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

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

doi:https://doi.org/10.5194/ascmo-9-67-2023

Articles | Volume 9, issue 1

https://doi.org/10.5194/ascmo-9-67-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/ascmo-9-67-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 9, issue 1

05 Jun 2023

| 05 Jun 2023

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

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

Data sets

Statistical downscaling of significant wave height: data Said Obakrim, Pierre Ailliot, Valérie Monbet, and Nicolas Raillard https://doi.org/10.5281/zenodo.5845423

Statistical downscaling of significant wave height: code for data preparation and model Said Obakrim, Pierre Ailliot, Valérie Monbet, and Nicolas Raillard https://doi.org/10.5281/zenodo.5845250

HOMERE. Ifremer Laboratoire Comportement des Structures en Mer, Ifremer Laboratoire Spatial et In terfaces Air Mer Mickael Accensi and Christophe Maisondieu https://doi.org/10.12770/cf47e08d-1455-4254-955e-d66225c9dc90

Short summary

Ocean wave climate has a significant impact on human activities, and its understanding is of socioeconomic and environmental importance. In this study, we propose a statistical model that predicts wave heights in a location in the Bay of Biscay. The proposed method allows us to understand the spatiotemporal relationship between wind and waves and predicts well both wind seas and swells.