Abstract
This paper describes two algorithms for the retrieval of high-resolution wind and wave fields from radar-image sequences acquired by a marine X-band radar. The wind-field retrieval algorithm consists of two parts. In the first part, wind directions are extracted from wind-induced streaks, which are approximately in line with the mean surface wind direction. The methodology is based on the retrieval of local gradients from the mean radar backscatter image and assumes the surface wind direction to be oriented normal to the local gradient. In the second part, wind speeds are derived from the mean radar cross section. Therefore, the dependence of the radar backscatter on the wind vector and imaging geometry has to be determined. Such a relationship is developed by using neural networks (NNs). For the verification of the algorithm, wind directions and speeds from nearly 3300 radar-image sequences are compared to in situ data from a colocated wind sensor. The wave retrieval algorithm is based on a methodology that, for the first time, enables the inversion of marine radar-image sequences to an elevation-map time series of the ocean surface without prior calibration of the acquisition system, and therefore, independent of external sensors. The retrieved ocean-surface elevation maps are validated by comparison of the resulting radar-derived significant wave heights, with the significant wave heights acquired from three colocated in situ sensors. It is shown that the accuracy of the radar-retrieved significant wave height is consistent with the accuracy of the in situ sensors.
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