Assessment of ocean wave spectrum using global Envisat/ASAR data and hindcast simulation

Abstract

Wave mode of spaceborne synthetic aperture radar (SAR) is designed for the global ocean wave observations. Despite the fact that the significant wave height inferred from SAR measurements has been validated against model output and in-situ data, SAR's primary and unique capability for operational 2-dimensional spectral description of sea state remains to be fully evaluated. In this study, we extended the previous assessment approaches by introducing a new SAR image spectral parameter, the Mean rAnge Cross-Spectrum (MACS) that focuses on the isolated wave scales along the radar line-of-sight direction. MACS is an efficient variable in that it characterizes the local wave spectra properties without need of the non-linear wave inversion procedure. The assessment is based on the multiple-year data acquired by Envisat/ASAR wave mode, along with the collocated WaveWatch III (WW3) hindcast and the in-situ buoy-observed wave spectra, for which the SAR forward transformation is systematically performed to obtain the simulated image spectra. Inter-comparison between SAR-measured and WW3-simulated MACS demonstrates that the consistency is wavelength (or wavenumber) dependent. Three typical wavelengths, around 62 m for windsea, 168 m for intermediate waves and 342 m for swell, are selected to present the MACS comparison in detail. Comparable magnitude of SAR-measured and the simulated MACS is observed for the intermediate waves and swell, while larger simulation values are predicted for the windsea waves. Spatial distribution of MACS agrees well between these two data sets for all wavelengths with high correlation coefficients (>0.8) in most of the global ocean. One exception is in the extratropics where the quantitative difference is particularly notable. In the contrary, when comparing SAR-measured and buoys-simulated MACS, the agreement increases towards the shorter (<100 m) wavelengths. We also found that the large-scale atmospheric/oceanic features persistent on SAR images lead to the overestimate of SAR MACS at long wavelengths, which is expected to bias the wave inversion. The wave spectra retrieval performance shall advance as long as such impact is properly resolved.