The higher spatial resolution (250–500 m) and bigger spectral width (20 nm) of MODIS visual ‘land’ bands are very informative for the visual identification and analysis of turbid coastal water features
compared to the spectrally narrow (10 nm) and spatially less detailed (1 km) MODIS ‘ocean’ bands (Gurova 2009). However, for the spectral analysis of these features we used normalized water leaving radiances (nLw) (Gordon & Wang 1994) and spectral diffuse attenuation coefficients of downwelling irradiance Kd_Lee (Lee et al. 2005), calculated from the ‘ocean’ bands (8–16), specially designed for such purposes. Images were processed from L1A level with Seadas 6.23 software, using the MUMM atmospheric correction algorithm Selleckchem IDH inhibitor (Ruddick et al. 2000), which is the best suited to turbid Baltic Sea waters (Woźniak et al. 2008). CDOM absorption coefficients aCDOM(400) were calculated using an empirical algorithm specially developed for the Baltic Sea and successfully validated ( Kowalczuk et al., 2005 and Kowalczuk et al., 2010). MODIS Sea Surface Temperature (SST) products were calculated with the standard algorithm implemented in Seadas 6.2 ( Brown & Minnett 1999). Wide Swath Mode images from Advanced Synthetic Aperture Radar (ASAR instrument on board the Envisat satellite)
were obtained from ESA archives. With a medium spatial resolution of 75 m pixel− 1, the ASAR WSM images, especially those obtained by multi-sensor approach, are very useful Metformin research buy for detailed spatial analysis of hydrodynamic features affecting the water surface (Gurova & Ivanov 2011). Secondly, examples of submesoscale eddies in SEB were selected from a series of measurements of sea surface currents in the marine area near the Curonian Spit (the Zelenogradsk-Rybachiy section) and the northern shore of the Sambian Peninsula, made by the coastal radar Sea Sonde CODAR system in 2006 and 2007. Two resolutions for a 30 × 30-cell grid were used in these measurements – 500 m cell− 1 and 250 m cell− 1 (Gorbatsky et al., 2007 and Babakov
et al., 2008). To analyse the wind statistics we used wind data at altitude 10 m from a coupled Ceramide glucosyltransferase sea-ice-ocean model of the Baltic Sea (BSIOM) with a spatial resolution of 1.2 nautical miles, which has been shown to provide realistic values when compared to field measurements (Rudolph & Lehmann 2006). Verification comparison of modelling data for a 6-hour average wind with measurements at point D6, located 20 km from the coast of the Curonian Spit, for a period of 92 days, showed general correspondence between the modelled data and measurements (Figure 2). Therefore, the wind statistics in this paper (Table 1 (see page 639) and wind diagrams in Figure 7 (see page 644)) were obtained using BSIOM data.
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