DOI: 10.1007/s11069-020-04307-y
论文题名: Toward the probabilistic forecasting of cyclone-induced marine flooding by overtopping at Reunion Island aided by a time-varying random-forest classification approach
作者: Lecacheux S. ; Rohmer J. ; Paris F. ; Pedreros R. ; Quetelard H. ; Bonnardot F.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 105, 期: 1 起始页码: 227
结束页码: 251
语种: 英语
中文关键词: 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
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. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/169152
Appears in Collections: 气候变化与战略
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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
Recommended Citation:
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]. Natural Hazards,2021-01-01,105(1)