Preprints
https://doi.org/10.5194/bg-2021-201
https://doi.org/10.5194/bg-2021-201

  18 Aug 2021

18 Aug 2021

Review status: this preprint is currently under review for the journal BG.

Bridging the gaps between particulate backscattering measurements and modeled particulate organic carbon in the ocean

Martí Galí1, Marcus Falls1, Hervé Claustre2, Olivier Aumont3, and Raffaele Bernardello1 Martí Galí et al.
  • 1Barcelona Supercomputing Center (BSC)
  • 2CNRS and Sorbonne Université, Laboratoire d’Océanographie de Villefranche, LOV, 06230 Villefranche-sur-7Mer, France
  • 3Sorbonne Université (CNRS/IRD/MNHN), LOCEAN-IPSL, Paris, France

Abstract. Oceanic particulate organic carbon (POC) is a relatively small (~4 Pg C) but dynamic component of the global carbon cycle with fast mean turnover rates compared to other oceanic, continental and atmospheric carbon stocks. Biogeochemical models historically focused on reproducing the sinking flux of POC driven by large fast-sinking particles (bPOC). However, suspended and slow-sinking particles (sPOC) typically represent 80–90 % of the POC stock, and can make important seasonal contributions to vertical fluxes through the mesopelagic layer (200–1000 m). Recent developments in the parameterization of POC reactivity in the PISCES model (PISCESv2_RC) have greatly improved its ability to capture sPOC dynamics. Here we evaluated this model by matching 3D and 1D simulations with BGC-Argo and satellite observations in globally representative ocean biomes, building on a refined scheme for converting particulate backscattering profiles measured by BGC-Argo floats to POC. We show that PISCES captures the major features of sPOC and bPOC as seen by BGC-Argo floats across a range of spatiotemporal scales, from highly resolved profile time series to biome-aggregated climatological profiles. Our results also illustrate how the comparison between the model and observations is hampered by (1) the uncertainties in empirical POC estimation, (2) the imperfect correspondence between modelled and observed variables, and (3) the bias between modelled and observed physics. Despite these limitations, we identified characteristic patterns of model-observations misfits in the mesopelagic layer of subpolar and subtropical gyres. These misfits likely result from both suboptimal model parameters and model equations themselves, pointing to the need to improve the model representation of processes with a critical influence on POC dynamics, such as sinking, remineralization, (dis)aggregation and zooplankton activity. Beyond model evaluation results, our analysis identified inconsistencies between current estimates of POC from satellite and BGC-Argo data, as well as POC partitioning into phytoplankton, heterotrophs and detritus deduced from in situ bio-optical data. Our approach can help constrain POC stocks, and ultimately budgets, in the epipelagic and mesopelagic ocean.

Martí Galí et al.

Status: open (until 19 Oct 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2021-201', Anonymous Referee #1, 23 Sep 2021 reply

Martí Galí et al.

Martí Galí et al.

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Short summary
Part of the organic matter produced by plankton in the upper ocean is exported to the deep ocean. This process, known as the biological carbon pump, is key for the regulation of atmospheric carbon dioxide and global climate. However, the dynamics of organic particles below the upper ocean layer are not well understood. Here we compared the measurements acquired by autonomous robots in the top 1000 m of the ocean to a numerical model, which can help improve future climate projections.
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