ALBERT

Description: The Southern Ocean (44–75°S) plays a critical role in the global carbon cycle, yet remains one of the most poorly sampled ocean regions. Different approaches have been used to estimate sea–air CO2 fluxes in this region: synthesis of surface ocean observations, ocean biogeochemical models, and atmospheric and ocean inversions. As part of the RECCAP (REgional Carbon Cycle Assessment and Processes) project, we combine these different approaches to quantify and assess the magnitude and variability in Southern Ocean sea–air CO2 fluxes between 1990–2009. Using all models and inversions (26), the integrated median annual sea–air CO2 flux of −0.42 ± 0.07 PgC yr−1 for the 44–75°S region, is consistent with the −0.27 ± 0.13 PgC yr−1 calculated using surface observations. The circumpolar region south of 58°S has a small net annual flux (model and inversion median: −0.04 ± 0.07 PgC yr−1 and observations: +0.04 ± 0.02 PgC yr−1), with most of the net annual flux located in the 44 to 58°S circumpolar band (model and inversion median: −0.36 ± 0.09 PgC yr−1 and observations: −0.35 ± 0.09 PgC yr−1). Seasonally, in the 44–58°S region, the median of 5 ocean biogeochemical models captures the observed sea–air CO2 flux seasonal cycle, while the median of 11 atmospheric inversions shows little seasonal change in the net flux. South of 58°S, neither atmospheric inversions nor ocean biogeochemical models reproduce the phase and amplitude of the observed seasonal sea–air CO2 flux, particularly in the AustralWinter. Importantly, no individual atmospheric inversion or ocean biogeochemical model is capable of reproducing both the observed annual mean uptake and the observed seasonal cycle. This raises concerns about projecting future changes in Southern Ocean CO2 fluxes. The median interannual variability from atmospheric inversions and ocean biogeochemical models is substantial in the Southern Ocean; up to 25% of the annual mean flux, with 25% of this interannual variability attributed to the region south of 58°S. Resolving long-term trends is difficult due to the large interannual variability and short time frame (1990–2009) of this study; this is particularly evident from the large spread in trends from inversions and ocean biogeochemical models. Nevertheless, in the period 1990–2009 ocean biogeochemical models do show increasing oceanic uptake consistent with the expected increase of −0.05 PgC yr−1 decade−1. In contrast, atmospheric inversions suggest little change in the strength of the CO2 sink broadly consistent with the results of Le Quéré et al. (2007).

Description: © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 19 (2013): 4037-4054, doi:10.5194/bg-10-4037-2013.

Description: The Southern Ocean (44–75° S) plays a critical role in the global carbon cycle, yet remains one of the most poorly sampled ocean regions. Different approaches have been used to estimate sea–air CO2 fluxes in this region: synthesis of surface ocean observations, ocean biogeochemical models, and atmospheric and ocean inversions. As part of the RECCAP (REgional Carbon Cycle Assessment and Processes) project, we combine these different approaches to quantify and assess the magnitude and variability in Southern Ocean sea–air CO2 fluxes between 1990–2009. Using all models and inversions (26), the integrated median annual sea–air CO2 flux of −0.42 ± 0.07 Pg C yr−1 for the 44–75° S region, is consistent with the −0.27 ± 0.13 Pg C yr−1 calculated using surface observations. The circumpolar region south of 58° S has a small net annual flux (model and inversion median: −0.04 ± 0.07 Pg C yr−1 and observations: +0.04 ± 0.02 Pg C yr−1), with most of the net annual flux located in the 44 to 58° S circumpolar band (model and inversion median: −0.36 ± 0.09 Pg C yr−1 and observations: −0.35 ± 0.09 Pg C yr−1). Seasonally, in the 44–58° S region, the median of 5 ocean biogeochemical models captures the observed sea–air CO2 flux seasonal cycle, while the median of 11 atmospheric inversions shows little seasonal change in the net flux. South of 58° S, neither atmospheric inversions nor ocean biogeochemical models reproduce the phase and amplitude of the observed seasonal sea–air CO2 flux, particularly in the Austral Winter. Importantly, no individual atmospheric inversion or ocean biogeochemical model is capable of reproducing both the observed annual mean uptake and the observed seasonal cycle. This raises concerns about projecting future changes in Southern Ocean CO2 fluxes. The median interannual variability from atmospheric inversions and ocean biogeochemical models is substantial in the Southern Ocean; up to 25% of the annual mean flux, with 25% of this interannual variability attributed to the region south of 58° S. Resolving long-term trends is difficult due to the large interannual variability and short time frame (1990–2009) of this study; this is particularly evident from the large spread in trends from inversions and ocean biogeochemical models. Nevertheless, in the period 1990–2009 ocean biogeochemical models do show increasing oceanic uptake consistent with the expected increase of −0.05 Pg C yr−1 decade−1. In contrast, atmospheric inversions suggest little change in the strength of the CO2 sink broadly consistent with the results of Le Quéré et al. (2007).

