the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 Mar 2024
An optimal transformation method applied to diagnosing the ocean carbon sink
Abstract. The ocean carbon sink plays a critical role in climate, absorbing anthropogenic carbon from the atmosphere and mitigating climate change. The sink shows significant variability on decadal timescales, but estimates from models and observations disagree with one another, raising uncertainty over the magnitude of the sink, its variability, and its driving mechanisms. There is a need to reconcile observationally-based estimates of air-sea CO2 fluxes with those of the changing ocean carbon inventory in order to improve our understanding of the sink, and doing so requires knowledge of how carbon is transported within the interior by the ocean circulation. Here we employ a recently developed Optimal Transformation Method (OTM) that uses water mass theory to relate interior changes in tracer distributions to transports and mixing and boundary forcings, and extend its application to include carbon using synthetic data. We validate the method using model outputs from a biogeochemical state estimate, and test its ability to recover boundary carbon fluxes and interior transports consistent with changes in heat, salt and carbon. Our results show that OTM effectively reconciles boundary carbon fluxes with interior carbon distributions when given a range of prior fluxes. OTM shows considerable skill in its reconstructions, reducing root-mean-squared errors from biased priors between model ‘truth’ and reconstructed boundary carbon fluxes by up to 71 %, with bias of the reconstructions consistently ≤ 0.06 mol-Cm−2 yr−1 globally. Inter-basin transports of carbon also compare well with the model truth, with residuals < 0.25 Pg C yr−1 for reconstructions produced using a range of priors. OTM has significant potential for application to reconciling observational estimates of air-sea CO2 fluxes with the interior accumulation of anthropogenic carbon.
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Status: open (until 08 May 2024)
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RC1: 'Comment on egusphere-2023-2448', Anonymous Referee #1, 03 Apr 2024
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Review invitation : 22-3-2024
Review accepted: 27-3-2024
Review sent: 3-4-2024
Review of the MS egusphere-2023-2448: An optimal transformation method applied to diagnosing the ocean carbon sink, by Neill Mackay et al.
General comment:
The air-sea exchange and oceanic cycle of carbon dioxide (CO2) is important in controlling the evolution of the climate and the chemistry (acidification). Significant progresses have been made over the last 10 years or so in observing, understanding and developing methods (models and data-based approaches) to quantify the ocean CO2 sink and its temporal variation. It is now well established that the global ocean is a major sink for CO2 but there are still uncertainties on the inter-annual to decadal scales and on the processes that drive the change of CO2 in both the surface and at depth. Detecting and understanding the drivers of ocean properties is challenging given the climate change and associated multiple forcing (wind, circulation, warming, including volcanoes, e.g. Fay et al, 2023). Thanks to the synthesis of observations (e.g. GLODAP), the decadal change of DIC and anthropogenic CO2 (Cant) in the ocean is now estimated at global scale (e.g. Gruber et al, 2019; Müller et al 2023) although there are regions where the data are sparse and the origin of the changes and drivers uncertain, such as in the southern ocean and in the deep layers.
In this context, Neill Mackay and co-authors present a new method (OTM) to reconstruct ocean CO2 concentrations in surface and the water column. They describe the OTM that has been detailed by Zika and Taimoor (2023, paper in revision) for heat and freshwater budgets. Here they extend OTM for the carbon budget. Concerning the CO2 sink, as noted by the authors, there are uncertainties between model and most data-based products and their method, when applied with observations, is probably promising to understand the origin of the bias and interpreting the DIC and C* changes. For example, after year 2000 GOBMs simulate a CO2 sink lower compared to the data-products as identified in several GCB reports (Friedlingstein et al, 2020, 2022) and recently recalled in the RECCAP2 stories (De Vries et al, 2023; Terhaar et al, 2024).
The introduction of the submitted paper is clear, results well presented, figures and references adapted. I am not specialist of the OTM method but I think compared to previous method dedicated to surface fields (e.g. Rodenbeck et al, 2015; Watson et al, 2020 among other) this offers a new view, especially in the water column including internal carbon transport.
The results, here based on the ECCO model, are convincing and I wondered how this could be applied to real world with observations. Quoting authors: “Once validated, OTM’s extension to carbon can be applied to observations to produce a globally consistent estimate of ocean carbon uptake, transports and mixing. ». It would be useful to inform the observations needed and that could be used for applying the OTM (data, periods, region…) and derived carbon change at global scale.
The paper is pleasant to read and probably suitable for publication in GMD once the paper from Zika and Taimoor (2023, submitted) is accepted in the same journal. Below are listed specific comments.
Specific comments:
C-01: Line 23: “…but with significant variability (Hauck et al., 2020).” Maybe also refer to De Vries et al (2023) and Terhaar et al (2024).
C-02: Line 25: “…have also suggested greater decadal variability and a steeper rate of increasing sink since the turn of the 21st century than GOBMs,”. Maybe recall that the difference could reach 1 PgC/yr (compared to 2.9 PgC/yr listed line 7).
C-03: Line 36: “The rate of change of the global inventory of Canth has been estimated at 2.6 ± 0.3 PgCyr−1 for the period 1994-2007 (Gruber et al., 2019)”. Maybe also refer to Müller et al (2023) who estimate change from 1994 to 2004 by 29 ± 3 PgC/decade but to 27 ± 3 PgC/decade from 2004 to 2014 (i.e. a weakening of the uptake ?). Also, I think these estimates where calculated for the layer 0-3000m only, not the full depth, and these results should be extended to the bottom (as proposed using OTM).
