Meteo-marine parameters for highly variable environment in coastal regions from satellite radar images

Abstract

The German Bight of the North Sea is the area with highly variable sea state conditions, intensive ship traffic and with a high density of offshore installations, e.g. wind farms in use and under construction. Ship navigation and the docking on offshore constructions is impeded by significant wave heights HS>1.3m. For these reasons, improvements are required in recognition and forecasting of sea state HS in the range 0–3m. Thus, this necessitates the development of new methods to determine the distribution of meteo-marine parameters from remote sensing data with an accuracy of decimetres for HS. The operationalization of these methods then allows the robust automatic processing in near real time (NRT) to support forecast agencies by providing validations for model results.A new empirical algorithm XWAVE_C (C=coastal) for estimation of significant wave height from X-band satellite-borne Synthetic Aperture Radar (SAR) data has been developed, adopted for coastal applications using TerraSAR-X (TS-X) and Tandem-X (TD-X) satellites in the German Bight and implemented into the Sea Sate Processor (SSP) for fully automatic processing for NRT services.The algorithm is based on the spectral analysis of subscenes and the model function uses integrated image spectra parameters as well as local wind information from the analyzed subscene. The algorithm is able to recognize and remove the influence of non-sea state produced signals in the Wadden Sea areas such as dry sandbars as well as nonlinear SAR image distortions produced by e.g. short wind waves and breaking waves. Also parameters of very short waves, which are not visible in SAR images and produce only unsystematic clutter, can be accurately estimated. The SSP includes XWAVE_C, a pre-filtering procedure for removing artefacts such as ships, seamarks, buoys, offshore constructions and slicks, and an additional procedure performing a check of results based on the statistics of the whole scene.The SSP allows an automatic processing of TS-X images with an error RMSE=25cm and Scatter Index SI=20% for total significant wave height HS from sequences of TS-X StripMap images with a coverage of ∼30km×300km across the German Bight. The SSP was tuned spatially with model data of the German Weather Service’s (DWD) CWAM (Coastal WAve Model) with 900m horizontal resolution and tuned in situ with 6 buoys located in DWD model domain in the German Bight. The collected, processed and analyzed data base for the German Bight consists of more than 60 TS-X StripMap scenes/overflights with more than 200 images since 2013 with sea state acquired in the domain HS=0–7m with a mean value of 1.25m over all available scenes at buoy locations.The paper addresses the development and implementation of XWAVE_C, and presents the possibilities of SSP delivering sea state fields by reproducing local HS variations connected with local wind gusts, variable bathymetry and moving wind fronts under different weather conditions.