Synthetic Aperture Radar Wave Mode Research Articles

Statistical analysis and intercomparison of WAM model data with global ERS‐1 SAR wave mode spectral retrievals over 3 years

Ocean wave spectra were retrieved from a set of ERS‐I synthetic aperture radar (SAR) wave mode (SWM) spectra between January 1993 and December 1995. An assessment is given of the SWM data quality and the retrieval performance as well as the operational feasibility of the retrieval algorithm. Sensitivity studies are performed to demonstrate the weak residual dependence of the retrieval on the first‐guess input spectrum. The mean spectral parameters of the SWM retrievals are compared with spectral parameters from collocated wave model (WAM) spectra. The time series of SWM‐retrieved and WAM‐derived monthly mean significant wave heights Hs in various ocean basins show good overall agreement but with a small systematic underestimation of Hs by the WAM. A decomposition of the wave spectra into wind sea and swell reveals an average 10% overprediction of the wind sea by the WAM while swell is underpredicted by 20–30%. The positive wind‐sea bias exhibits no clear wave height dependence, while the negative swell bias decreases with swell wave height. This could be due to a too strong damping in the WAM at low frequencies. Detailed regional investigations point to the existence of smaller‐scale phenomena, which may not be adequately reproduced by the WAM at the present resolution of the wind forcing. Finally, an intercomparison is made of the observed and modeled azimuthal cutoff length scales, and global distributions are investigated. Ratios of the observed azimuthal cutoff wavenumber to the mean azimuthal wavenumber component indicate that about 75% of the swell can be directly resolved by the SAR, while about 70% of the wind sea lies at least partially beyond the cutoff.

The effect of assimilating ERS‐1 fast delivery wave data into the North Atlantic WAM model

The launch of the European ERS satellites has provided a new source of wave information that is particularly suitable for use in improving wave forecasts in the open ocean. We have implemented and tested a simple system for assimilating corrections to model wave fields produced by the WAM model, where the corrections are derived from inverted synthetic aperture radar (SAR) image spectra from ERS‐1. Corrections are applied to significant wave height, mean period and direction for wave modes that are detectable in both the model and the SAR data. The system has been tested in a storm situation and in moderate conditions using buoy data and altimeter data, as well as SAR observations for verification. Overall, it is demonstrated that the net effect of assimilating SAR data is beneficial but very small. The small impact is due at least partly to relatively small spatial and temporal coverage of the SAR wave mode data. Locally larger impacts were found in the storm situation in individual cases where SAR observations were collocated with independent buoy observations.

An optimal interpolation scheme for the assimilation of spectral wave data

An optimal interpolation scheme for assimilating two‐dimensional wave spectra is presented which is based on a decomposition of the spectrum into principal wave systems. Each wave system is represented by three characteristic parameters: significant wave height, mean propagation direction, and mean frequency. The spectrum is thereby reduced to a manageable number of parameters. From the correction of the wind‐sea system a correction of the local wind is derived. A 2‐month test of the system using wave spectra retrieved from ERS 1 synthetic aperture radar wave mode data in the Atlantic yielded consistent corrections of winds and waves. However, the corrected wind data alone, although valuable in identifying wind errors in critical high wind speed regions, are too sparsely distributed in space and time to be used in isolation and need to be combined with other data in an atmospheric data assimilation scheme. This emphasizes the need for the development of combined wind and wave data assimilation schemes for the optimal use of satellite wind and wave data.