Can We Estimate Air‐Sea Flux of Biological O2 From Total Dissolved Oxygen?

Abstract

AbstractIn this study, we compare mechanistic and empirical approaches to reconstruct the air‐sea flux of biological oxygen () by parameterizing the physical oxygen saturation anomaly (ΔO2[phy]) in order to separate the biological contribution from total oxygen. The first approach matches ΔO2[phy] to the monthly climatology of the argon saturation anomaly from a global ocean circulation model's output. The second approach derives ΔO2[phy] from an iterative mass balance model forced by satellite‐based physical drivers of ΔO2[phy] prior to the sampling day by assuming that air‐sea interactions are the dominant factors driving the surface ΔO2[phy]. The final approach leverages the machine‐learning technique of Genetic Programming (GP) to search for the functional relationship between ΔO2[phy] and biophysicochemical parameters. We compile simultaneous measurements of O2/Ar and O2 concentration from 14 cruises to train the GP algorithm and test the validity and applicability of our modeled ΔO2[phy] and . Among the approaches, the GP approach, which incorporates ship‐based measurements and historical records of physical parameters from the reanalysis products, provides the most robust predictions (R2 = 0.74 for ΔO2[phy] and 0.72 for ; RMSE = 1.4% for ΔO2[phy] and 7.1 mmol O2 m−2 d−1 for ). We use the empirical formulation derived from GP approach to reconstruct regional, inter‐annual, and decadal variability of based on historical oxygen records. Overall, our study represents a first attempt at deriving from snapshot measurements of oxygen, thereby paving the way toward using historical O2 data and a rapidly growing number of O2 measurements on autonomous platforms for independent insight into the biological pump.