. 2019. Influence of storm timing and forward speed on tides and storm surge during Hurricane Matthew. Ocean Modelling 137: 1–19. https://doi.org/10.1016/j.ocemod.2019.03.004.
Webster, P. J., Greg J. Holland, J. A. Curry, and H.-R Chang. 2005. Changes in Tropical Cyclone Number, Duration, and Intensity in a Warming Environment. Science 309: 1844–1846. https://doi.org/10.1126/science.1116448.