Variable reactivity of particulate organic matter in a global ocean biogeochemical model

Aumont, Olivier; Hulten, Marco van; Roy‐Barman, Matthieu; Dutay, Jean-Claude; Éthé, Christian; Gehlen, Marion

doi:10.5194/bg-14-2321-2017

Cited by 62 publications

(88 citation statements)

References 109 publications

(182 reference statements)

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“…This version of PISCES includes two size classes of POC, both with differential remineralisation rates (Aumont et al, 2017), , corresponding with "small" and "big" particles ( Fig. 1).…”

Section: Particle Dynamicsmentioning

confidence: 99%

“…6b), but the spatial distributions are very different. More detailed results and discussion on the simulation of POC 10 are to be found in Aumont et al (2017).…”

Section: Particlesmentioning

confidence: 99%

“…We evaluate how well the model fits with observations, but tuning is not one of our main goals. Just like Dutay et al (2009), we use the NEMO-OPA ocean general circulation model and the PISCES biogeochemical model with 10 improved particle dynamics (Aumont et al, 2017). There are several improvements since Dutay et al (2009), namely the new model -includes lithogenic particles from dust deposition;…”

mentioning

confidence: 99%

“…20 Aumont et al (2017) showed that dissolution rates of Particulate Organic Carbon (POC) were overestimated, and they improved on this by introducing a spectrum of different labilities. This improved the simulation of both small and large POC significantly, so we use this same model for our simulations.…”

mentioning

confidence: 99%

“…-improved the biogeochemistry, affecting the biogenic particle distributions (Aumont et al, 2015(Aumont et al, , 2017; -includes three different phases per nuclide (dissolved, and adsorbed onto big (and small) particles), whereas Dutay et al…”

mentioning

confidence: 99%

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A global scavenging and circulation ocean model of thorium-230 and protactinium-231 with realistic particle dynamics (NEMO–ProThorP 0.1)

Hulten¹,

Dutay²,

Roy‐Barman³

2017

Preprint

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“…This version of PISCES includes two size classes of POC, both with differential remineralisation rates (Aumont et al, 2017), , corresponding with "small" and "big" particles ( Fig. 1).…”

Section: Particle Dynamicsmentioning

confidence: 99%

“…6b), but the spatial distributions are very different. More detailed results and discussion on the simulation of POC 10 are to be found in Aumont et al (2017).…”

Section: Particlesmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A global scavenging and circulation ocean model of thorium-230 and protactinium-231 with realistic particle dynamics (NEMO–ProThorP 0.1)

Hulten¹,

Dutay²,

Roy‐Barman³

2017

Preprint

Self Cite

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Slow‐sinking particulate organic carbon in the Atlantic Ocean: Magnitude, flux, and potential controls

Baker

Henson

Cavan

et al. 2017

Global Biogeochemical Cycles

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The remineralization depth of particulate organic carbon (POC) fluxes exported from the surface ocean exerts a major control over atmospheric CO₂ levels. According to a long‐held paradigm most of the POC exported to depth is associated with large particles. However, recent lines of evidence suggest that slow‐sinking POC (SSPOC) may be an important contributor to this flux. Here we assess the circumstances under which this occurs. Our study uses samples collected using the Marine Snow Catcher throughout the Atlantic Ocean, from high latitudes to midlatitudes. We find median SSPOC concentrations of 5.5 μg L−1, 13 times smaller than suspended POC concentrations and 75 times higher than median fast‐sinking POC (FSPOC) concentrations (0.07 μg L−1). Export fluxes of SSPOC generally exceed FSPOC flux, with the exception being during a spring bloom sampled in the Southern Ocean. In the Southern Ocean SSPOC fluxes often increase with depth relative to FSPOC flux, likely due to midwater fragmentation of FSPOC, a process which may contribute to shallow mineralization of POC and hence to reduced carbon storage. Biogeochemical models do not generally reproduce this behavior, meaning that they likely overestimate long‐term ocean carbon storage.

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Dynamic Biological Functioning Important for Simulating and Stabilizing Ocean Biogeochemistry

Buchanan

Matear

Chase

et al. 2018

Global Biogeochemical Cycles

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The biogeochemistry of the ocean exerts a strong influence on the climate by modulating atmospheric greenhouse gases. In turn, ocean biogeochemistry depends on numerous physical and biological processes that change over space and time. Accurately simulating these processes is fundamental for accurately simulating the ocean's role within the climate. However, our simulation of these processes is often simplistic, despite a growing understanding of underlying biological dynamics. Here we explore how new parameterizations of biological processes affect simulated biogeochemical properties in a global ocean model. We combine 6 different physical realizations with 6 different biogeochemical parameterizations (36 unique ocean states). The biogeochemical parameterizations, all previously published, aim to more accurately represent the response of ocean biology to changing physical conditions. We make three major findings. First, oxygen, carbon, alkalinity, and phosphate fields are more sensitive to changes in the ocean's physical state. Only nitrate is more sensitive to changes in biological processes, and we suggest that assessment protocols for ocean biogeochemical models formally include the marine nitrogen cycle to assess their performance. Second, we show that dynamic variations in the production, remineralization, and stoichiometry of organic matter in response to changing environmental conditions benefit the simulation of ocean biogeochemistry. Third, dynamic biological functioning reduces the sensitivity of biogeochemical properties to physical change. Carbon and nitrogen inventories were 50% and 20% less sensitive to physical changes, respectively, in simulations that incorporated dynamic biological functioning. These results highlight the importance of a dynamic biology for ocean properties and climate.

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Variable reactivity of particulate organic matter in a global ocean biogeochemical model

Cited by 62 publications

References 109 publications

A global scavenging and circulation ocean model of thorium-230 and protactinium-231 with realistic particle dynamics (NEMO–ProThorP 0.1)

A global scavenging and circulation ocean model of thorium-230 and protactinium-231 with realistic particle dynamics (NEMO–ProThorP 0.1)

Slow‐sinking particulate organic carbon in the Atlantic Ocean: Magnitude, flux, and potential controls

Dynamic Biological Functioning Important for Simulating and Stabilizing Ocean Biogeochemistry

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