气候变化领域集成服务门户(CCPortal): Toward the probabilistic forecasting of cyclone-induced marine flooding by overtopping at Reunion Island aided by a time-varying random-forest classification approach

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DOI	10.1007/s11069-020-04307-y
	Toward the probabilistic forecasting of cyclone-induced marine flooding by overtopping at Reunion Island aided by a time-varying random-forest classification approach
	Lecacheux S.; Rohmer J.; Paris F.; Pedreros R.; Quetelard H.; Bonnardot F.
发表日期	2021
ISSN	0921030X
起始页码	227
结束页码	251
卷号	105 期号:1
英文摘要	In 2017, Irma and Maria highlighted the vulnerability of small islands to cyclonic events and the necessity of advancing the forecast techniques for cyclone-induced marine flooding. In this context, this paper presents a generic approach to deriving time-varying inundation forecasts from ensemble track and intensity forecasts applied to the case of Reunion Island in the Indian Ocean. The challenge for volcanic islands is to account for the full complexity of wave overtopping processes while also ensuring a robustness and timeliness that are compatible with emergency requirements. The challenge is addressed by following a hybrid approach relying on the combination of process-based models with a statistical model (herein, a random-forest classifier) trained with a precalculated database. The latter enables one to translate any time series of coastal marine conditions into the time-varying probability of inundation for different sectors. The application detailed for the case of Cyclone Dumile at Sainte-Suzanne city shows that the proposed approach enables quick discrimination, in both space and time, thereby identifying safe and exposed areas and demonstrating that probabilistic forecasting of marine flooding by overtopping is feasible. The whole method can be easily adapted to other territories and scales provided that validated process-based models are available. Beyond early warning applications, the developed database and statistical models may also be used for informing risk prevention and adaptation strategies. © 2020, Springer Nature B.V.
关键词	Cyclones Machine learning Marine flooding Modeling Overtopping Probabilistic forecast
英文关键词	climate modeling; ensemble forecasting; flooding; machine learning; overtopping; probability; tropical cyclone; Mascarene Islands; Reunion
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206353
作者单位	BRGM, 3 av. C. Guillemin, Orléans, 45060, France; Météo-France Océan Indien, 50 Blvd du Chaudron, Sainte-Clotilde, La Réunion 97491, France
推荐引用方式 GB/T 7714	Lecacheux S.,Rohmer J.,Paris F.,et al. Toward the probabilistic forecasting of cyclone-induced marine flooding by overtopping at Reunion Island aided by a time-varying random-forest classification approach[J],2021,105(1).
APA	Lecacheux S.,Rohmer J.,Paris F.,Pedreros R.,Quetelard H.,&Bonnardot F..(2021).Toward the probabilistic forecasting of cyclone-induced marine flooding by overtopping at Reunion Island aided by a time-varying random-forest classification approach.Natural Hazards,105(1).
MLA	Lecacheux S.,et al."Toward the probabilistic forecasting of cyclone-induced marine flooding by overtopping at Reunion Island aided by a time-varying random-forest classification approach".Natural Hazards 105.1(2021).