Editing IPCC:AR6/WGI/Chapter-5 (section)

===== 5.2.1.3.1 Ocean carbon fluxes and storage: Global multi-decadal trends =====

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In the first assessment approach, the mean global multi-decadal (1960–2019) trends in the ocean sink (S <sub>ocean</sub> ) for CO <sub>2</sub> show a high degree of coherence across the nine GOBMs and six ''p'' CO <sub>2</sub> -based observational product reconstructions (1987–2018) which, despite a temporary slowdown (or ‘hiatus’) in the 1990s, is also quasi-linear over that period (Figure 5.8a; [[#Gregor--2019|Gregor et al., 2019]] ; [[#Hauck--2020|Hauck et al., 2020]] ). This coherence between the GOBMs and observations-based reconstructions (1987–2018; r <sup>2</sup> =0.85) provides ''high confidence'' that the ocean sink (S <sub>ocean</sub> in [[#5.2.1.5|Section 5.2.1.5]] ) evaluated from GOBMs (1960–2019) grew quasi-linearly from 1.0 ± 0.3 PgC yr <sup>–1</sup> to 2.5 ± 0.6 PgC yr <sup>–1</sup> between the decades 1960–1969 and 2010–2019 in response to global CO <sub>2</sub> emissions (Figure 5.8a; Table 5.1; [[#Friedlingstein--2020|Friedlingstein et al., 2020]] ; [[#Hauck--2020|Hauck et al., 2020]] ). The cumulative ocean CO <sub>2</sub> uptake (105 ± 20 PgC) is 23% of total anthropogenic CO <sub>2</sub> emissions (450 ± 50 PgC) for the same period ( [[#Friedlingstein--2020|Friedlingstein et al., 2020]] ). Notwithstanding the ''high confidence'' in the magnitude of the annual to decadal trends for S <sub>ocean,</sub> this assessment is moderated to ''medium'' c ''onfidence'' by the ''low confidence'' in the currently inadequately constrained uncertainties in the pre-industrial land-to-ocean carbon flux, the uncertain magnitude of winter outgassing from the Southern Ocean, and the uncertain effect of the ocean surface cool-skin, the effect of data sparsity, differences between wind products and the uncertain contribution from the changing land–ocean continuum on global and regional fluxes ( [[#Jacobson--2007|Jacobson et al., 2007]] ; [[#Resplandy--2018|Resplandy et al., 2018]] ; [[#Roobaert--2018|Roobaert et al., 2018]] ; [[#Bushinsky--2019|Bushinsky et al., 2019]] ; [[#Hauck--2020|Hauck et al., 2020]] ; [[#Watson--2020|Watson et al., 2020]] ; [[#Gloege--2021|Gloege et al., 2021]] ). However, both GOBMs and ''p'' CO <sub>2</sub> -based observational products independently reveal a slowdown or ‘hiatus’ of the ocean sink in the 1990s, which provides a valuable constraint for model verification and leads to greater confidence in the model outputs (Figure 5.8a; [[#Landschützer--2016|Landschützer et al., 2016]] ; [[#Gregor--2018|Gregor et al., 2018]] ; [[#DeVries--2019|DeVries et al., 2019]] ; [[#Hauck--2020|Hauck et al., 2020]] ). A number of studies point to the role of the Southern Ocean in the global ‘1990s hiatus’ in air–sea CO <sub>2</sub> fluxes, but provide different process-based explanations linking ocean temperature, mixing and meridional overturning circulation (MOC) responses to variability in large-scale climate systems, wind stress and volcanic activity, as well as the sensitivity of the air–sea CO <sub>2</sub> flux to small changes in the atmospheric forcing from anthropogenic CO <sub>2</sub> ( [[#Landschützer--2016|Landschützer et al., 2016]] ; [[#DeVries--2017|DeVries et al., 2017]] ; [[#Bronselaer--2018|Bronselaer et al., 2018]] ; [[#Gregor--2018|Gregor et al., 2018]] ; [[#Gruber--2019a|Gruber et al., 2019a]] ; [[#Keppler--2019|Keppler and Landschützer, 2019]] ; [[#McKinley--2020|McKinley et al., 2020]] ; [[#Nevison--2020|Nevison et al., 2020]] ). Data sparsity in the Southern Ocean could also be a factor amplifying the global decadal perturbation of the 1990s ( [[#Gloege--2021|Gloege et al., 2021]] ). Therefore, while there is ''high confidence'' in the 1990s hiatus of the global ocean sink for anthropogenic CO <sub>2,</sub> and that the Southern Ocean makes an observable contribution to it, there is still ''low confidence'' in the attribution for the processes behind the 1990s hiatus ( [[#5.2.1.3.2|Section 5.2.1.3.2]] ). Observed increases in the amplitude of the seasonal cycle of ocean ''p'' CO <sub>2</sub> and reductions in the mean global buffering capacity provide ''high confidence'' that the growing CO <sub>2</sub> sink is also beginning to drive observable large-scale changes in ocean carbonate chemistry ( [[#Jiang--2019|Jiang et al., 2019]] ). However, there is ''medium confidence'' that these changes which, depending on the emissions scenario, could drive future ocean feedbacks, are still too small to emerge from the historical multi-decadal observed growth rate of S <sub>ocean</sub> (Sections 5.1.2; 5.3.2 and 5.4.2, and Figure 5.8a; SROCC ( [[#5.2.2.3.2|Section 5.2.2.3.2]] ; [[#Bates--2014|Bates et al., 2014]] ; [[#Sutton--2016|Sutton et al., 2016]] ; [[#Fassbender--2017|Fassbender et al., 2017]] ; [[#Landschützer--2018|Landschützer et al., 2018]] ; [[#Jiang--2019|Jiang et al., 2019]] ). A recent model-based study suggests that re-emergence of previously stored anthropogenic CO <sub>2</sub> is changing the buffering capacity of the mixed layer and reducing the ocean sink for anthropogenic CO <sub>2</sub> during the historical period ( [[#Rodgers--2020|Rodgers et al., 2020]] ). This trend is not reflected in observations-based products (Figure 5.8a), so we attribute a ''low confidence'' .

