New biooptical information from satellite data
In order to understand the marine phytoplankton’s role in the global marine ecosystem and biogeochemical cycles it is necessary to derive its global, in particular the distribution of major functional phytoplankton types (PFT), but also on phytoplankton physiology and its degradation products in the world oceans. Nearly all current global ocean colour products are retrieved from multi-spectral ocean colour sensors, because of their much higher spatial resolution and temporal coverage, but as well for the lack of expertise to analyze hyper-spectral datasets. The use of multi-spectral data limits the ability to differentiate among the optical imprints of different water constituents. Although phytoplankton types have different marker pigments, the differences in the spectral absorption structures are small, since they also have many pigments in common. The small number of wavelength bands and the broad band resolution of multi-spectral sensors provide only limited information on the difference of the phytoplankton absorption structures.
To get a global quantitative estimate of different PFT in the oceans, PHYTOOPTICS in in cooperation with the Institute of Environmental Physics at the University of Bremen (IUP) has adapted the technique of Differential Optical Absorption Spectroscopy (DOAS), which has been established for retrieval of atmospheric components, for the retrieval of the absorption and biomass of major phytoplankton groups (PhytoDOAS; Phytoplankton DOAS) from data of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY; SCanning Imaging absorption spectrometer for Atmospheric ChartographY onboard ENVISAT) satellite sensor. It allows the determination of the biomass of the four above mentioned different phytoplankton groups (Bracher et al. 2009 describes the retrieval of two PFT, Sadeghi et al. 2012a the improved PhytoDOAS with the retrieval of four PFT, see Figure 1 below) analytically and independent from a priori information using high spectrally resolved satellite data from SCIAMACHY. PhytoDOAS accounts in addition to atmospheric compounds also for the absorption of water itself and its optical constituents. So far, the method has only been applied (e.g. in Sadeghi et al. 2012b, Ye et al. 2012) to the hyper-spectral SCIAMACHY data (covering 2002-2012). The drawback is the coarser spatial resolution of the ground scene (30 km by 60 km) which is nonetheless acceptable for open ocean conditions. However, the coverage close to the coasts and at the high latitudes very limited. Especially at coastal sites a data product with better temporal and spatial resolution is required in order meet the data users’ needs. To tackle this short-coming, we have been funded by ESA to conduct the SynSenPFT project, we a high spatially and temporal resolved data set of phytoplankton groups from space is currently developed. Specific adaptions of PhytoDOAS to other and new hyperspectral sensors and to the Southern Ocean are focus of the DFG-Project PHYSYN where the data set will also be used to improve coupled ecosystem-ocean modelling in order to assess variability and change of PFT in this ocean.
Hyper-spectral satellite data and methods like PhytoDOAS have the potential to overcome this: the optical imprints of different “types” (terrigenous or marine) can be observed by the filling-in of Fraunhofer Lines in the hyper-spectral backscattered sun light due to the specific trans-spectral processes (Wolanin et al. 2015a, 2015b - see details in PhD project A. Wolanin), as it can be detected for inelastic scattering on water molecules (Vountas et al. 2007, Dinter et al. 2015). In addition, chl-a fluorescence provides rich source of physiological information of phytoplankton because of the inverse relationship of chl-a fluorescence and photosynthesis.
References and Publications
Bracher A., Vountas M., Dinter T., Burrows J.P., Röttgers R., Peeken I. (2009). Quantitative observation of cyanobacteria and diatoms from space using PhytoDOAS on SCIAMACHY data. Biogeosciences 6: 751-764.
Dinter T., Rozanov V., Burrows, J. P., Bracher A. (2015) Retrieving the availability of light in the ocean utilising spectral signatures of vibrational Raman scattering in hyper-spectral satellite measurements. Ocean Science11: 373-389.
Wolanin A., Rozanov V., Dinter T., Bracher A. (2015a) Detecting CDOM fluorescence using high spectrally resolved satellite data: a model study. In: G. Lohmann, H. Meggers, V. Unnithan, D. Wolf-Gladrow, J. Notholt, A. Bracher (eds.), Towards an Interdisciplinary Approach in Earth System Science, SpringerBriefs in Earth System Sciences, Springer, Heidelberg, Germany. ISBN 978-3-319-13864-0, DOI 10.1007/978-3-319-13865-7, pages 109-121
Wolanin A., Rozanov V., Noel S., Dinter T., Vountas M., Burrows J.P., Bracher A. (2015b) Phytoplankton chl-a fluorescence from hyperspectal data. Remote Sensing of Environment 166: 243-261 . doi: 10.1016/j.rse.2015.05.018
Sadeghi, A. , Dinter, T. , Vountas, M. , Taylor, B. , Peeken, I. , Altenburg Soppa, M. and Bracher, A. (2012) Improvements to the PhytoDOAS method for identification of coccolithophores using hyper-spectral satellite data. Ocean Science, 8 (6), pp. 1055-1070. doi:10.5194/os-8-1055-2012 , hdl:10013/epic.40463
Sadeghi, A. , Dinter, T. , Vountas, M. , Taylor, B. , Altenburg-Soppa, M. and Bracher, A. (2012) Remote sensing of coccolithophore blooms in selected oceanic regions using the PhytoDOAS method applied to hyper-spectral satellite data, Biogeosciences, 9 (6), pp. 2127-2143. doi:10.5194/bg-9-2127-2012 , hdl:10013/epic.39765
Sadeghi, A. , Dinter, T. , Vountas, M. , Taylor, B. and Bracher, A. (2012) Improving the PhytoDOAS method to retrieve coccolithophores using hyper-spectral satellite data. Lohmann, G. , Grosfeld, K. , Wolf-Gladrow, D. , Unnithan, V. , Notholt, J. and Wegner, A. (editors) , In: Earth System Science: Bridging the Gaps between Disciplines Perspectives from a Multi-disciplinary Helmholtz Graduate Research School, Series: SpringerBriefs in Earth System Sciences, Heidelberg, Springer, 138 p., ISBN: 978-3-642-32235-8 . doi:10.1007/978-3-642-32235-8 , hdl:10013/epic.40464
Vountas M., Dinter T., Bracher A., Burrows J. P., Sierk B. (2007) Spectral studies of ocean water with space-borne sensor SCIAMACHY using Differential Optical Absorption Spectroscopy (DOAS). Ocean Science 3: 429-440.
Ye, Y. , Völker, C. , Bracher, A. , Taylor, B. and Wolf-Gladrow, D. (2012)
Environmental controls on N2 fixation by Trichodesmium in the tropical eastern North Atlantic Ocean - A model-based study, Deep-Sea Research Part I-Oceanographic Research Papers, 64 , pp. 104-117. doi:10.1016/j.dsr.2012.01.004 , hdl:10013/epic.39337
Fig. 1: Mean chl-a conc. in March 2007 of different phytoplankton groups derived with PhytoDOAS from SCIAMACHY data. Representative photographs for each group from S. Kranz and S. Wiegmann (AWI).
Fig. 2: Light availability [photon/s/m] in the ocean in Oct 2008 from SCIAMACHY (Figure from Dinter et al. 2015)