Arctic marine primary production with respect to changes in sea ice cover
The influence of the rapid changes in sea ice coverage on Arctic primary production has not been studied enough so far due to the lack of sufficient in situ measurements and gaps in satellite data in high latitudes.
To study this in more detail we want to investigate the interaction between the changing sea ice coverage, other physical parameters (e.g. sea surface temperature, wind field/ocean currents) and the biomass and primary production of phytoplankton in the Arctic Ocean by using in-situ, remote sensing and modeling techniques.
Primary production (PPR) will be calculated using two global PPR models. PPR estimates obtained from Behrenfeld and Falkowski (1997) model will be compared to those calculated using Antoine and Morel (1996) and Antoine et al (1996) method. These models use PAR (Photosynthetically Active Radiation), SST (Sea Surface Temperature), CHL (CHLorophyll-a) and climatology of MLD (Mixed Layer Depth) as the main input parameters. Phytoplankton biomass data will be taken for the total CHL from the merged GlobColour MERIS-SeaWiFS-MODIS product and for different Phytoplankton Functional Types (PFT) from SCIAMACHY (according to Bracher et al. 2009). In order to choose the most appropriate PAR dataset for the Arctic, it is planned to compare MERIS and SeaWIFS PAR products. SST values will be taken from MODIS.
After the Arctic CHL, PAR and PPR satellite-based datasets are ready, it is planned to validate them with in situ data from various RV POLARSTERN cruises. In situ measurements, besides being used as ground truth for satellite data, will as well help to illucidate regional features of the Arctic waters. The usual approach while working with the global primary production models is to obtain the parameters that depend on the vertical structure of the waters and strongly vary regionally (such as MLD) from the satellite measurements. In our research it is planned to use in-situ measurements (chlorophyll-a vertical profiles, phytoplankton species composition, absorption by particulates and CDOM (Coloured Dissolved Organic Matter), PAR and oth.) to estimate these parameters. Chlorophyll-a and primary production values will be compared to those derived from the coupled ocean-ice-ecosystem model by Losch et al. (2008) to give suggestions for improving it for Arctic Ocean application. Results of the comparison shall determine whether the model spatial resolution is sufficient to capture the variability observed by satellite (i.e. the most comprehensive validation data currently available). Spatial patchiness in the satellite data will be assessed and compared with the range in model data at all available resolutions.
Afterwards the temporal variability of the physical factors, such as wind speed (from QuikSCAT), sea ice cover (from the PHAROS group of University of Bremen), sea surface temperature (from MODIS) will be studied using e. g. wavelet transform analysis. Cross correlation analysis will be applied to investigate if the observed phytoplankton biomass and primary production variability can be related to the regional climate variability and large-scale climatic conditions.
Figure 1. Satellite data-based Arctic primary production and sea ice distribution for September 2003.
Top left: PPR retrieved using Behrenfeld and Falkowski (1997) model [3]; Top right: PPR retrieved using Antoine, André and Morel (1996) model [1,2]; Bottom left: Difference between two maps on the top; Bottom right: Sea ice concentration retrieved by PHAROS group of University of Bremen.
PhD student: Alexandra Cherkasheva, POLMAR stipend.
Supervisors: Prof. Dr. J. Notholt (Remote Sensing Group, IUP)
Dr. Astrid Bracher (PHYTOOPTICS group, AWI - part of the group at IUP)
References:
1. Antoine, D. and A. Morel (1996). Oceanic primary production: I. Adaptation of a spectral light-photosynthesis model in view of application to satellite chlorophyll observations, Global Biogeochemical Cycles, 10, 43-55.
2. Antoine, D., André J.M. and A. Morel (1996). Oceanic primary production: II. Estimation at global scalefrom satellite (Coastal Zone Color Scanner) chlorophyll, Global Biogeochemical Cycles, 10, 57-69.
3. Behrenfeld, MJ, PG Falkowski; Photosynthetic rates derived from satellite-based chlorophyll concentration, Limnology and Oceanography, vol. 42, 1-20, 1997
4. 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
5. Losch, M., M. Schröter, S. Hohn, & C. Völker; High-resolution modelling of phytoplankton distribution and adaptation, NIC Symposium 20-21 February 2008, Forschungszentrum Jülich; proceedings (NIC series 39)/ organized by John von Neumann Institute for Computing. Ed. by Gernot Münster, Forschungszentrum Jülich, 289-296, 2008.
