ALBERT

Description: Quantitative distributions of major functional PFTs of the world ocean improve the understanding of the role of marine phytoplankton in the global marine ecosystem and biogeochemical cycles. Chl-a fluorescence gives insight on the health of phytoplankton and is related to phytoplankton biomass. In this study, global ocean color satellite products of different dominant phytoplankton functional types' (PFTs') biomass and chlorophyll fluorescence retrieved from hyperspectral satellite data using Differential Optical Absorption Spectroscopy applied to phytoplankton (PhytoDOAS) are presented (see also Bracher et al. 2009, Sadeghi et al. 2012a). Data are compared to ocean color products from multispectral sensors and application of the hyperspectral data set in studying phytoplankton dynamics are presented (Sadeghi et al. 2012b, Ying et al. 2012). Although current hyperspectral sensors have poor spatial resolution (〉30kmx30km), they are useful for the verification and improvement of the high spatially resolved multi-spectral ocean color products. Future applications of PhytoDOAS retrieval to other hyperspectral sensors and its synergistic use with information gained from multispectral ocean color sensors are proposed.

Description: The Arctic Ocean receives considerable input of terrigenous carbon supplied by the Arctic rivers. In the context of climate change and thawing permafrost in Eastern Siberia, freshwater discharge and subsequently the riverine input may increase in the future, affecting the radiation budget in the region. Here, we examine the effect of the water optically active constituents on the radiation budget of the Laptev Sea surface waters. We use a coupled atmosphere-ocean radiative transfer model (RTM), MERIS data and in situ measurements of CDOM absorption (aCDOM), total suspended matter (TSM) and chlorophyll concentration (Chla) to simulate the radiative heating. As a first step, we evaluate RTM simulation capabilities by implementing MERIS imaging geometry and collocating every in-situ station to MERIS data to simulate the top of the atmosphere radiance. Additionally, we demonstrate the significant influence of CDOM and TSM on the energy budget of the Laptev Sea surface waters. Results show that high CDOM absorption may lead to 11.4% more absorbed energy in the surface layer (upper 2m) compared to low CDOM waters, which corresponds to an increased heating rate of about 1.3°C/day. Regarding TSM, high concentration leads to an increase of 10.6% in the absorbed energy and 1.2°C/day in the heating rate compared to low concentrations, while the impact of phytoplankton is almost negligible. As more energy is trapped in the surface, cooling occurs in the sub-surface layer (〉2m). We further examine the influence of the absorbed solar energy on the melting of sea ice and the induced surface fluxes to the atmosphere. In addition, using satellite remote sensing retrievals of aCDOM, TSM, Chla and sea surface temperature data as input to the RTM simulations, we present the spatial distribution of potential radiative heating of Laptev Sea surface waters.

Description: 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 5 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 10 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 15 study have been computed. The patterns of total phytoplankton biomass and specific dynamics of coccolithophores 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 to the compared geophysical variables. This suggests, that PhytoDOAS 20 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.

Description: Quantitative distributions of major functional PFTs of the world ocean improve the understanding of the role of marine phytoplankton in the global marine ecosystem and biogeochemical cycles. Chl-a fluorescence gives insight on the health of phytoplankton and is related to phytoplankton biomass. In this study, global ocean color satellite products of different dominant phytoplankton functional types' (PFTs') biomass and chlorophyll fluorescence retrieved from hyperspectral satellite data using Differential Optical Absorption Spectroscopy (DOAS) are presented. Global biomass distributions from 2002 -2010 of different dominant PFTs (diatoms, cyanobacteria, coccolithophores, dinoflagellates) are derived with PhytoDOAS, the currently specialized method of DOAS for deriving chl-a of PFTs from satellite data of SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Cartography) on ENVISAT (details in Bracher et al. BG 2009, Sadeghi et al. OSD 2011). Results of the global maps of PFT distribution are validated with global PFT data derived from using Hirata et al. (2011) approach of parameterizing satellite chl-a from Globcolour with collocated HPLC pigment data. In addition, SCIAMACHY monthly mean data of coccolithophore biomass in three selected oceanic regions 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 DOAS method was also adapted to detect successfully globally the filling-in of Fraunhofer Lines caused by chlorophyll fluorescence in the backscattered SCIAMACHY spectra and compared to data of fluorescence-line-height from MODIS and MERIS. The results suggest that DOAS is a valid method for retrieving PFTs and chlorophyll fluorescence from hyper-spectral measurements. Overall, DOAS products are much less dependent on a priori information than common multi-spectal ocean colour products which result from empirical and semi-analytical methods. In addition, the DOAS technique has the advantage to overcome problems with an accurate atmospheric correction encountered for the traditional multi-spectral ocean color products because only the differential signals of both atmospheric and oceanic absorbers are fitted while all other (broad-band) absorption and scattering processes are successfully approximated with an low order polynomial. Although current hyperspectral sensors have poor spatial resolution (〉30kmx30km), they are useful for the verification and improvement of the high spatially resolved multi-spectral ocean color products. Future applications of PhytoDOAS retrieval to other hyperspectral sensors and its synergistic use with information gained from multispectral ocean color sensors are proposed.

