Abstract
Abstract. The temporal variability of the sea surface partial pressure of CO2 (pCO2) and the underlying processes driving this variability are poorly understood in the coastal ocean. In this study, we tailor an existing method that quantifies the effects of thermal changes, biological activity, ocean circulation and freshwater fluxes to examine seasonal pCO2 changes in highly variable coastal environments. We first use the Modular Ocean Model version 6 (MOM6) and biogeochemical module Carbon Ocean Biogeochemistry And Lower Trophics version 2 (COBALTv2) at a half-degree resolution to simulate coastal CO2 dynamics and evaluate them against pCO2 from the Surface Ocean CO2 Atlas database (SOCAT) and from the continuous coastal pCO2 product generated from SOCAT by a two-step neuronal network interpolation method (coastal Self-Organizing Map Feed-Forward neural Network SOM-FFN, Laruelle et al., 2017). The MOM6-COBALT model reproduces the observed spatiotemporal variability not only in pCO2 but also in sea surface temperature, salinity and nutrients in most coastal environments, except in a few specific regions such as marginal seas. Based on this evaluation, we identify coastal regions of “high” and “medium” agreement between model and coastal SOM-FFN where the drivers of coastal pCO2 seasonal changes can be examined with reasonable confidence. Second, we apply our decomposition method in three contrasted coastal regions: an eastern (US East Coast) and a western (the Californian Current) boundary current and a polar coastal region (the Norwegian Basin). Results show that differences in pCO2 seasonality in the three regions are controlled by the balance between ocean circulation and biological and thermal changes. Circulation controls the pCO2 seasonality in the Californian Current; biological activity controls pCO2 in the Norwegian Basin; and the interplay between biological processes and thermal and circulation changes is key on the US East Coast. The refined approach presented here allows the attribution of pCO2 changes with small residual biases in the coastal ocean, allowing for future work on the mechanisms controlling coastal air–sea CO2 exchanges and how they are likely to be affected by future changes in sea surface temperature, hydrodynamics and biological dynamics.
Highlights
The ocean plays an important role in offsetting humaninduced carbon dioxide (CO2) emissions associated with cement production and fossil fuel combustion (Friedlingstein et al, 2019)
Our analysis reveals that the seasonal amplitudes simulated by Modular Ocean Model version 6 (MOM6)-COBALT are systematically larger than the ones estimated by the coastal SOM-FFN product (Fig. 5a– b, red colors in Fig. 5c and positive biases in Table S2) for all coastal regions belonging to EBC, WBC, and Indian and tropical margins
An Oceanic General Circulation Model (OGCM) (MOM6-COBALT) that is primarily designed for the open ocean was used to examine sea surface pressure of CO2 (pCO2) seasonality in the coastal domain
Summary
The ocean plays an important role in offsetting humaninduced carbon dioxide (CO2) emissions associated with cement production and fossil fuel combustion (Friedlingstein et al, 2019). The ocean is a net sink that absorbs roughly one-quarter of the anthropogenic CO2 emitted into the atmosphere (−2.5 ± 0.6 petagram of carbon per year (Pg C yr−1) for the 2009–2018 decade, Friedlingstein et al, 2019). Roobaert et al.: A framework to evaluate and elucidate the driving mechanisms of It is less constrained and understood in the coastal ocean. In recent decades, significant progress has been made with regard to the quantification and analysis of the spatial distribution of the coastal air–sea CO2 exchange (F CO2) globally and regionally (e.g., Borges et al, 2005; Cai, 2011; Chen et al, 2013; Laruelle et al, 2010, 2014; Roobaert et al, 2019). A more in-depth analysis revealed that the majority of the coastal seasonal F CO2 variations stems from the air–sea gradient in partial pressure of CO2 (pCO2), changes in wind speed and sea ice cover can be significant regionally
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