Charting Riverine Carbon’s Impact on the Global Ocean with a data-assimilative model
ECCO‑Darwin is a pioneering, data‑assimilative global ocean model that couples ocean physics and biogeochemistry. Yet until now, it lacked a key piece of the puzzle: lateral fluxes of carbon and nutrients from land. In this study, I addressed this gap by integrating global datasets of freshwater runoff (JRA55‑do) and watershed‑derived loads of carbon, nitrogen, and silica from Global NEWS 2 into the model’s coastal boundaries.

With these new inputs, I ran a series of sensitivity experiments on high‑performance computing clusters, generating terabytes of output to assess how riverine fluxes affect air–sea CO₂ exchange and net primary production across the global ocean from 2000–2019. Results show that riverine carbon inputs drive additional outgassing (+0.22 Pg C yr⁻¹), while accompanying nutrients support enhanced biological uptake (–0.17 Pg C yr⁻¹), yielding a net global CO₂ outgassing of roughly +0.03 Pg C yr⁻¹. I compared these outcomes with state‑of‑the‑art observational data products for pCO₂ and CO₂ fluxes, providing a robust, data‑constrained view of land–ocean coupling.
This work highlights the critical role of lateral inputs in global ocean biogeochemistry, advances the ECCO‑Darwin framework, and underscores the value of high‑performance computing and data‑model integration for understanding and managing the Earth’s changing climate.
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