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. 2019 Jun 11;116(24):11646-11651.
doi: 10.1073/pnas.1900371116. Epub 2019 May 28.

Decadal trends in the ocean carbon sink

Tim DeVries  1   2 , Corinne Le Quéré  3 , Oliver Andrews  3   4 , Sarah Berthet  5 , Judith Hauck  6 , Tatiana Ilyina  7 , Peter Landschützer  7 , Andrew Lenton  8   9   10 , Ivan D Lima  11 , Michael Nowicki  12   2 , Jörg Schwinger  13 , Roland Séférian  5
Affiliations

Decadal trends in the ocean carbon sink

Tim DeVries et al. Proc Natl Acad Sci U S A. .

Abstract

Measurements show large decadal variability in the rate of [Formula: see text] accumulation in the atmosphere that is not driven by [Formula: see text] emissions. The decade of the 1990s experienced enhanced carbon accumulation in the atmosphere relative to emissions, while in the 2000s, the atmospheric growth rate slowed, even though emissions grew rapidly. These variations are driven by natural sources and sinks of [Formula: see text] due to the ocean and the terrestrial biosphere. In this study, we compare three independent methods for estimating oceanic [Formula: see text] uptake and find that the ocean carbon sink could be responsible for up to 40% of the observed decadal variability in atmospheric [Formula: see text] accumulation. Data-based estimates of the ocean carbon sink from [Formula: see text] mapping methods and decadal ocean inverse models generally agree on the magnitude and sign of decadal variability in the ocean [Formula: see text] sink at both global and regional scales. Simulations with ocean biogeochemical models confirm that climate variability drove the observed decadal trends in ocean [Formula: see text] uptake, but also demonstrate that the sensitivity of ocean [Formula: see text] uptake to climate variability may be too weak in models. Furthermore, all estimates point toward coherent decadal variability in the oceanic and terrestrial [Formula: see text] sinks, and this variability is not well-matched by current global vegetation models. Reconciling these differences will help to constrain the sensitivity of oceanic and terrestrial [Formula: see text] uptake to climate variability and lead to improved climate projections and decadal climate predictions.

Keywords: carbon budget; carbon dioxide; climate variability; ocean carbon sink; terrestrial carbon sink.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
(A) Global CO2 emissions from fossil-fuel-burning, cement production, and land-use change (FF+LUC) (red curve), compared with the measured rate of accumulation of CO2 in the atmosphere (gold curve) and the inferred rate of change of CO2 accumulation in the land and ocean (blue curve). Thin lines are annual means, and thick lines are 5-y running means. (B) Decadal trends in CO2 emissions (FF+LUC) and the atmospheric and total land+ocean sinks. For emissions, positive values indicate an increasing source and negative values a decreasing source (left-hand arrows; sign convention as in Eq. 1). For the atmosphere and land+ocean sinks, positive values indicate a decreasing sink and negative values an increasing sink (right-hand arrows; opposite the sign convention in Eq. 1). All data are from the 2017 Global Carbon Budget (3, 4). Error bars are 1-σ.
Fig. 2.
Fig. 2.
(A) Estimates of the ocean carbon sink from a subset of models participating in the SOCOM project (15), a subset of GOBMs participating in the 2017 Global Carbon Budget (3) and an OCIM with (24) and without (12) decadal variability in ocean circulation. Thick lines are the ensemble mean from each method, with shading representing one SD uncertainty. For the OCIM with variable circulation, the mean value at the end of each decade (1989, 1999, and 2009) is shown, with error bars representing one SD. For the OCIM with constant circulation, error bars are the ensemble range. SOCOM results have been adjusted for outgassing of riverine CO2 (Materials and Methods). (B) Decadal trends in the net (land+ocean) carbon sink (blue bar; same as in Fig. 1) and four estimates of decadal trends in the ocean carbon sink from SOCOM models (red bar), GOBMs (purple bar), and OCIM with decadal variability in ocean circulation (gold bar) and without any variability in ocean circulation (dashed line).
Fig. 3.
Fig. 3.
Decadal trends in ocean carbon uptake for the global ocean (A) and for different ocean regions (B–F) as defined by the biomes of refs. and (see SI Appendix for biome definitions and definitions of the models used here). (B) Southern Ocean. (C) North Atlantic. (D) North Pacific. (E) Low-latitude Atlantic. (F) Low-latitude Pacific + Indian. The global ocean in A is the sum of the regions in B–F and does not include coastal regions and marginal seas. Trends and color-coding are as in Fig. 2B, with symbols representing individual models. Positive trends represent a weakening oceanic CO2 sink and negative trends a strengthening oceanic CO2 sink.
Fig. 4.
Fig. 4.
Decadal trends in ocean carbon uptake simulated by GOBMs for the regions in Fig. 3. (A) Global ocean. (B) Southern Ocean. (C) North Atlantic. (D) North Pacific. (E) Low-latitude Atlantic. (F) Low-latitude Pacific + Indian. Shown separately are the trends due to both CO2 and climate variability (blue bar; same as purple bar in Fig. 3), trends due to CO2 variability only (red bar), and trends due to climate variability only (gold bar). Error bars are one SD of the model ensemble mean. Symbols represent results from individual models as defined in Fig. 3.
Fig. 5.
Fig. 5.
Trends in the terrestrial CO2 sink calculated as a residual from the global carbon budget (Eq. 1) using the estimates of the ocean CO2 sink from three methods considered here (GOBMs, SOCOM, and OCIM with variable circulation) and from the DGVMs participating in the 2017 Global Carbon Budget (3). See SI Appendix for definitions of DGVMs used here.
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