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Sea state in the Baltic Sea from space-borne high-resolution synthetic aperture radar imagery

Rikka, Sander, Pleskachevsky, Andrey, Uiboupin, Rivo, Jacobsen, Sven
International journal of remote sensing 2018 v.39 no.4 pp. 1256-1284
algorithms, correlation, data analysis, islands, models, remote sensing, satellites, spectral analysis, storms, synthetic aperture radar, wind speed, Atlantic Ocean, Baltic Sea, Baltic States, North Sea
In this work, remote sensing synthetic aperture radar (SAR) data from X-band TerraSAR-X and TanDEM-X (TS-X and TD-X) satellites have been used to adopt the algorithms for estimating sea state parameters in the specific condition of the Baltic Sea with archipelago islands and where short steep sea state dominates. Since the moving targets can be defocused and shifted in SAR images, sea state consisting of short windsea waves with strong local orbital velocities and wave breaking needs additional effort for accurate estimation of the total significant wave height that consists of swell and windsea parts. The XWAVE_C algorithm, developed for the North Sea, where the long swell waves coming from the Atlantic Ocean are present during storms, was further enhanced for the short steep windsea which dominates under ordinary storm conditions in the Baltics. For the empirical XWAVE_C model function, based on the spectral analysis of subscenes as well as on local wind information, an additional term was incorporated for assessment the minimal windsea significant wave height by applying JONSWAP wave spectra. A term to compensate spectral distortions triggered by windsea waves moving in SAR flight direction has also been introduced. In total, 95 TS-X/TD-X StripMap scenes between 2012 and 2017 were acquired in Eastern Baltic Sea, processed and analysed. The wave height results from SAR images were compared with collocated in situ data from 11 available buoys. The analysed data include both high and low windsea conditions. The comparison of SAR-derived wave heights with measured wave heights shows high agreement with a correlation coefficient r of 0.88. The wind speed, estimated from SAR images, was compared to measurements from 14 collocated in situ stations, yielding a high agreement with an r value of 0.90. This article is focused on the algorithm developments; however, it is also the first study of sea state retrieval in the Baltic Sea using high-resolution satellite-based techniques. The results show the local variability in the wave fields connected to atmospheric features. The observed local wave height can increase by 1–2 m in kilometre-size cells that are accompanied by wind gusts. The developed algorithms are installed in the German Aerospace Center’s (DLR) ground station Neustrelitz and can also be used in near-real-time.