Ocean color and biogeochemistry (CBIOMES)
Completed projectProject start: July 2017 | Project end: June 2022
Funder: US Simons Foundation
Principal Investigator: Dr Shubha Sathyendranath
Other participants from PML: Dr Bror Jonsson, Dr Glen Tarran, Dr Marie-Fanny Racault
Earth observation of ocean color remains our only window into the pelagic ecosystem at synoptic scales. It is a rich source of data, and chlorophyll concentration is the principal product, which provides valuable information on how the light from the sun (the energy source for the entire ecosystem) is coupled to the marine biota through the pigments contained in phytoplankton.
The absorbed energy is used by phytoplankton to produce organic carbon (marine primary production). We can combine light at the sea surface (another product available routinely using satellite data), with chlorophyll concentration from ocean color, to estimate marine primary production at the global scale, using models of light penetration, and photosynthesis.
The growing list of satellite products includes phytoplankton functional types and phytoplankton size distribution. It is important to recognize that these products are not raw data. We arrive at them by combining various models with the satellite data on spectral radiance at multiple wavelengths in the visible domain, detected at the level of the satellite. Often, these models are different from, and employ different assumptions from, what is done by ecosystem models.
In this five year $1.25m project, funded through a grant from the US Simons Foundation as part of its Collaboration on Computational Biogeochemical Modeling of Marine Ecosystems (CBIOMES) programme we will develop or improve novel satellite-based products, including phytoplankton functional types, particulate organic carbon, photosynthesis-irradiance parameters and phytoplankton carbon. These products, along with more standard products such as chlorophyll concentration and marine primary production, will form part of the CBIOMES data atlas. They will be used for comparison with ecosystem model outputs, and in data assimilation.