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

To calculate the direction and rate of carbon dioxide gas (CO2) exchange between the ocean and atmosphere, it is critical to know the partial pressure of CO2 in surface seawater (pCO2(sw)). Over the last decade, a variety of data products of global monthly pCO2(sw) have been produced, primarily for the open ocean on 1° latitude by 1° longitude grids. More recently, monthly products of pCO2(sw) that are more finely spatially resolved in the coastal ocean have been made available. A remaining challenge in the development of pCO2(sw) products is the robust characterization of seasonal variability, especially in nearshore coastal environments. Here we present a monthly data product of pCO2(sw) at 0.25° latitude by 0.25° longitude resolution in the Northeast Pacific Ocean, centered around the California Current System (CCS). The data product (RFR-CCS; Sharp et al., 2021; https://doi.org/10.5281/zenodo.5523389) was created using the most recent (2021) version of the Surface Ocean CO2 Atlas (Bakker et al., 2016) from which pCO2(sw) observations were extracted and fit against a variety of 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 moored autonomous surface platforms, and find that the data product effectively captures seasonal pCO2(sw) cycles at nearshore mooring sites. This result is notable because alternative global products for the coastal ocean do not capture local variability effectively in this region. 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 pCO2(sw) gradients seen in RFR-CCS reconstructions of pCO2(sw).

Sharp J. D., Fassbender A. J., Carter B. R., Lavin P. D. & Sutton A. J., 2021. A monthly surface pCO2 product for the California Current Large Marine Ecosystem. Earth System Science Data Discussions. Article.


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