Estimation of Two-dimensional Ocean Wave Spectra from Envisat Asar Wave Mode Data Using a Maximum a Posteriori Approach

Two-dimensional ocean wave spectra are measured from ENVISAT ASAR wave mode cross spectra on a global scale. The measurement is performed using a parametric retrieval scheme, which makes use of prior information taken from numerical wave models. The Partition Rescale and Shift algorithm (PARSA) is based on a partitioning technique, which splits an a prior wave spectrum into its wave system components. Integral parameters of these systems, such as mean direction, mean wavelength, waveheight, and directional spreading are then adjusted iteratively to improve the consistency with the SAR observation. The method takes into account the full nonlinear SAR imaging process and uses a maximum a posteriori approach, which is based on statistical model quantifying the errors of the SAR imaging model, the SAR measurement, and the prior wave spectra. The method is applied to a global data set of ENVISAT ASAR data acquired during the CAL/VAL phase. The benefit of cross spectra compared to conventional symmetric image spectra is demonstrated.