Estimation of Arctic Air-Sea CO2 Fluxes by Inverse Methods: Use of OSSEs to Assess Atmospheric Sampling Strategies

Estimates of atmospheric CO₂ uptake by the Arctic Ocean over recent decades from multiple methods indicate accelerating regional carbon uptake (Yasunaka et  al. 2024). This trend is  attributed to such factors as regional climate-change impacts and associated sea-ice loss. Yasunaka et al. (2024) also note a significant range of uncertainty among the various model and data analysis methods that were employed to derive regional Arctic Ocean air-sea fluxes (e.g., from surface ocean pCO₂ products, ocean biogeochemical models, and atmospheric inversions). This highlights a need for more robust  flux estimation methods  involving expanded observational networks and improved modelling tools to enable more accurate quantification of regional fluxes and an improved prediction capability to estimate future changes in oceanic CO₂ uptake in the rapidly evolving Arctic.

In this analysis we employ the GEOSChem-Local Ensemble Transform Kalman Filter  inverse analysis system (Chen et al. 2021) to develop sets of Observing System Sampling Experiments (OSSEs) that assess alternative atmospheric CO₂ sampling strategies and observational network extensions towards improved estimates of Arctic Ocean air-sea CO₂ fluxes. We assess the performance of individual sampling strategies using a range of metrics applied to the atmospheric inversions; these include regional CO₂ flux error reductions  and model concentration biases at sampling sites.