A Dynamic Constraint Method for Retrieving Sea Surface Wind Speed Using High-Frequency Radars

Abstract

The inversion of sea surface wind speed using traditional high-frequency radar algorithms, which rely on fuzzy second-order spectral information in the sea surface echo spectrum, often suffers from low accuracy due to their sensitivity to noise. This study introduces a novel approach based on dynamic constraints, known as the dynamic constraint method (DCM), which combines traditional algorithms with additional oceanic dynamic data, such as tidal and wind-induced currents, to improve the inversion accuracy. By incorporating oceanic dynamics, the wind speed inversion process is extended from a semiempirical framework to a framework constrained by dynamic factors. DCM dynamically constrains the inversion error of the traditional algorithm by establishing a global adaptive dynamic mapping relationship between the contribution rates of the wind-induced current speed and the tidal current speed within the radar detection area. As a result, DCM can reasonably improve wind speed inversion accuracy. Sensitivity experiments have also demonstrated the fault tolerance of DCM. Furthermore, DCM successfully captures realistic spatial and temporal distribution characteristics of wind speed at a height of 10 m above the sea surface.