Statistical Comparison of Ocean Wave Directional Spectra Derived From SWIM/CFOSAT Satellite Observations and From Buoy Observations - Archive ouverte HAL Access content directly
Journal Articles IEEE Transactions on Geoscience and Remote Sensing Year : 2022

Statistical Comparison of Ocean Wave Directional Spectra Derived From SWIM/CFOSAT Satellite Observations and From Buoy Observations

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Abstract

The comparison and verification of ocean wave spectrum by remote sensing and by in-situ measurements at the spectral level is quite rare, because the use of the traditional comparison method lead to very limited spatio-temporal matching pairs. In this paper, a new comparison method is proposed. With this method, under different sea conditions (wind wave mainly/swell mainly) and sea surface conditions (wind speed smaller than 20m/s, significant wave height from 1m to 7m), mean directional wave height spectra from SWIM (Surface Waves Investigation and Monitoring) are compared at the spectral level to the buoy counterparts, in different classes of sea-state. This includes the comparison of the omni-directional wave height spectrum and the directional function at the peak wave number. The comparison results show that under medium and high sea conditions, wave directional spectra provided by the SWIM beams at 8 ° and 10 ° incidence have a high consistency with those from buoy data. Under low sea conditions, the measurement bias of SWIM wave directional spectra mainly comes from three phenomena which are, by order of importance, an abnormal lifting of spectral energy caused by non-wave components at low wave numbers (parasitic peak), from the non-linear surfboard effect in the radar imaging mechanism and from a slight underestimation of speckle noise spectral density.
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Dates and versions

hal-03740045 , version 1 (28-07-2022)

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Cite

Ying Xu, Danièle Hauser, Jianqiang Liu, Jianyang Si, Chen Yan, et al.. Statistical Comparison of Ocean Wave Directional Spectra Derived From SWIM/CFOSAT Satellite Observations and From Buoy Observations. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60, pp.5117520. ⟨10.1109/TGRS.2022.3199393⟩. ⟨hal-03740045⟩
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