Optical Quantification of Wind-Wave Breaking and Regional Variations in Different Offshore Seas Using Landsat-8 OLI Images

Abstract

Oceanic whitecaps, as indicators of increased air–sea exchange, can be effectively captured by Landsat-8 Operational Land Imager (OLI) images with a 30-m spatial resolution. This study used a new adaptive iterative triangle algorithm, which was applied to 400 OLI images synchronized with National Data Buoy Center-measured wind speeds, covering the different offshore areas of the United States over the last ten years to automatically extract whitecap-affected pixels. By integrating radiative transfer equations, we calculated the whitecap coverage (W), determined that a 4 km window size is optimal for calculating W, and established a whitecap coverage-sea surface wind speed model. A sliding window method was used to achieve high-resolution (100 m) large-area sea surface wind speed estimations. More importantly, this study provides new insights into the impact of different wind and wave conditions on W and regional variations in the whitecap coverage-sea surface wind speed model from an optical satellite perspective, which can effectively quantify the wind-wave breaking and distinguish the regional variations of them in different offshore seas. By comparing with 10-m resolution data from the Sentinel-2 Multi-Spectral Instrument, we further clarified the impact of spatial resolution on the selection of methods for calculating W, revealing scale effects in optical remote sensing of whitecap detection and proposing corresponding W calculation strategies. These results demonstrate the potential of high-resolution optical remote sensing for monitoring whitecaps, estimating sea surface winds and studying air–sea interactions.