Estimating phytoplankton size classes from their inherent optical properties

Phytoplankton plays a massive role in the regulation of greenhouse gases, with different functional types affecting the carbon cycle differently. The most practical way of synoptically mapping the ocean’s phytoplankton communities is through remote sensing with the aid of ocean-optics algorithms. This thesis is a study of the relationships between the Inherent Optical Properties (IOPs) of the ocean and the physical constituents within it, with a special focus on deriving phytoplankton size classes. Three separate models were developed, each focusing on a different relationship between absorption and phytoplankton size classes, before being combined into a final ensemble model. It was shown that all of the developed models performed better than the baseline model, which only estimates the mean values per size class, and that the results of the final ensemble model is comparable to, and performs better than, most other published models on the NOMAD dataset