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https://doi.org/10.5194/essd-2020-300
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2020-300
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  22 Oct 2020

22 Oct 2020

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This preprint is currently under review for the journal ESSD.

OceanSODA-ETHZ: A global gridded data set of the surface ocean carbonate system for seasonal to decadal studies of ocean acidification

Luke Gregor and Nicolas Gruber Luke Gregor and Nicolas Gruber
  • Environmental Physics, Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, 8092 Zürich, Switzerland

Abstract. Ocean acidification has altered the ocean's carbonate chemistry profoundly since preindustrial times, with potentially serious consequences for marine life. Yet, no long-term global observation-based data set exists that permits to study changes in ocean acidification for all carbonate system parameters over the last few decades. Here, we fill this gap and present a methodologically consistent global data set of all relevant surface ocean parameters, i.e., dissolved inorganic carbon (DIC), total alkalinity (TA), partial pressure of CO2 (pCO2), pH, and the saturation state with respect to mineral CaCO3 (Ω) at monthly resolution over the period 1985 through 2018 at a spatial resolution of 1 × 1°. This data set, named OceanSODA-ETHZ, was created by extrapolating in time and space the surface ocean observations of pCO2 (from the Surface Ocean CO2 ATlas (SOCAT)) and total alkalinity (TA, from the Global Ocean Data Analysis Project (GLODAP)) using the newly developed Geospatial Random Cluster Ensemble Regression (GRaCER) method. This method is based on a two-step (cluster-regression) approach, but extends it by considering an ensemble of such cluster-regressions, leading to higher robustness. Surface ocean DIC, pH, and Ω were then computed from the globally mapped pCO2 and TA using the thermodynamic equations of the carbonate system. For the open ocean, the cluster regression method estimates pCO2 and TA with global near-zero biases and root mean squared errors of 12 µatm and 13 µmol kg−1, respectively. Taking into account also the measurement and representation errors, the total error increases to 14 µatm and 21 µmol kg−1, respectively. We assess the fidelity of the computed parameters by comparing them to direct observations from GLODAP, finding surface ocean pH and DIC global biases of near zero, and root mean squared errors of 0.023 and 16 µmol kg−1, respectively. These errors are very comparable to those expected by propagating the total errors from pCO2 and TA through the thermodynamic computations, indicating a robust and conservative assessment of the errors. We illustrate the potential of this new dataset by analyzing the climatological mean seasonal cycles of the different parameters of the surface ocean carbonate system, highlighting their commonalities and differences. The OceanSODA-ETHZ data can be downloaded from https://doi.org/10.25921/m5wx-ja34 (Gregor and Gruber, 2020).

Luke Gregor and Nicolas Gruber

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Luke Gregor and Nicolas Gruber

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OceanSODA-ETHZ: A global gridded data set of the surface ocean carbonate system for seasonal to decadal studies of ocean acidification (NCEI Accession 0220059) Luke Gregor and Nicolas Gruber https://doi.org/10.25921/m5wx-ja34

Luke Gregor and Nicolas Gruber

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Short summary
Ocean acidification (OA) has altered the ocean’s carbonate chemistry, with consequences for marine life. Yet, no observation-based data set exists that permits to study changes in OA. We fill this gap with a global data set of relevant surface ocean parameters over the period 1985–2018. This data set, OceanSODA-ETHZ, was created by using satellite and other data to extrapolate ship-based measurements of carbon dioxide and total alkalinity from which parameters for OA were computed.
Ocean acidification (OA) has altered the ocean’s carbonate chemistry, with consequences for...
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