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'''Figure 5.8 |''' '''Multi-decadal trends for the ocean sink of CO''' <sub>2</sub> '''.''' '''(a)''' The multi-decadal (1960–2019) trends in the annual ocean sink (S <sub>ocean</sub> ) reconstructed from nine Global Ocean Biogeochemical Models (GOBM) forced with atmospheric re-analysis products ( [[#Hauck--2020|Hauck et al., 2020]] ), six observationally based gap-filling products that reconstructed spatial and temporal variability in the ocean CO <sub>2</sub> flux from sparse observations of surface ocean ''p'' CO <sub>2</sub> (Supplementary Materials 5.SM.2). The trends in S <sub>ocean</sub> were calculated from the mean annual GOBM outputs, and the observational products were used to provide confidence in the GOBM assessments (r <sup>2</sup> =0.85). Thick lines represent the multi-model mean. Observationally based products have been corrected for pre-industrial river carbon fluxes (0.62 PgC yr <sup>–1</sup> ) based on the average of estimates from [[#Jacobson--2007|Jacobson et al. (2007)]] and [[#Resplandy--2018|Resplandy et al. (2018)]] . '''(b)''' Mean decadal constraints and their confidence intervals for global ocean sink (S <sub>ocean</sub> ) of anthropogenic CO <sub>2</sub> using multiple independent or quasi-independent lines of evidence or methods for the period 1990–2019 (see Supplementary Materials Tables 5.SM.1 and 5.SM.2 for magnitudes, uncertainties and published sources). Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

The second assessment approach makes use of six independent methods to constrain the mean decadal ocean sink over the period 1990–2019 (Figure 5.8b). This provides a multi-decadal advance on the 1990–1999 decadal constraint from ( [[#Denman--2007|Denman et al., 2007]] ) that has been widely used as a model constraint for GOBMs used for the global carbon budget ( [[#Hauck--2020|Hauck et al., 2020]] ). The ''medium confidence'' attributed by this assessment of the global multi-decadal trend (Figure 5.8a) is further supported by the broad agreement in magnitude and trend of the decadal mean ocean CO <sub>2</sub> uptake with assessments that also include additional observations-based, independent methods such as ocean CO <sub>2</sub> inversion and atmospheric CO <sub>2</sub> and O <sub>2</sub> /N <sub>2</sub> measurements (Figure 5.8b; Supplementary Materials Tables 5.SM.1 and 5.SM.2).

