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Can contemporary satellites estimate swell dissipation rate?

Authors :
Jiang, Haoyu
Babanin, Alexander V.
Liu, Qingxiang
Stopa, Justin E.
Chapron, Bertrand
Chen, Ge
Source :
Remote Sensing of Environment. Nov2017, Vol. 201, p24-33. 10p.
Publication Year :
2017

Abstract

Swell dissipation can influence air-sea interactions and is an error source in numerical models. Remote sensors, including altimeters and synthetic aperture radars, were employed to estimate swell dissipation rates in previous studies. A detailed error analysis is conducted here to better understand the results of these studies. With the help of a numerical model, we find that the point source model cannot separate swell dissipation from frequency dispersion and angular spreading effectively. Monte Carlo simulations of remotely sensing an ideal swell packet show that the accuracy of the estimated dissipation rate depends on the number, the span, and the wave height error of the observations on the swell track. The results also demonstrate that the dependence between estimated dissipation rates and wave steepness is an inherent relation from the fitting process which cannot prove that the boundary-layer turbulence is the leading reason for swell dissipation. Both the point source and the measurement errors of wave heights cause large errors of estimated dissipation rates. Comparing the overall error with the estimated dissipation rates, this study shows that the present swell tracking scheme using satellite data is sufficient to estimate a mean dissipation rate statistically through many swell tracks but is insufficient for case studies of swell dissipation. Besides, a buffer analysis shows that islands might cause more potential errors in many swell tracks used in previous studies, and ideal locations for future experiments are also identified. More advanced techniques are required for a better understanding of swell dissipation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00344257
Volume :
201
Database :
Academic Search Index
Journal :
Remote Sensing of Environment
Publication Type :
Academic Journal
Accession number :
125415746
Full Text :
https://doi.org/10.1016/j.rse.2017.08.037