POSTER Session 2

COUPLING ECOLOGICAL CONCEPTS WITH AN OCEAN-COLOR MODEL: INVERSION MODELING

Understanding how phytoplankton respond to climate change is a major question in ocean science, and ocean-color remote sensing is our only means of monitoring phytoplankton in the surface ocean over large temporal and spatial scales. However, developing ocean-color algorithms for climate change studies requires addressing issues of ambiguity in the ocean-color signal. For example, for the same chlorophyll-a concentration (Chl-a), the color of the ocean can be different depending on the type of phytoplankton present in the water. We present an ocean-color modeling framework that incorporates Chl-a-specific inherent optical properties of environments dominated by three different size classes of phytoplankton, and a dependency of model parameters on sea surface temperature (SST) that partitions total Chl-a among the three size classes. The model can be used to simulate spectral remote sensing reflectance as a function of SST and total Chl-a. Here, we invert the model by including two spectrally independent parameters designed to capture deviations in the optical properties of non-algal and dissolved substances from the classical Case-1 assumption. The inversion model is validated using global in-situ and satellite datasets. We also test the model using recent field measurements of optical properties collected on the PICCOLO cruise in the Weddell Sea, Antarctic, characterized by unique water temperatures and phytoplankton types. The new ocean color model will be used to answer questions on how phytoplankton are responding to climate change.

Xuerong Sun, University of Exeter, United Kingdom, https://orcid.org/0000-0003-4855-6692

Robert Brewin, University of Exeter, United Kingdom

Giorgio Dall’Olmo, Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS), Italy

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