DETERMINATION OF PHYTOPLANKTON CONCENTRATIONS FROM SPACE-BORNE SPECTROSCOPIC MEASUREMENTS
Since its launch into orbit on board of the ENVISAT spacecraft on March 1st, 2002, the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) continuously measures transmitted, reflected and scattered solar radiation from 220 - 2380 nm at moderate spectral resolution (0,2 n...
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| Autores principales: | , , , , , |
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| Lenguaje: | English |
| Publicado: |
Facultad de Ciencias Naturales y Oceanográficas, Universidad de Concepción
2004
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| Acceso en línea: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-65382004000300039 |
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| Sumario: | Since its launch into orbit on board of the ENVISAT spacecraft on March 1st, 2002, the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) continuously measures transmitted, reflected and scattered solar radiation from 220 - 2380 nm at moderate spectral resolution (0,2 nm - 1,5 nm). Global maps of atmospheric trace gas distributions are derived from these measurements using the Differential Optical Absorption Spectroscopy (DOAS) technique. Although SCIAMACHY is primarily an atmospheric mission, part of the detected solar radiation penetrates the ocean surface and picks up an absorption signal from molecular species in sea water. In the visible part of the measured spectra, spectral features of chlorophyll can clearly be identified. We show that the spectral signature of chlorophyll in SCIAMACHY spectra can be used to infer column densities of phytoplankton abundance. We present first results obtained in a case study of a phytoplankton bloom event off the West African coast in March 2003 and compare the results with ocean colour measurements of the SeaWifs instrument. While the spatial resolution of the SCIAMACHY instrument (60 x 30 km) is coarse in comparison with ocean colour instruments, we provide evidence that the detected spectral signatures have the potential of discriminating between different phytoplankton species. Finally, we investigate a method to infer chlorophyll concentration by exploiting the additional information from effective water penetration depth, which is obtained from the DOAS analysis of liquid water absorption |
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