A monthly surface pCO2 product for the California Current Large Marine Ecosystem.

A common strategy for calculating the direction and rate of carbon dioxide gas (CO 2) exchange between the ocean and atmosphere relies on knowledge of the partial pressure of CO 2 in surface seawater (p CO 2(sw)), a quantity that is frequently observed by autonomous sensors on ships and moored buoys, albeit with significant spatial and temporal gaps. Here we present a monthly gridded data product of p CO 2(sw) at 0.25 ∘ latitude by 0.25 ∘ longitude resolution in the northeastern Pacific Ocean, centered on the California Current System (CCS) and spanning all months from January 1998 to December 2020. The data product (RFR-CCS; Sharp et al., 2022; 10.5281/zenodo.5523389) was created using observations from the most recent (2021) version of the Surface Ocean CO 2 Atlas (Bakker et al., 2016). These observations were fit against a variety of collocated and contemporaneous satellite- and model-derived surface variables using a random forest regression (RFR) model. We validate RFR-CCS in multiple ways, including direct comparisons with observations from sensors on moored buoys, and find that the data product effectively captures seasonal p CO 2(sw) cycles at nearshore sites. This result is notable because global gridded p CO 2(sw) products do not capture local variability effectively in this region, suggesting that RFR-CCS is a better option than regional extractions from global products to represent p CO 2(sw) in the CCS over the last 2 decades. Lessons learned from the construction of RFR-CCS provide insight into how global p CO 2(sw) products could effectively characterize seasonal variability in nearshore coastal environments. We briefly review the physical and biological processes – acting across a variety of spatial and temporal scales – that are responsible for the latitudinal and nearshore-to-offshore p CO 2(sw) gradients seen in the RFR-CCS reconstruction of p CO 2(sw). RFR-CCS will be valuable for the validation of high-resolution models, the attribution of spatiotemporal carbonate system variability to physical and biological drivers, and the quantification of multiyear trends and interannual variability of ocean acidification. [ABSTRACT FROM AUTHOR]