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| Titel |
Remote sensing of coccolithophore blooms in selected oceanic regions using the PhytoDOAS method applied to hyper-spectral satellite data |
| VerfasserIn |
A. Sadeghi, T. Dinter, M. Vountas, B. Taylor, M. Altenburg-Soppa, A. Bracher |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 9, no. 6 ; Nr. 9, no. 6 (2012-06-14), S.2127-2143 |
| Datensatznummer |
250007122
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| Publikation (Nr.) |
 copernicus.org/bg-9-2127-2012.pdf |
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| Zusammenfassung |
| In this study temporal variations of coccolithophore blooms are investigated
using satellite data. Eight years (from 2003 to 2010) of data of SCIAMACHY, a
hyper-spectral satellite sensor on-board ENVISAT, were processed by the
PhytoDOAS method to monitor the biomass of coccolithophores in three selected
regions. These regions are characterized by frequent occurrence of large
coccolithophore blooms. The retrieval results, shown as monthly mean time
series, were compared to related satellite products, including the total
surface phytoplankton, i.e. total chlorophyll a (from GlobColour merged
data) and the particulate inorganic carbon (from MODIS-Aqua). The
inter-annual variations of the phytoplankton bloom cycles and their maximum
monthly mean values have been compared in the three selected regions to the
variations of the geophysical parameters: sea-surface temperature (SST),
mixed-layer depth (MLD) and surface wind-speed, which are known to affect
phytoplankton dynamics. For each region, the anomalies and linear trends of
the monitored parameters over the period of this study have been computed.
The patterns of total phytoplankton biomass and specific dynamics of
coccolithophore chlorophyll a in the selected regions are discussed in
relation to other studies. The PhytoDOAS results are consistent with the two
other ocean color products and support the reported dependencies of
coccolithophore biomass dynamics on the compared geophysical variables. This
suggests that PhytoDOAS is a valid method for retrieving coccolithophore
biomass and for monitoring its bloom developments in the global oceans.
Future applications of time series studies using the PhytoDOAS data set are
proposed, also using the new upcoming generations of hyper-spectral satellite
sensors with improved spatial resolution. |
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