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Combining a Stochastic LAgrangian Model of Marine Particles with ESA’s Big Data to Understand the Effects of a ChaNging Ocean on the PlanKtonic Food Web (SLAM DUNK)



The oceans, a major sink of carbon dioxide (CO2), rely on a set of food web processes that generate gravitational sinking particles to transfer CO2 from the atmosphere to the deep ocean. These processes are collectively known as the biological carbon pump (BCP) and have become a focal point of research as anthropogenic CO2 emissions rise. Over the past three decades, there has been increased observational and modelling capacity aimed at quantifying how much of the BCP-generated particulate organic carbon (POC) flux reaches the deep ocean before it is degraded into CO2 and upwelled to the atmosphere. Despite these efforts, oceanographers still lack a clear understanding of the mechanisms controlling POC flux transfer efficiency to the deep ocean (Teff). Two key challenges persist.

On the observational side, collecting in situ data has traditionally been difficult given the vastness of the ocean. On the computational side, although conventional numerical models have improved quantifications of the fluxes of carbon transferred to depth, they are unable to untangle the factors that control Teff as they are unsuited to resolve the vectors that transfer that carbon: marine particles. Satellites have leveraged observational capacity with their synoptic-scale coverage of the surface ocean carbon pools. In this context, ESA launched the Ocean Colour Climate Change Initiative (OC-CCI) and Biological Pump and Carbon Exchange Processes (BICEP) project to derive key variables of the surface ocean carbon cycle from remote sensing of ocean colour. In an unprecedented effort, OC-CCI and BICEP have created a portfolio of long-term, quality-controlled interrelated variables that comprehensively characterise the surface ocean BCP. However, the deeper ocean, where Teff is set, remains disparately less well characterised and a growing need has emerged to extend the satellite-based representation of marine carbon to the deeper ocean, a task requiring models. SLAM DUNK proposes combining ESA’s satellite-derived data products of the surface ocean carbon cycle with a novel mechanistic model of marine particles developed within the BCP framework. The goal is to understand the water column particle dynamics, surface ocean ecosystem structure and environmental factors controlling the global patterns of Teff. ESA’s data products are essential for calibrating and validating the model, which requires a well-resolved surface ocean ecosystem to generate ocean interior POC fluxes comparable to observations, and thus improve simulated estimates of Teff. This involves assimilating into the model (i) the amount of atmospheric CO2 fixed by phytoplankton (net primary production), (ii) the amount of that carbon that leaves the surface ocean as sinking POC flux (export production) and (iii) its distribution into phytoplankton groups of varying sizes and carbon contents (phytoplankton functional types). Phytoplankton group characteristics dictate particle sinking velocities and, consequently, the fate of POC as an emergent property of thousands of computational particles with distinct life histories.

This model implementation of ESA’s Earth Observations (EO) data will generate an array of model outputs that will benefit ocean-colour science, marine biogeochemistry and ocean forecasting and ultimately addresses a critical challenge in oceanography: understanding the marine carbon cycle’s response to anthropogenic climate change.


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