Beyond a Single Look Azimuth: A Composite Approach to Directional Wave Spectra Retrieval from Coastal X-Band Radar
Remote sensing systems, and X-band marine radar (MR) specifically, enable the acquisition of directional wave spectra (DWS) over a wide spatial coverage by processing backscatter images. It has been shown that the MR look azimuth has a significant impact on the accuracy of the resulting DWS. While the effect of azimuthal dependency is observed in both deep and shallow water, it becomes critical for measurements in coastal environments, where spectral properties change frequently due to wave refraction, reflection, and dissipation. In this study, shore-based MR data are used to process DWS and integrated wave parameters across different wave regimes. The dependence of the DWS uncertainties on the look azimuth is evaluated via comparison with concurrent Acoustic Doppler Current Profiler (ADCP) measurements. We propose a retrieval strategy that composites multiple sub-images sampled at different look azimuths along a common isobath, so that every window captures the same stage of wave shoaling, for a more accurate evaluation of DWS and integrated wave parameters. The approach assumes an alongshore-uniform bathymetry, a condition met at the present site and common to gently sloping sandy coasts, and its applicability to irregular shorelines is considered in the discussion. The developed composite approach enhances the ability of the MR to accurately resolve sea-state directionality even in the case of multiple interacting wave systems. Cross-validation against the ADCP shows that the retrieved mean wave direction can differ by up to 30 between extreme look azimuths, and that the composite scheme recovers directionality with the best-balanced error metrics across the tested methods. These results argue against reliance on any single MR window for coastal directional monitoring. This advancement is essential for coastal engineering applications, as even directional misinterpretations of a few degrees can significantly alter the estimates of longshore sediment transport.
Authors
- Yaron Toledo (ORCID: https://orcid.org/0000-0003-0025-9509)
- Vika G. Grigorieva (ORCID: https://orcid.org/0000-0002-5138-8450)
- Nir Haim (ORCID: https://orcid.org/0000-0002-1748-5820)
Institutions
- Tel Aviv University (IL)
Publication Details
- Journal
- Remote Sensing
- Published
- 2026-10-19
- DOI
- https://doi.org/10.3390/rs18203592
- Primary Topic
- Ocean Waves and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.00