Description: A. Lenton, B. Tilbrook, R. J. Matear and R. M. Law were funded by the Australian Climate Change Science Program and theWealth from Oceans National Research Flagship. S. C. Doney acknowledges support from the National Science Foundation (OPP-0823101), T. Takahashi is supported by grants from United States NOAA (NA08OAR4320754) and National Science Foundation (ANT 06-36879). D. Baker, N. Gruber, M. Hoppema, N. Metzl acknowledge the support of EU FP7 project CARBOCHANGE (264879). S. C. Doney acknowledges support from the National Science Foundation (OPP-0823101). N. S. Lovenduski is grateful for support from NSF (OCE-1155240) and NOAA (NA12OAR4310058). This study is also a contribution to the international IMBER/SOLAS Projects. C. Sweeney acknowledges support from the United States NOAA (NA12OAR4310058) and National Science Foundation (0944761).

Description: The Southern Ocean (44° S–75° S) plays a critical role in the global carbon cycle, yet remains one of the most poorly sampled ocean regions. Different approaches have been used to estimate sea-air CO2 fluxes in this region: synthesis of surface ocean observations, ocean biogeochemical models, and atmospheric and ocean inversions. As part of the RECCAP (REgional Carbon Cycle Assessment and Processes) project, we combine these different approaches to quantify and assess the magnitude and variability in Southern Ocean sea-air CO2 fluxes between 1990–2009. Using all models and inversions (26), the integrated median annual sea-air CO2 flux of −0.42 ± 0.07 Pg C yr−1 for the 44° S–75° S region is consistent with the −0.27 ± 0.13 Pg C yr−1 calculated using surface observations. The circumpolar region south of 58° S has a small net annual flux (model and inversion median: −0.04 ± 0.07 Pg C yr−1 and observations: +0.04 ± 0.02 Pg C yr−1), with most of the net annual flux located in the 44° S to 58° S circumpolar band (model and inversion median: −0.36 ± 0.09 Pg C yr−1 and observations: −0.35 ± 0.09 Pg C yr−1). Seasonally, in the 44° S–58° S region, the median of 5 ocean biogeochemical models captures the observed sea-air CO2 flux seasonal cycle, while the median of 11 atmospheric inversions shows little seasonal change in the net flux. South of 58° S, neither atmospheric inversions nor ocean biogeochemical models reproduce the phase and amplitude of the observed seasonal sea-air CO2 flux, particularly in the Austral Winter. Importantly, no individual atmospheric inversion or ocean biogeochemical model is capable of reproducing both the observed annual mean uptake and the observed seasonal cycle. This raises concerns about projecting future changes in Southern Ocean CO2 fluxes. The median interannual variability from atmospheric inversions and ocean biogeochemical models is substantial in the Southern Ocean; up to 25% of the annual mean flux with 25% of this inter-annual variability attributed to the region south of 58° S. Trends in the net CO2 flux from the inversions and models are not statistically different from the expected increase of –0.05 Pg C yr−1 decade−1 due to increasing atmospheric CO2 concentrations. However, resolving long term trends is difficult due to the large interannual variability and short time frame (1990–2009) of this study.

Description: Future changes to the organic carbon and carbonate pumps are likely to affect ocean ecosystem dynamics and the biogeochemical climate. Here, biological dependencies on the Rain and Redfield ratios on pCO2 are implemented in a coupled Biogeochemistry-Ocean Model, the CSIRO-Mk3L, to establish extreme-case carbonate saturation vulnerability to model parameterisation at year 2500 using IPCC Representative Concentration Pathway 8.5. Surface carbonate saturation is relatively insensitive to the combined effects of variable Rain and Redfield ratios (an anomaly of less than 10 % of the corresponding change in the control configuration by year 2500), but the global zonally-averaged ocean interior anomaly due to these feedbacks is up to 130 % by 2500. A non-linear interaction between organic and carbonate pumps is found in export production, where higher rates of photosynthesis enhance calcification by raising surface alkalinity. This non-linear effect has a negligible influence on surface carbonate saturation but does significantly influence ocean interior carbonate saturation fields (an anomaly of up to 45 % in 2500). The strongest linear and non-linear sensitivity to combined feedbacks occurs in low-latitude remineralisation zones below regions of enhanced biological production, where dissolved inorganic carbon rapidly accumulates.

