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

TLDR: Gregor et al. as mentioned in this paper presented a methodologically consistent global data set of all relevant surface ocean parameters, i.e., dissolved inorganic carbon (DIC), total alkalinity (TA), partial pressure of CO 2 ( pCO2 ), pH, and the saturation state with respect to mineral CaCO 3 ( Ω ) at a monthly resolution over the period 1985 through 2018 at a spatial resolution of 1 ∘ × 1 √.

Abstract: . 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 CO 2 ( pCO2 ), pH, and the saturation state with respect to mineral CaCO 3 ( 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 CO 2 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  µ atm and 13  µ mol kg −1 , respectively. Taking into account also the measurement and representation errors, the total uncertainty increases to 14  µ atm and 21  µ mol 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  µ mol kg −1 , respectively. These uncertainties are very comparable to those expected by propagating the total uncertainty from pCO2 and TA through the thermodynamic computations, indicating a robust and conservative assessment of the uncertainties. We illustrate the potential of this new data set by analyzing the climatological mean seasonal cycles of the different parameters of the surface ocean carbonate system, highlighting their commonalities and differences. Further, this data set provides a novel constraint on the global- and basin-scale trends in ocean acidification for all parameters. Concretely, we find for the period 1990 through 2018 global mean trends of 8.6  ±  0.1  µ mol kg −1 per decade for DIC, − 0.016  ±  0.000 per decade for pH, 16.5  ±  0.1  µ atm per decade for p CO 2 , and − 0.07  ±  0.00 per decade for Ω . The OceanSODA-ETHZ data can be downloaded from https://doi.org/10.25921/m5wx-ja34 ( Gregor and Gruber ,  2020 ) .