Description: Nearly ten years (July 2002 to April 2012) of SCIAMACHY data, a hyper-spectral satellite sensor on-board ENVISAT, were processed by the improved, multi-target, PhytoDOAS method to monitor the biomass of coccolithophores besides diatoms and cyanobacteria. Data have been evaluated with other coccolithphore related satellite products and modeled coccolithophore distributions derived from the NASA Ocean Biogeochemical Model. The retrieval's sensitivity was assessed by using the coupled oceanic-atmospheric radiative transfer model SCIATRAN. Temporal variations of coccolithophores were investigated using satellite data in three selected regions characterized by frequent occurrence of large coccolithophore blooms. Monthly mean data 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). In addition, the inter-annual variations of the phytoplankton bloom cycles and their maximum monthly mean values were compared in the three selected regions to the variations of the following geophysical parameters: sea-surface temperature (SST), mixed-layer depth (MLD) and surface wind speed, which are known to affect phytoplankton dynamics. PhytoDOAS data are consistent with the two other ocean color products and support the reported dependencies of coccolithophore biomass' dynamics to the compared geophysical variables. These results suggest that multi-target PhytoDOAS is a valid method for retrieving coccolithophores' biomass and for monitoring their bloom developments in the global oceans.

Description: The goal of this study was to improve PhytoDOAS, which is a new retrieval method for quantitative identification of major phytoplankton functional types (PFTs) using hyper-spectral satellite data. PhytoDOAS is an extension of the Differential Optical Absorption Spectroscopy (DOAS, a method for detection of atmospheric trace gases), developed for remote identification of oceanic phytoplankton groups. Thus far, PhytoDOAS has been successfully exploited to identify cyanobacteria and diatoms over the global ocean from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) hyper-spectral data. This study aimed to improve PhytoDOAS for remote identification of coccolithophores, another functional group of phytoplankton. The main challenge for retrieving more PFTs by PhytoDOAS is to overcome the correlation effects between different PFT absorption spectra. Different PFTs are composed of different types and amounts of pigments, but also have pigments in common, e.g. chl a, causing correlation effects in the usual performance of the PhytoDOAS retrieval. Two ideas have been implemented to improve PhytoDOAS for the PFT retrieval of more phytoplankton groups. Firstly, using the fourthderivative spectroscopy, the peak positions of the main pigment components in each absorption spectrum have been derived. After comparing the corresponding results of major PFTs, the optimized fit-window for the PhytoDOAS retrieval of each PFT was determined. Secondly, based on the results from derivative spectroscopy, a simultaneous fit of PhytoDOAS has been proposed and tested for a selected set of PFTs (coccolithophores, diatoms and dinoflagellates) within an optimized fit-window, proven by spectral orthogonality tests. The method was then applied to the processing of SCIAMACHY data over the year 2005. Comparisons of the PhytoDOAS coccolithophore retrievals in 2005 with other coccolithophore-related data showed similar patterns in their seasonal distributions, especially in the North Atlantic and the Arctic Sea. The seasonal patterns of the PhytoDOAS coccolithophores indicated very good agreement with the coccolithophore modeled data from the NASA Ocean Biochemical Model (NOBM), as well as with the global distributions of particulate inorganic carbon (PIC), provided by MODIS (MODerate resolution Imaging Spectroradiometer)- Aqua level-3 products. Moreover, regarding the fact that coccolithophores belong to the group of haptophytes, the PhytoDOAS seasonal coccolithophores showed good agreement with the global distribution of haptophytes, derived from synoptic pigment relationships applied to SeaWiFS chl a. As a case study, the simultaneous mode of PhytoDOAS has been applied to SCIAMACHY data for detecting a coccolithophore bloom which was consistent with the MODIS RGB image and the MODIS PIC map of the bloom, indicating the functionality of the method also in short-term retrievals.