Evolution of oxygen and stratification in the North Pacific Ocean in CMIP6 Earth System Models

Abstract. This study examines the linkages between the upper ocean (0–200 m) oxygen (O₂) content and stratification in the North Pacific Ocean in four Earth system models (ESMs), an ocean hindcast simulation, and ocean reanalysis data. Trend and variability of oceanic O₂ content are driven by the imbalance between physical supply and biological demand. The physical supply is primarily controlled by ocean ventilation, which is responsible for the transport of O₂-rich surface waters into subsurface. To quantify the ocean ventilation, Isopycnic Potential Vorticity (IPV) is used as a dynamical proxy in this study. IPV is a quasi-conservative tracer proportional to density stratification, which can be interpreted as a proxy for ocean ventilation and can be evaluated from temperature and salinity measurements alone. The predictability potential of the IPV field is evaluated through its information entropy. Results highlight a strong O₂-IPV connection and somewhat higher (than in rest of the basin) predictability potential for IPV in the tropical Pacific, in the area strongly affected by the El Niño Southern Oscillation. This pattern of higher predictability and strong anticorrelation between O₂ and stratification is robust across multiple models and datasets. In contrast, the variability of IPV at mid-latitudes has low predictability potential and its center of action differs from that of O₂. In addition, the locations of extreme events or hotspots may or may not differ among the two fields, with a strong model dependency, which persists in future projections. These results, on one hand, suggest the possibility to monitor ocean O₂ through few observational sites co-located with some of the more abundant IPV measurements in the tropical Pacific, and, on the other, question the robustness of the IPV-O₂ relationship in the extra-tropics. The proposed framework helps characterizing and interpreting O₂ variability in relation to physical variability and may be especially useful in the analysis of new observationally-based data products derived from the BGC-ARGO float array in combination with the traditional but far more abundant ARGO data.