Publications des scientifiques de l'IRD

Krien Y., Arnaud G., Cece R., Ruf C., Belmadani A., Khan J., Bernard D., Islam A. K. M. S., Durand Fabien, Testut Laurent, Palany P., Zahibo N. (2018). Can we improve parametric cyclonic wind fields using recent satellite remote sensing data ?. Remote Sensing, 10 (12), p. art. 1963 [18 p.]. ISSN 2072-4292.

Titre du document
Can we improve parametric cyclonic wind fields using recent satellite remote sensing data ?
Année de publication
2018
Type de document
Article référencé dans le Web of Science WOS:000455637600105
Auteurs
Krien Y., Arnaud G., Cece R., Ruf C., Belmadani A., Khan J., Bernard D., Islam A. K. M. S., Durand Fabien, Testut Laurent, Palany P., Zahibo N.
Source
Remote Sensing, 2018, 10 (12), p. art. 1963 [18 p.] ISSN 2072-4292
Parametric cyclonic wind fields are widely used worldwide for insurance risk underwriting, coastal planning, and storm surge forecasts. They support high-stakes financial, development and emergency decisions. Yet, there is still no consensus on a potentially best parametric approach, nor guidance to choose among the great variety of published models. The aim of this paper is to demonstrate that recent progress in estimating extreme surface wind speeds from satellite remote sensing now makes it possible to assess the performance of existing parametric models, and select a relevant one with greater objectivity. In particular, we show that the Cyclone Global Navigation Satellite System (CYGNSS) mission of NASA, along with the Advanced Scatterometer (ASCAT), are able to capture a substantial part of the tropical cyclone structure, and to aid in characterizing the strengths and weaknesses of a number of parametric models. Our results suggest that none of the traditional empirical approaches are the best option in all cases. Rather, the choice of a parametric model depends on several criteria, such as cyclone intensity and the availability of wind radii information. The benefit of using satellite remote sensing data to select a relevant parametric model for a specific case study is tested here by simulating hurricane Maria (2017). The significant wave heights computed by a wave-current hydrodynamic coupled model are found to be in good agreement with the predictions given by the remote sensing data. The results and approach presented in this study should shed new light on how to handle parametric cyclonic wind models, and help the scientific community conduct better wind, wave, and surge analyses for tropical cyclones.
Plan de classement
Limnologie physique / Océanographie physique [032] ; Télédétection [126]
Description Géographique
ATLANTIQUE ; PACIFIQUE EST
Localisation
Fonds IRD [F B010074949]
Identifiant IRD
fdi:010074949
Contact