Coastal-ocean uptake of anthropogenic carbon

Bourgeois, Timotheé; Orr, James C.; Resplandy, Laure; Terhaar, Jens; Éthé, Christian; Gehlen, Marion; Bopp, Laurent

doi:10.5194/bg-13-4167-2016

Cited by 97 publications

(131 citation statements)

References 91 publications

(129 reference statements)

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“…For a long time, the lack of information on the coastal seas has barely been considered in the oceanic and global carbon budgets. The coastal ocean's role in terms of carbon export and relative productivity is disproportionately large in respect to its total surface area (7 %), when compared with the open ocean (Bourgeois et al, 2016). As the annual amplitude of air-sea pCO 2 difference is significantly larger in coastal regions than open ocean , the variability in the exchange is high.…”

Section: Introductionmentioning

confidence: 99%

The potential of using remote sensing data to estimate air–sea CO2 exchange in the Baltic Sea

et al. 2017

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Abstract. In this article, we present the first climatological map of air-sea CO 2 flux over the Baltic Sea based on remote sensing data: estimates of pCO 2 derived from satellite imaging using self-organizing map classifications along with class-specific linear regressions (SOMLO methodology) and remotely sensed wind estimates. The estimates have a spatial resolution of 4 km both in latitude and longitude and a monthly temporal resolution from 1998 to 2011. The CO 2 fluxes are estimated using two types of wind products, i.e. reanalysis winds and satellite wind products, the higher-resolution wind product generally leading to higher-amplitude flux estimations.Furthermore, the CO 2 fluxes were also estimated using two methods: the method of Wanninkhof et al.

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Section: Introductionmentioning

confidence: 99%

The potential of using remote sensing data to estimate air–sea CO2 exchange in the Baltic Sea

et al. 2017

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“…We define the difference between the historical simulation and the control simulation as the anthropogenic component. These ORCA05 simulations were first used by Bourgeois et al (2016) to assess the budget of anthropogenic carbon in the coastal ocean.…”

Section: Biogeochemical Simulationsmentioning

confidence: 99%

“…This physical model is coupled via TOP to version 1 of PISCES. In this study we use NEMO at three resolutions: a laminar 2°-configuration 25 (ORCA2) typical of coarse-resolution ocean models (Madec et al, 1998), which does not resolve eddies; an intermediate 0.5°-configuration (ORCA05) that just begins to allow eddies to appear spontaneously (Bourgeois et al, 2016); and a higherresolution, eddy admitting version, i.e., 0.25°-configuration (ORCA025), which is still not eddy resolving (Barnier et al, 2006).…”

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confidence: 99%

Model constraints on the anthropogenic carbon budget of the Arctic Ocean

Terhaar¹,

Orr²,

Gehlen³

et al. 2018

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Abstract. The Arctic Ocean is projected to experience not only amplified climate change but also amplified ocean acidification.Modeling future acidification depends on our ability to simulate baseline conditions and changes over the industrial era. range from a previous data-based C ant storage estimate (2.5 to 3.3 Pg C). Yet those limits may each need to be reduced by 10 about 10% because data-based C ant concentrations in deep waters remain at ∼6 µmol kg −1 , while they should be almost negligible by analogy to the near-zero observed CFC-12 concentrations from which they are calculated. Across the three resolutions, there was roughly three times as much anthropogenic carbon that entered the Arctic Ocean through lateral transport than via the flux of CO 2 across the air-sea interface. Wider comparison to nine earth system models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) reveals much larger diversity of stored anthropogenic carbon and 15 lateral transport. Only the CMIP5 models with higher lateral transport obtain C ant inventories that are close to the data-based estimates. Increasing resolution also enhances acidification, e.g., with greater shoaling of the Arctic's average depth of the aragonite saturation horizon during 1960-2012, from 50 m in ORCA2 to 210 m in ORCA025. To assess the potential to further refine modeled estimates of the Arctic Ocean's C ant storage and acidification, sensitivity tests that adjust model parameters are needed given that century-scale global ocean biogeochemical simulations still cannot be run routinely at high resolution.

