Directional wave spectra at the regional scale with the KuROS airborne radar: comparisons with models

Abstract

In situ observations, satellite observations, as well as regional observations from airborne remote sensing are very useful to characterize sea-state evolution and related physical processes, improve numerical modelling and contribute to climate variable survey. Directional wave spectra describe the complexity of sea-state and give access to parameters such as directional parameters (mean direction and directional distribution of energy) and frequency parameters (peak frequency, frequency spread). In this paper, directional ocean wave spectra and their parameters, retrieved from observations carried out with the airborne radar system KuROS during two field campaigns, are analyzed. These campaigns provide a very rich variety of meteorological conditions: high wind conditions either fetch-limited cases or mature sea conditions and moderate wind conditions and sea-state dominated by swell. The objective of this paper is to compare the KuROS data set with numerical wave model outputs and buoy observations. This comparison aims first at assessing the performances on main wave parameters (significant wave height, mean direction at the peak, peak frequency) retrieved from KuROS in different conditions (wind sea, swell, mixed seas). And then, to discuss on parameters characterizing the shape of the wave spectra, namely the frequency and the directional spread. Results of the comparisons show that, due to the size of the KuROS radar footprint, ocean waves with dominant wavelengths lower than 200 m are the most appropriate situations for wave retrieval. They also show an overestimation of the model frequency spread and an underestimation of the model directional spread compare to KuROS and buoy data for both campaigns.

Directional and Frequency Spread of Surface Ocean Waves From SWIM Measurements

“…From comparison between MFWAM results with buoy and KuROS airborne radar data (KuROS is a concept similar to SWIM), Le Merle et al. (2019) concluded on the same kind of overestimation of the model frequency spread compared to buoy and radar observations in fetch limited conditions in the Mediterranean sea. Several authors have also discussed in the past, that the frequency width of the modeled wave spectrum is highly sensitive to the way the non‐linear interactions are taken into account (Gagnaire‐Renou, 2009; Hasselmann & Hasselmann, 1985a, 1985b; Rogers & Van Vledder, 2013).…”

Speckle Noise Spectrum at Near-Nadir Incidence Angles for a Time-Varying Sea Surface

“…Equation (1)(2)(3)(4) here above are identical to (7)(8)(9)(10)(11)(12) in [1]. Jackson then transposes this formalism to the wavenumber domain by writing, ν = ,…”

“…We recall first that KuROS is a Ku-band (f=13.5GHz) radar, with a near-nadir pointing rotating antenna, which provides the backscattering coefficients in the incidence range from about 5° to 18° and the azimuth range of 0 to 360° . The data sets analyzed here come from KuROS flights carried out in the northwestern part of the Mediterranean Sea as part of the Hymex experiment [10], [12].…”

“…This method is now operationally used by The European Space Agency to provide wave spectra from SAR images. It was also later used by Caudal [10] and Le Merle [12] in the processing of their airborne real-aperture scanning radar observations to retrieve wave spectra.…”

Processing Technology Based on Radar Signal Design and Classification

“…The progress and development of radar technology cannot be separated from the promotion of multidisciplinary basic research, such as optics [128,129], measuring means [130][131][132], imaging [133], experimental observation [134], algorithm improvement [135], and model optimization [136]. Multidisciplinary radar design and optimization [137,138] not only considers the coupling design between disciplines but also is more appropriate to the essence of the problem, so that the radar signal can be high quality and fidelity.…”