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

• Published in: Earth System Science Data
• Main Authors: Gregor, Luke, Gruber, Nicolas
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus GmbH
• Subjects: geo; envir; Ocean acidification
• Online Access: https://doi.org/10.5194/essd-13-777-2021; https://archimer.ifremer.fr/doc/00683/79538/82214.pdf; https://archimer.ifremer.fr/doc/00683/79538/82216.pdf; https://archimer.ifremer.fr/doc/00683/79538/

Ocean acidification has profoundly altered the ocean's carbonate chemistry since preindustrial times, with potentially serious consequences for marine life. Yet, no long-term, global observation-based data set exists that allows us 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 a 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 (code available at https://doi.org/10.5281/zenodo.4455354, Gregor, 2021). This method is based on a two-step (cluster-regression) approach but extends it by considering an ensemble of such cluster regressions, leading to improved 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 uncertainty 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, as well as root mean squared errors of 0.023 and 16 µmol kg−1, respectively. These uncertainties are very comparable to those expected by ...