From raw ERS wavemode data, complex SAR images of size 5 km x 10 km - so called imagettes - are computed using DLR's BSAR processor. Being collected over oceans every 200 km along the orbit, imagettes provide a patchy daily global coverage of the world's oceans. This paper presents DLR's processing chain and results for a three week testing period covering the detection of ocean slicks and sea ice, the use of cross spectra to derive wave spectra over open ocean, the detection of one or several ocean wave systems together with its wave length and its propagation direction, and the estimation of single wave heights.
In sea ice covered areas, statistical parameters derived from the SAR are well correlated to physical measures such as the ice deformation energy and ridge frequency.
Over ice free areas, comparisons between the SAR results and the ECMWF analysis as well as model results show good agreement in most cases. Observed deviations between SAR measurements and model results are discussed. As a new application of wave mode data statistics are presented on the occurence of extreme waves.
As soon as ESA will make available the daily global raw wavemode data for the whole lifetime of ERS-1 and ERS-2, it will be possible to DLR to derive unique statistics on sea ice and wave parameters for a period of at least 10 years, which may be even extended by the use of ENVISAT data in future. Together with near surface wind fields which are also derivable from the imagettes, this work will be of extreme use for climate research applications.
An algorithm is introduced, which is designed to retrieve
high-resolution wind fields from C-band synthetic aperture radars
(SAR) operating at both vertical and horizontal polarization. The
wind directions are extracted from wind-induced streaks, which are
approximately in line with the mean wind direction near to the
ocean surface. The wind speeds are derived from the normalized
radar cross section (NRCS) and image geometry of the calibrated
SAR images, together with the local wind direction retrieved from
the image. Therefore the semi empirical C-band model CMOD4, which
describes the dependency of the NRCS on wind and image geometry,
is used. The CMOD4 was originally developed for the scatterometer
of the European remote sensing satellites ERS-1 and 2 operating at
C-band with vertical polarization. Consequently CMOD4 requires
modification for horizontal polarization, which is performed by
considering the polarization ratio. To verify the algorithm, wind
fields were computed from the European satellites ERS-1/2 and
ENVISAT SAR as well as the Canadian satellite RADARSAT-1 and
compared to results from numerical models and a scatterometer.