Assessing the Observational Uncertainties of Dissolved Oxygen Climatology and Seasonal Cycle Through a Coordinated Intercomparison Project

Abstract Uncertainties in global ocean oxygen inventories are assessed by a coordinated intercomparison of dissolved oxygen inventories derived from two observational data sets with distinct quality control (QC) protocols and five different statistical interpolation methods. We investigate key sources of uncertainty including mapping interpolation schemes and data QC methods, which contribute more significantly than measurement or sampling errors. Local differences in mapped oxygen content can reach up to 10 μmol/kg (about 4% of the surface climatological mean), especially in the regions of high variability and poor sampling such as the eastern tropical Pacific and the coastal Antarctica. Globally integrated differences, however, are small (≤0.17% above 2,000 m depth). Mapping methods are likely the largest contributor of the uncertainty for the annual mean, but both mapping and QC methods are important for the seasonal cycle. These results are limited by only including two sets of QC methods and only statistical interpolation techniques. Future incorporation of machine learning‐based methods and time‐dependent oxygen maps will be critical for tracking deoxygenation trends and for providing observational constraints to validate Earth System Models.