Here we provide a third comparative assessment approach depicting the spatial coherence of ocean air–sea fluxes and storage rates of CO <sub>2</sub> as well as a quantitative assessment of both fluxes for the same period (1994–2007; Figure 5.9). Observation-based ''p'' CO <sub>2</sub> flux products show that emissions of natural CO <sub>2</sub> occur mostly in the tropics and high-latitude Southern Ocean, and that the uptake and storage of anthropogenic CO <sub>2</sub> occurs predominantly in the mid-latitudes (Chapter 9, Figure 5.9 and Cross-Chapter Box 5.3). Strong ocean CO <sub>2</sub> sink regions are those in the mid-latitudes associated with the cooling of poleward flowing subtropical surface waters as well as equatorward flowing sub-polar surface waters, both of which contribute to the formation of Mode, Intermediate and Deep water masses that transport anthropogenic CO <sub>2</sub> into the ocean interior on time scales of decades to centuries in both hemispheres ( [[IPCC:Wg1:Chapter:Chapter-9#9.2.2.3|Section 9.2.2.3]] and Figure 5.9; [[#DeVries--2014|DeVries, 2014]] ; [[#Gruber--2019b|Gruber et al., 2019b]] ; [[#Wu--2019|Wu et al., 2019]] ). The mean decadal scale magnitude and uncertainties of S <sub>ocean</sub> from net air sea fluxes (F <sub>net</sub> ) were calculated from an ensemble of six observational-based product reconstructions (Figure 5.9a) and the storage rates in the ocean interior derived from multiple ocean interior CO <sub>2</sub> datasets ( [[#Gruber--2019b|Gruber et al., 2019b]] ; Figure 5.9b). The cumulative CO <sub>2</sub> stored in the ocean interior from 1800 to 2007 has been estimated at 140 ±18 PgC ( [[#Gruber--2019b|Gruber et al., 2019b]] ). As reported in SROCC ( [[#5.2.2.3.1|Section 5.2.2.3.1]] ; [[#IPCC--2019b|IPCC, 2019b]] ), the net ocean CO <sub>2</sub> storage between 1994–2007 was 29 ± 4 PgC, which corresponds to a mean storage of 26 ± 5% of anthropogenic CO <sub>2</sub> emissions for that period ( [[#Gruber--2019b|Gruber et al., 2019b]] ). The resulting net annual storage rate of anthropogenic CO <sub>2</sub> , equivalent to S <sub>ocean</sub> for the period mid-1994 to mid-2007 is 2.2 ± 0.3 PgC yr <sup>–1</sup> , which is in very close agreement with the top-down air–sea flux estimate of S <sub>ocean</sub> of 2.1 ± 0.5 PgC yr <sup>–1</sup> from GOBMs and 1.9 ± 0.3PgC yr <sup>–1</sup> from ''p'' CO <sub>2</sub> -based observational products with the steady river carbon flux correction of 0.62 PgC yr <sup>–1</sup> for the same time period ( [[#Gruber--2019b|Gruber et al., 2019b]] ; [[#Hauck--2020|Hauck et al., 2020]] ). This close agreement between these independent ocean CO <sub>2</sub> sink estimates derived from air–sea fluxes and storage rates in the ocean interior support the ''medium confidence'' assessment that the ocean anthropogenic carbon storage rates continue to be determined by the ocean sink (S <sub>ocean</sub> ) in response to growing CO <sub>2</sub> emissions (Figure 5.9; [[#McKinley--2020|McKinley et al., 2020]] ).

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'''Figure 5.9 |''' '''Comparative regional characteristics of the mean decadal (1994–2007) sea-air CO''' <sub>2</sub> '''flux (Fnet) and ocean storage of anthropogenic CO''' <sub>2</sub> '''. (a)''' Regional source–sink characteristics for contemporary ocean air – sea CO <sub>2</sub> fluxes (F <sub>net</sub> ) derived from the ensemble of six observation-based products using Surface Ocean CO <sub>2</sub> ( [[IPCC:Wg1:Chapter:Atlas|Atlas]] (SOCAT)v6 observational dataset ( [[#Landschützer--2014|Landschützer et al., 2014]] ; [[#Rödenbeck--2014|Rödenbeck et al., 2014]] ; [[#Zeng--2014|Zeng et al., 2014]] ; [[#Bakker--2016|Bakker et al., 2016]] ; [[#Denvil-Sommer--2019|Denvil-Sommer et al., 2019]] ; [[#Gregor--2019|Gregor et al., 2019]] ; [[#Iida--2021|Iida et al., 2021]] ). Warm colours depict outgassing fluxes and black contours characterize the super-biomes defined from [[#Fay--2014|Fay and McKinley (2014)]] and adjusted by [[#Gregor--2019|Gregor et al. (2019)]] also used to calculate the variability in regional flux anomalies (Supplementary Materials Figure 5.SM.1); '''(b)''' The regional characteristics of the storage fluxes of CO <sub>2</sub> in the ocean interior for the same period ( [[#Gruber--2019b|Gruber et al., 2019b]] ). The dots reflect ocean areas where the 1-sigma standard deviation of Fnet from the six observational-based product reconstructions is larger than the magnitude of the mean. This reflects source–sink transition areas where the mean Fnet is small and more strongly influenced by spatial and temporal variability across the products. Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

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