*Lyuba Novi1, Annalisa Bracco2, Ito Takamitsu2, Yohei Takano3
(1.NOC, Liverpool, UK, 2.Georgia Tech, GA, USA, 3.BAS, Cambridge, UK)
Keywords:Oxygen variability, Stratification predictability , Information Entropy
In this work we explore the relationship between the oxygen (O2) content in the upper ocean (0-200m) and stratification in the North Pacific Ocean using four Earth system models (ESMs), an ocean hindcast simulation, and an ocean reanalysis. The variability and trends in oceanic O2 levels are influenced by the imbalance between biological demand and physical supply. The latter is mainly governed by ocean ventilation which facilitates the movement of oxygen-rich surface waters to the subsurface. In this context, isopycnic potential vorticity (IPV)—a quasi-conservative tracer related to density stratification, that can be derived from temperature and salinity data—is used as a dynamic indicator for ocean ventilation. The predictability potential of the IPV field is evaluated through its information entropy (IE). The results show a strong connection between O2 and IPV, with slightly higher predictability potential for IPV in the tropical Pacific—where the El Niño–Southern Oscillation takes place—compared to other areas of the basin. The increased predictability and the strong inverse correlation between O2 and stratification remain consistent across various models and datasets. At mid latitudes IPV has instead low predictability potential and its center of action is different from that of O2. Additionally, the locations of extreme events or hotspots may vary between the two fields, with a significant dependence on the model used, also in future projections. While these findings suggest that monitoring ocean O2 in the tropical Pacific could be feasible using a limited number of observational sites co-located with the more widespread IPV measurements, they also raise concerns about the reliability of the IPV–O2 relationship in extratropical regions. The proposed framework helps to contextualize and interpret O2 variability in relation to physical variability. It could be useful for analysing new observation-based data products derived from the BGC-Argo float array in conjunction with the more widely available traditional Argo data.