| Summary: | The Synthetic Aperture Radar (SAR) onboard the European Satellite ERS-2 is operated in wave-mode over the global oceans whenever no image-mode acquisition (100 x 100km) is requested. Conventionally image spectral information from these (5x10km) wavemode data is delivered as an ESA product, the UWA 2D spectra, to measure ocean waves over the global oceans in real time. The image spectra are used together with first guess information to derive two dimensional ocean wave spectra and to assimilate these into ocean wave models in order to improve ocean wave forecast. The original 5 km x 10 km synthetic aperture radar (SAR) images that contain information on a variety of additional geophysical parameters like sea ice parameters, sea surface features, wind speed and direction, and individual ocean wave parameters were not stored for further investigation. In the scope of the project Wave Atlas, ESA provided a two years wave-mode dataset of ERS-2 SAR raw data, mainly collected during 1999 and 2000, which was reprocessed to single-look-complex imagettes at DLR using the BSAR processor. The processed dataset contains daily typically between 1300 and 1500 images of 10 km by 5 km size from all global oceans. In this study the data were used for a statistical evaluation resulting in global ocean maps of different basic image parameters like,e.g., mean radar cross section and its standard deviation, the modulation depth and the image inhomogeneity. From these image parameters oceanic parameters like significant wave height, mean period and their respective regional and temporal variability during the seasons of the year are derived using the empirical algorithms CWIND1.0 and CWAVE1.0 [1] and Schulz-Stellenfleth et al, this issue. The reprocessing of wave mode data is planned to be extended to the full lifetime of ERS-1 and ERS-2, which spans at least the time period of 1991-2006 as an ESA product. This will allow the derivation of wave climatologies on a decadal basis in particular enabling the analysis of climate trends. As ...
|
|---|