Seasonal variability of the aragonite saturation state (ΩAR) in the upper (50 m and 100 m depths) North Pacific Ocean (NPO) was investigated using multiple linear regression (MLR). The MLR algorithm derived from a high-quality carbon dataset accurately predicted the ΩAR of evaluation datasets (three time-series stations and P02 section) with acceptable uncertainty (<0.1 ΩAR). The algorithm was combined with seasonal climatology data, and the estimated ΩAR varied in the range of 0.4–0.6 in the mid-latitude western NPO, with the largest variation found for the tropical eastern NPO. These marked variations were largely controlled by seasonal changes in vertical mixing and thermocline depth, both of which determine the degree of entrainment of CO2-rich corrosive waters from deeper depths. Our MLR-based subsurface ΩAR climatology is complementary to surface climatology based on pCO2 measurements.

Kim T.-W., Park G.-H., Kim D., Lee K., Feely R. A. & Millero F. J., in press. Seasonal variations in the aragonite saturation state in the upper open-ocean waters of the North Pacific Ocean. Geophysical Research Letters. Article(subscription required).