Decreasing the uncertainty in Particulate Organic Carbon (POC) distribution and budgets in the North Atlantic mesopelagic layer

Association for the Sciences of Limnology and Oceanography (ASLO) Aquatic Sciences Meeting, Resilence and Recovery in Aquatic Systems, 4-9 June 2023, Palma de Mallorca, Spain The mesopelagic layer (200-1000m) plays a fundamental role in oceanic carbon sequestration. It also hosts a massive biomass o...

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Bibliographic Details
Main Authors: Orihuela-García, M. Andrea, Ruprich-Robert, Yohan, Galí, Martí, Lapin, Vladimir, Loosveldt-Tomas, Saskia
Format: Conference Object
Language:unknown
Published: Association for the Sciences of Limnology and Oceanography 2023
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Online Access:http://hdl.handle.net/10261/362867
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Summary:Association for the Sciences of Limnology and Oceanography (ASLO) Aquatic Sciences Meeting, Resilence and Recovery in Aquatic Systems, 4-9 June 2023, Palma de Mallorca, Spain The mesopelagic layer (200-1000m) plays a fundamental role in oceanic carbon sequestration. It also hosts a massive biomass of zooplankton and small fish that feed on sinking detritus (i.e., POC). However, scientific understanding of mesopelagic POC is still underdeveloped due to the numerous processes involved (gravitational sinking, horizontal transport, biological transformations by bacteria and zooplankton…). The objective of this study is to quantify the terms dominating the spatiotemporal variability of the mesopelagic POC budget in different regions of the North Atlantic. The choice of these regions is based on dynamical and biogeochemical criteria. Our analyses are based on numerical simulations performed with the ocean dynamical model NEMO4 (Madec et al. 2008) coupled to the biogeochemical model PISCES-v2 (Aumont et al. 2017). Compared to observations, our model shows biases in mesopelagic POC distribution and fluxes (from spatially distributed bioArgo floats and the sediment trap time series at BATS). Those biases can arise from uncertainties in POC supply from the surface layer and from the representation in mesopelagic processes in the model equations. Improving the model performance at the surface, we expect improving the model performance in the mesopelagic layer. For that, we develop a model sub-routine that allows constraining the model to follow satellite observations, in terms of small and large phytoplankton carbon biomass at the sea surface. Eventually, this enables us to reduce the uncertainty in mesopelagic POC distribution and budget