Statistical modeling of the space–time relation between wind and significant wave height

Abstract. Many marine activities, such as designing ocean structures and planning marine operations, require the characterization of sea-state climate. This study investigates the statistical relationship between wind and sea states, considering its spatiotemporal behavior. A transfer function is established between wind fields over the North Atlantic (predictors) and the significant wave height (predictand) at three locations: southwest of the French coast (Gironde), the English Channel, and the Gulf of Maine. The developed method considers both wind seas and swells by including local and global predictors. Using a fully data-driven approach, the global predictors' spatiotemporal structure is defined to account for the non-local and non-instantaneous relationship between wind and waves. Weather types are constructed using a regression-guided clustering method, and the resulting clusters correspond to different wave systems (swells and wind seas). Then, in each weather type, a penalized linear regression model is fitted between the predictor and the predictand. The validation analysis proves the models skill in predicting the significant wave height, with a root mean square error of approximately 0.3 m in the three considered locations. Additionally, the study discusses the physical insights underlying the proposed method.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Statistical modeling of the space–time relation between wind and significant wave height ; volume:9 ; number:1 ; year:2023 ; pages:67-81 ; extent:15
Advances in statistical climatology, meteorology and oceanography ; 9, Heft 1 (2023), 67-81 (gesamt 15)

Creator
Obakrim, Said
Ailliot, Pierre
Monbet, Valérie
Raillard, Nicolas

DOI
10.5194/ascmo-9-67-2023
URN
urn:nbn:de:101:1-2023060804282710509646
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
14.08.2025, 10:55 AM CEST

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Associated

  • Obakrim, Said
  • Ailliot, Pierre
  • Monbet, Valérie
  • Raillard, Nicolas

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