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“…Aumont and Bopp, 2006;Bourgeois et al, 2016;Matear and Lenton, 2008;Le Quéré et al, 2007;Schwinger et al, 2016;Thomas et al, 2008). In addition to the four quadratic equations obtained from 14 C bomb inventories, we also included the hybrid equation…”

Section: Sensitivity and Uncertainty Analysis 30mentioning

confidence: 99%

“…In numerous modeling studies, FCO 2 is still calculated using k-parametrizations from the literature combined with a different wind product from the one used to calibrate the coefficient c (e.g. Aumont and Bopp, 2006;Bourgeois et al, 2016;Matear and Lenton, 2008;Le Quéré et al, 2007;Schwinger et al, 2016;Thomas et al, 2008). …”

mentioning

confidence: 99%

Uncertainty of the global oceanic CO2 uptake induced by wind forcing: quantification and spatial analysis

Roobaert¹,

Laruelle²,

Landschützer³

et al. 2017

Preprint

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Abstract. The calculation of the air-water CO 2 exchange (FCO 2 ) in the ocean not only depends on the gradient in CO 2 partial pressure at the air-water interface but also on the parameterization of the gas exchange transfer velocity (k) and the choice of wind product. Here, we present regional and global-scale quantifications of the uncertainty in FCO 2 induced by several widely used k-formulations and 4 wind speed data products (CCMP, ERA, NCEP1 and NCEP2). The analysis is 10 performed at a 1° x 1° resolution using the sea surface pCO 2 climatology generated by Landschützer et al. (2015) that the range of global FCO 2 , calculated with these k-relationships, diverge by 12 % when using CCMP, ERA or NCEP1.Due to differences in the regional wind patterns, regional discrepancies in FCO 2 are more pronounced than global. These global/regional differences significantly increase when using NCEP2 or other k-formulations which include earlier relationships (i.e. Wanninkhof et al., 2009) as well as numerous local/regional parameterizations derived experimentally. To minimize uncertainties associated with the choice of wind product it is possible to recalculate the 20 coefficient c globally (hereafter called c * ) for a given wind product and its spatio-temporal resolution, in order to match the last evaluation of the global k value. We thus performed these recalculations for each wind product at the resolution and time period of our study but the resulting global FCO 2 estimates still diverge by 10 %. These results also reveal that the Equatorial Pacific, the North Atlantic and the Southern Ocean are the regions in which the choice of wind product will most strongly affect the estimation of the FCO 2 , even when using c * . 25

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Coastal-ocean uptake of anthropogenic carbon

Abstract: International audienc

Cited by 97 publications

References 91 publications

The potential of using remote sensing data to estimate air–sea CO<sub>2</sub> exchange in the Baltic Sea

The potential of using remote sensing data to estimate air–sea CO<sub>2</sub> exchange in the Baltic Sea

Model constraints on the anthropogenic carbon budget of the Arctic Ocean

Uncertainty of the global oceanic CO<sub>2</sub> uptake induced by wind forcing: quantification and spatial analysis

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Coastal-ocean uptake of anthropogenic carbon

Abstract: International audienc

Cited by 97 publications

References 91 publications

The potential of using remote sensing data to estimate air–sea CO&lt;sub&gt;2&lt;/sub&gt; exchange in the Baltic Sea

The potential of using remote sensing data to estimate air–sea CO&lt;sub&gt;2&lt;/sub&gt; exchange in the Baltic Sea

Model constraints on the anthropogenic carbon budget of the Arctic Ocean

Uncertainty of the global oceanic CO&lt;sub&gt;2&lt;/sub&gt; uptake induced by wind forcing: quantification and spatial analysis

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The potential of using remote sensing data to estimate air–sea CO<sub>2</sub> exchange in the Baltic Sea

The potential of using remote sensing data to estimate air–sea CO<sub>2</sub> exchange in the Baltic Sea

Uncertainty of the global oceanic CO<sub>2</sub> uptake induced by wind forcing: quantification and spatial analysis