Identifying the biological control of the annual and multi-year variations in South Atlantic air–sea CO₂ flux

Abstract

Abstract. The accumulation of anthropogenic CO2 emissions in the atmosphere has been buffered by the absorption of CO2 by the global ocean, which acts as a net CO2 sink. The CO2 flux between the atmosphere and the ocean, which collectively results in the oceanic carbon sink, is spatially and temporally variable, and fully understanding the driving mechanisms behind this flux is key to assessing how the sink may change in the future. In this study a time series decomposition analysis was applied to satellite observations to determine the drivers that control the sea–air difference of CO2 partial pressure (ΔpCO2) and the CO2 flux on seasonal and inter-annual timescales in the South Atlantic Ocean. Linear trends in ΔpCO2 and the CO2 flux were calculated to identify key areas of change. Seasonally, changes in both the ΔpCO2 and CO2 flux were dominated by sea surface temperature (SST) in the subtropics (north of 40∘ S) and were correlated with biological processes in the subpolar regions (south of 40∘ S). In the equatorial Atlantic, analysis of the data indicated that biological processes are likely a key driver as a response to upwelling and riverine inputs. These results highlighted that seasonally ΔpCO2 can act as an indicator to identify drivers of the CO2 flux. Inter-annually, the SST and biological contributions to the CO2 flux in the subtropics were correlated with the multivariate El Niño–Southern Oscillation (ENSO) index (MEI), which leads to a weaker (stronger) CO2 sink in El Niño (La Niña) years. The 16-year time series identified significant trends in ΔpCO2 and CO2 flux; however, these trends were not always consistent in spatial extent. Therefore, predicting the oceanic response to climate change requires the examination of CO2 flux rather than ΔpCO2. Positive CO2 flux trends (weakening sink for atmospheric CO2) were identified within the Benguela upwelling system, consistent with increased upwelling and wind speeds. Negative trends in the CO2 flux (intensifying sink for atmospheric CO2) offshore into the South Atlantic gyre were consistent with an increase in the export of nutrients from mesoscale features, which drives the biological drawdown of CO2. These multi-year trends in the CO2 flux indicate that the biological contribution to changes in the air–sea CO2 flux cannot be overlooked when scaling up to estimates of the global ocean carbon sink.

A comprehensive analysis of air-sea CO2 flux uncertainties constructed from surface ocean data products

“…Therefore, it is important to assess all sources of uncertainties within the air-sea CO 2 fluxes as some components may be more dominant in some regions as opposed to others (Figure 4). These uncertainties should also be considered when assessing trends and/or more complex decompositions of seasonal, interannual and decadal variability (Ford et al, 2022b;Landschützer et al, 2016Landschützer et al, , 2018. A concerted effort to implement these full uncertainty budgets for the air-sea CO 2 fluxes in preparation for future advances and reductions of uncertainties in the air-sea CO 2 flux calculations would appear critical.…”

Canada's marine carbon sink: an early career perspective on the state of research and existing knowledge gaps

“…Regional downscaling of low-resolution models to higher resolution, especially in heterogeneous regions like the Canadian Arctic Archipelago, can result in more informative model projections (Table 2). As an example, mesoscale eddies are quite important for mixing (and therefore also impact air-sea CO 2 fluxes; Ford et al 2022), but are often not resolved in current generations of earth system models (Frölicher et al 2015) models (looking at data from where and when we have realworld observations within the full model field) can be used to evaluate the performance of current observation gap-filling techniques (Gloege et al 2021) in regions of high air-sea CO 2 fluxes and high uncertainty (e.g., high-latitude oceans; Gruber et al 2019b). Moreover, new statistical tools and techniques such as emergent constraints (a way of looking at the relationship between a variable of current climate state within individual models, and future changes in a variable of interest that make up an ensemble) accelerate the development and improvement of the next generations of earth system models (e.g., Hall et al 2019;Bourgeois et al 2022).…”