Description: The ocean's role has been pivotal in modulating rising atmospheric CO2 levels since the industrial revolution, sequestering over a quarter of all fossil-fuel derived CO2 emissions. Net oceanic uptake of CO2 has roughly doubled between the 1960's (~1 Pg C yr−1) and 2000's (~2 Pg C yr−1), with expectations it will continue to absorb even more CO2 with rising future atmospheric CO2 levels. However, recent CO2 observational analyses along with numerous model predictions suggest the rate of oceanic CO2 uptake is already slowing, largely as a result of a natural decadal-scale outgassing signal. This recent and unexpected CO2 outgassing signal represents a paradigm-shift in our understanding of the oceans role in modulating atmospheric CO2. Current tracer-based estimates for the ocean storage of anthropogenic CO2 assume the ocean circulation and biology is in steady state, thereby missing the new and potentially important "non-steady-state" CO2 outgassing signal. By combining data-based techniques that assume the ocean is in steady-state, with techniques that constrain the net oceanic CO2 uptake signal, we show how to extract the non-steady-state CO2 signal from observations. Over the entire industrial era, the non-steady-state CO2 outgassing signal (~13 ± 10 Pg C) is estimated to represent about 9% of the total net CO2 inventory change (~142 Pg C). However between 1989 and 2007, the non-steady-state CO2 outgassing signal (~6.3 Pg C) has likely increased to be ~18% of net oceanic CO2 storage over that period (~36 Pg C), a level which cannot be ignored. The present uncertainty of our data-based techniques for oceanic CO2 uptake limit our capacity to quantify the non-steady-state CO2 signal, however with more data and better certainty estimates across a~range of diverse methods, this important and growing CO2 signal could be better constrained in the future.

Description: The ocean's role in modulating the observed 1–7 Pg C yr−1 inter-annual variability in atmospheric CO2 growth rate is an important, but poorly constrained process due to sparse spatio-temporal ocean carbon measurements. Here, we investigate and develop a non-linear empirical approach to predict inorganic CO2 concentrations (total carbon dioxide (CT) and total alkalinity (AT) in the global ocean mixed-layer from hydrographic properties (temperature, salinity, dissolved oxygen and nutrients). The benefit of this approach is that once the empirical relationship is established, it can be applied to hydrographic datasets that have better spatio-temporal coverage, and therefore provide an additional constraint to diagnose ocean carbon dynamics globally. Previous empirical approaches have employed multiple linear regressions (MLR), and relied on ad-hoc geographic and temporal partitioning of carbon data to constrain complex global carbon dynamics in the mixed-layer. Synthesising a new global CT/AT carbon bottle dataset consisting of ~33 000 measurements in the open ocean mixed-layer, we develop a neural network based approach to better constrain the non-linear carbon system. The approach classifies features in the global biogeochemical dataset based on their similarity and homogeneity in a self-organizing map (SOM; Kohonen, 1988). After the initial SOM analysis, which includes geographic constraints, we apply a local linear optimizer to the neural network which considerably enhances the predictive skill of the new approach. We call this new approach SOMLO, or self-organizing multiple linear output. Using independent bottle carbon data, we compare a traditional MLR analysis to our SOMLO approach to capture the spatial CT and AT distributions. We find the SOMLO approach improves predictive skill globally by 19% for CT, with a global capacity to predict CT to within 10.9 μmol kg−1 (9.2 μmol kg−1 for AT. The non-linear SOMLO approach is particularly powerful in complex, but important regions like the Southern Ocean, North Atlantic and equatorial Pacific where residual standard errors were reduced between 25–40% over traditional linear methods. We further test the SOMLO technique using the Bermuda Atlantic time-series (BATS) and Hawaiian ocean (HOT) datasets, where hydrographic data was capable of explaining 90% of the seasonal cycle and inter-annual variability at those multi-decadal time-series stations.