|Paper title||Modeling of phytoplankton primary production in the Greenland Sea using satellite data|
|Form of presentation||Poster|
The aim of work is evaluation phytoplankton’s influence on the carbon cycle, oxygen concentration, and ocean dwellers food web in the Greenland Sea.
There are several tasks to achieve our goal: 1) to study the interaction between chlorophyll and physical properties of the sea water; 2) to determine seasonal cycle of spatial pattern and vertical profile of phytoplankton; 3) to estimate primary production.
To begin with, the Arctic waters are quite unstable in terms of sea ice thickness, open water area, research accessibility, and, moreover, are likely to face ice-free summers in the near future. As a result, these changes provide changes of the light absorbance, nutrient distribution and phytoplankton seasonality. And yet, it is still unknown if it decreases or increases phytoplankton primary production in the Greenland Sea. There is a lack of field data, hence, satellite data provide an alternative.
Phytoplankton are responsible for releasing half of the World’s oxygen and over 90% of marine primary production. Our work combines satellite and field data to investigate seasonal cycle, variability and productivity of phytoplankton in the Greenland Sea (Fram Strait), and apply modelling techniques to estimate primary production of the area.
Satellite HERMES GlobColor data were processed by MatLab/Python. Field data was used to recover Gaussian coefficients in order to apply them to the satellite data, what gives us possibility to implement depth profiles and establish Euphotic depth for every data cell.
From the field data from the Fram Strait’s 2021 RV Kronprinz Haakon summer cruise chlorophyll-a, light absorbance by particulates and primary production were measured. Using remote sensing data of chlorophyll concentration, sea temperature and photosynthetically available radiation, we were able to obtain modelled estimations of primary production. Further, field and satellite data primary production estimations were compared.
We plan that our primary production estimates will be used for validation of other biogeochemical models.