Photosynthetic marine phytoplankton form the base of the marine food web and drive the biological pump (BP), i.e. the sinking and sequestering of organic carbon to the deep ocean that lowers…

This $665,864.55 grant was awarded by the National Aeronautics and Space Administration (NASA) to the California State University San Marcos Corporation (CSUSM Corp), a non-profit Hispanic-Serving Institution, to conduct a joint study of ocean color satellite data and the latest generation of Earth System Models (CMIP6). The goals are to: (1) improve the KSM09 algorithm for retrieving size-partitioned phytoplankton carbon concentrations and carbon-based phytoplankton size classes from satellite data, compare it to an absorption-based algorithm, and produce a merged multi-platform dataset; and (2) establish biology-physics connections and characterize biological El Niño-Southern Oscillation variability in the satellite record and climate models. This research aims to better understand the role of marine phytoplankton in the biological carbon pump and oceanic ecosystem dynamics. The grant has an ultimate completion date of September 30, 2022 and does not include a set-aside designation.

Photosynthetic marine phytoplankton form the base of the marine food web and drive the biological pump (BP), i.e. the sinking and sequestering of organic carbon to the deep ocean that lowers atmospheric CO2. Phytoplankton size is a master trait that affects the structure and function of oceanic ecosystems; phytoplankton size classes (PSCS) closely correspond to phytoplankton functional types (PFTS). PSCS change inter-annually and on decadal timescales, with implications for ecosystem ecology and the BP. Recent advances in ocean color science allow more complete characterization of ocean ecosystems e.g., kostadinov ET AL. (2016A, TK16) leverage the backscattering-based particle size distribution (PSD) algorithm KSM09 in order to retrieve size-partitioned phytoplankton carbon (C) concentrations and carbon-based PSCS. Here we propose a joint study of ocean color satellite data and the latest generation of earth system models (which are part of the 6TH coupled model intercomparison, CMIP6) to: (1) improve the KSM09 algorithm, compare IT with an absorption-based PFT algorithm, and produce a multi-platform merged data set, and (2) establish biology-physics connections and characterize biological EL NI O-southern oscillation (ENSO) variability in this satellite record and in climate models. Specifically, we propose: task a. PSD algorithm improvements and multi-platform merging task A1. Model backscattering using non-spherical particles and/or coated spheres: improvements in the KSM09 PSD algorithm will be introduced, namely particulate backscattering will be modeled using the non-spherical particle scattering kernels of dubovik ET AL. (2006). If reasonable closure of backscattering values and spectral shape cannot be obtained, MIE code for coated spheres will be used instead (zhang ET AL., 2017). Here we propose a joint study of ocean color satellite data and the latest generation of earth system models (which are part of the 6TH coupled model intercomparison, CMIP6) to: (1) improve the KSM09 algorithm, compare IT with an absorption-based PFT algorithm, and produce a multi-platform merged data set, and (2) establish biology-physics connections and characterize biological EL NI O-southern oscillation (ENSO) variability in this satellite record and in climate models. Specifically, we propose: task a. PSD algorithm improvements and multi-platform merging task A1. Model backscattering using non-spherical particles and/ or coated spheres: improvements in the KSM09 PSD algorithm will be introduced, namely particulate backscattering will be modeled using the non-spherical particle scattering kernels of dubovik ET AL. (2006). If reasonable closure of backscattering values and spectral shape cannot be obtained, MIE code for coated spheres will be used instead (zhang ET AL., 2017). Task A2. Comparison with absorptionbased algorithm of ROY ET AL. (2013): satellite imagery of PSD/PFT generated using the KSM/TK16 algorithms will be compared to the output of the ROY ET AL. (2013) PSD/PFT algorithm that is designed to retrieve the phytoplankton-only PSD. The KSM09 algorithm is sensitive to all particles. This comparison will yield information about the particle assemblage and/or inform future improvements to the KSM09 algorithm, e.g. introduction of better treatments of the index of refraction in KSM09.