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Sea surface temperature retrieval from MSG/SEVIRI data in the Baltic Sea area

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The aim of the paper was to confirm the proposition that the classical SST algorithms MCSST and NLSST originally prepared for AVHRR data could also be used for Meteosat/SEVIRI data with satisfactory accuracy in the mid-latitude region, where the spatial resolution is about 7x7 km. The research was performed in the southern Baltic Sea (between 13°E 53°N and 21°E 58°N). Data were collected in all the seasons of 2007. The coefficients were found by means of regression analysis. SSTs determined on the basis of AVHRR data were used in the regression analysis instead of in situ data. A set of paired AVHRR and SEVIRI images spaced no more than 8 minutes apart were compared. The results show that the method is capable of producing sea surface temperatures with a statistical error (standard deviation) of 1°C.
Słowa kluczowe
Czasopismo
Rocznik
Strony
331--344
Opis fizyczny
bibliogr. 17 poz., fot., tab., wykr.
Twórcy
autor
autor
  • Institute of Oceanography, University of Gdańsk, al. Marszałka Piłsudskiego 46, PL-81-378 Gdynia, Poland, oceak@univ.gda.pl
Bibliografia
  • 1.Borgne P., Legendre G., Marsouin A., 2006, Operational SST retrieval from MSG/SEVIRI data, Proc. 2006 EUMETSAT Conf., Helsinki, Finland.
  • 2.Derrien M., Farki B., Harang L., Le Gléau H., Noyalet A., Pochic D., Sairouni A., 1993, Automatic cloud detection applied to NOAA-11/AVHRR imagery, Remote Sens. Environ., 46 (3), 246-267.
  • 3.DerrienM., Le Gléau H., 2005, MSG/SEVIRI cloud mask and type from SAFNWC, Int. J. Remote Sens., 26 (21), 4707-4732.
  • 4.EUMETSAT, 2007, Cloud detection for MSG - Algorithm theoretical basis document, Vol. 2, EUM/MET/REP/07/0132.
  • 5.Karlsson K.-G., 1996, Cloud classification with the SCANDIA model, SMHI Rep. Meteorol. Climatol. No. 67.
  • 6.Krężel A., Ostrowski M., Szymelfenig M., 2005, Sea surface temperature distribution during upwelling along the Polish Baltic coast, Oceanologia, 47 (4), 415-432.
  • 7.Levizzani V., Schmetz J., Lutz H. J., Kerkmann J., Alberoni P.P., Cervino M., 2001, Precipitation estimations from geostationary orbit and prospects for METEOSAT Second Generation, Meteorol. Appl., 8 (1), 23-41.
  • 8.Li X., Pichel W., Clemente-Colon P., Krasnopolsky V., Sapper J., 2001, Validation of coastal sea and lake surface temperature measurements derived from NOAA/AVHRR data, Int. J. Remote Sens., 22 (7), 1285-1303.
  • 9.Lutz H. J., 1999, Cloud processing for Meteosat Second Generation, EUMETSAT Tech. Mem. No. 4.
  • 10.Romaguera M., Sobrino J.A., Olesen F.-S., 2006, Estimation of sea surface temperature from SEVIRI data: algorithm testing and comparison with AVHRR products, Int. J. Remote Sens., 27 (22), 5081-5086.
  • 11.Rossow W. B., Garder L.C., 1993a, Cloud detection using satellite measurements of infrared and visible radiances for ISCCP, J. Climate, 6 (12), 2341-2369.
  • 12.Rossow W.B., Garder L.C., 1993b, Validation of ISCCP cloud detections, J. Climate, 6 (12), 2370-2393.
  • 13.Rossow W.B., Mosher F., Kinsella E., Arking A., Desbois M., Harrison E., Minnis P., Ruprecht E., Seze G., Simmer C., Smith E., 1985, ISCCP cloud algorithm intercomparison, J. Clim. Appl. Meteorol., 24 (9), 877-903.
  • 14.Saunders R.W., Kriebel K.T., 1988, An improved method for detecting clear sky and cloudy radiances from AVHRR data, Int. J. Remote Sens., 9 (1), 123-150.
  • 15.Schmetz J., Govaerts Y., KőnigM., Lutz H.-J., Ratier A., Tjemkes S., 2002, A short introduction to Meteosat Second Generation (MSG), EUMETSAT.
  • 16.Valiente J.A., Niclos R., Barbera M. J., Estrela M. J., 2007, Analysis of the SST Split-Window Equation using the synergy between Meteosat Second Generation and NOAA polar satellites, Proc. 2007 EUMETSAT Conf., Amsterdam, The Netherlands.
  • 17.Walton C.C., Pichel W.G., Sapper J.F., May D.A., 1998, The development and operational application of nonlinear algorithms for the measurement of sea surface temperatures with the NOAA polar-orbiting environmental satellites, J. Geophys. Res., 103 (C12), 27999-28012.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS8-0003-0010
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