C-04: Line 290: « This mismatch indicates that OTM is unable to recover the correct transports of carbon solely from information about the changes in temperature and salinity and associated boundary fluxes of heat and salt/freshwater ». This is an important result suggesting that for carbon one need to use apriori fluxes as well (correct ?).
C-05: Line 298: « The net inter-basin carbon transports from the case 2 OTM solution are shown on Fig. 8… ». Figure 8 and 9 show the total carbon transport for 1995-2015; could you also show the same for the difference between 1995-2005 and 2010-2015 to highlight the power of OTM to derive carbon budget changes?
C-06: Figure 8: Compared to the carbon transport from Mikaloff Fletcher et al (2007), there is a difference of the carbon flux in the Indian Ocean and at the Indonesian throughflow. On Line 145 you informed that “the Indonesian throughflow is set to a net transport of 15 Sv westwards, based on volume transports from ECCO-Darwin ». Mikaloff Fletcher et al (2007) showed a natural carbon flux toward the Pacific whereas Mikaloff Fletcher et al (2006) presented a Cant flux toward the Indian Ocean. Could you comment ?
C-07: Line 350: « the method therefore does not resolve either tracer or flux gradients within a water mass. The effect of the latter is illustrated on Fig. 5, where we compare the unaltered ECCO-Darwin boundary carbon fluxes with the result of binning the fluxes into water mass space and then remapping them back into geographical coordinates using a mask ». Maybe specify where the large differences occur: e.g. NE-PAC, SE-PAC, SO-ATL and Indian (source versus sink ?). Would those differences be the same when applying OTM with observations?
C-08: Line 370: « for example in the case of the South Pacific/Indian Ocean, it could be beneficial to further split the Southern Ocean in a manner that allows the imposition of an Antarctic Circumpolar Current. ». A suggestion for future analysis: select the Drake Passage for the transport using observations available at this boundary (Meredith et al, 2011; Munro et al, 2015)?
C-09: Line 407: « We are working on producing our own global, full-depth, time-evolving estimates of DIC and C∗ in the ocean, using machine learning with satellite and GLODAP data, which we hope by combining with OTM will enable us to produce the first global estimate of the uptake, transport and storage of carbon directly from observations. ». Why not starting/testing OTM using MOBO-DIC (Keppler et al)? Is the MOBO-DIC period 2004-2017 too short to test OTM and because MOBO-DIC is not extended to the bottom? Is your new global data-based product already developed? Could you specify the data that would be needed for applying OTM (T, AT, DIC, O2, nutrients, other ?). Are the existing data synthesis available enough for your future analysis or would you recommend to extend GLODAP, SOCAT, etc… ?
C-09: Figure 2: curiosity: what, where are the outliers at high salinity 38 (Red Sea, MedSea, Arabian Sea?)
C-10: Figure 5: In the legend maybe recall that (b) is for Case 2.
C-11: Title: “An optimal transformation method applied to diagnosing the ocean carbon sink.”
As there are also sources in some regions (EqPAC), maybe change the title: “An optimal transformation method applied to diagnosing the ocean carbon budget”.
;;;;;;;;; Reference in this review not listed in the MS
DeVries, T., Yamamoto, K., Wanninkhof, R., Gruber, N., Hauck, J., Müller, J. D., et al. (2023). Magnitude, trends, and variability of the global ocean carbon sink from 1985-2018. Global Biogeochemical Cycles, 37, e2023GB007780, doi:10.1029/2023GB007780
Fay, A. R., McKinley, G. A., Lovenduski, N. S., Eddebbar, Y., Levy, M. N., Long, M. C., Olivarez, H. C., and Rustagi, R. R.: Immediate and Long-Lasting Impacts of the Mt. Pinatubo Eruption on Ocean Oxygen and Carbon Inventories, Global Biogeochem. Cy., 37, e2022GB007513, https://doi.org/10.1029/2022GB007513, 2023.
Friedlingstein, P., et al: Global Carbon Budget 2020, Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, 2020.
Meredith, M. P., and Coauthors, 2011: Sustained monitoring of the Southern Ocean at Drake Passage: past achievements and future priorities. Rev. Geophys., 1-36.
Mikaloff Fletcher, et al: Inverse estimates of the oceanic sources and sinks of natural CO2 and the implied oceanic carbon transport, Global biogeochemical cycles, GB1010, doi:10.1029/2006GB002751, 2007
Müller, J. D., Gruber, N., Carter, B., Feely, R., Ishii, M., Lange, N., et al. (2023). Decadal trends in the oceanic storage of anthropogenic carbon from 1994 to 2014. AGU Advances, 4, e2023AV000875. https://doi.org/10.1029/2023AV000875
Munro,D. R., N. S. Lovenduski, T. Takahashi, B. B. Stephens, T. Newberger, and C. Sweeney (2015), Recent evidence for a strengthening CO2 sink in the Southern Ocean from carbonate system measurements in the Drake Passage (2002–2015), Geophys. Res. Lett., 42, doi:10.1002/2015GL065194.
Terhaar, J., Goris, N., Müller, J. D., DeVries, T., Gruber, N., Hauck, J., et al. (2024). Assessment of global ocean biogeochemistry models for ocean carbon sink estimates in RECCAP2 and recommendations for future studies. Journal of Advances in Modeling Earth Systems, 16, e2023MS003840. https://doi.org/10.1029/2023MS003840
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Citation: https://doi.org/10.5194/egusphere-2023-2448-RC1
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