Quantitative observation of cyanobacteria and diatoms from space using PhytoDOAS on SCIAMACHY data.

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Bracher, A. , Vountas, M. , Dinter, T. , Burrows, J. P. , Röttgers, R. and Peeken, I. (2008): Quantitative observation of cyanobacteria and diatoms from space using PhytoDOAS on SCIAMACHY data. , Biogeosciences Discussion, 5 , pp. 4559-4590 .
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In this study the technique Differential Optical Absorption Spectroscopy (DOAS) has been adapted for the retrieval of the absorption and biomass of two major phytoplankton groups (PhytoDOAS) from data of the satellite sensor Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). SCIAMACHY measures back scattered solar radiation in the UV-Vis-NIR spectral region with a high spectral resolution (0.2 to 1.5 nm). In order to identify phytoplankton absorption characteristics in SCIAMACHY data in the range of 430 to 500 nm, phytoplankton absorption spectra measured in-situ during two different RV "Polarstern" expeditions were used. The two spectra have been measured in different ocean regions where different phytoplankton groups (cyanobacteria and diatoms) dominated the phytoplankton composition. Results show clearly different absorption characteristics of the phytoplankton groups in the SCIAMACHY spectra. Globally distributed pigment concentrations for these characteristic phytoplankton groups for two monthly periods (FebruaryMarch 2004 and OctoberNovember 2005) were derived from these differential absorptions by including the information of the sensor's optical paths within the water column (i.e. light penetration depth) according to Vountas et al. (2007) derived from DOAS fits of inelastic scattering. The satellite retrieved information on cyanobacteria and diatoms distribution matches well the concentrations measured at collocated water samples with HPLC technique and concentrations derived from the global model analysis with the NOBM model (Gregg et al., 2003; Gregg and Casey, 2007). Identifying quantitative distribution of key phytoplankton groups from space allow to distinguish various biogeochemical provinces and will be of great importance for the global modelling of marine ecosystem and biogeochemical cycles addressing climate changes in the oceanic biosphere.

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