Model data for: Drawdown of atmospheric pCO2 via dynamic particle export stoichiometry in the ocean twilight zone
Cite this dataset
Tanioka, Tatsuro; Matsumoto, Katsumi (2021). Model data for: Drawdown of atmospheric pCO2 via dynamic particle export stoichiometry in the ocean twilight zone [Dataset]. Dryad. https://doi.org/10.5061/dryad.70rxwdbxq
Understanding the global carbon cycle is key to understanding the climate system. One of the large unknowns is the processes happening in the twilight zone of the ocean. Here, we focus on how elemental stoichiometry of particulate organic matter in the twilight zone affects the strength of the biological pump and atmospheric CO2. We show through modeling that atmospheric CO2 is very sensitive to the change in C:P ratio in the twilight zone. Numerous model studies study the link between the carbon cycle and flexible elemental stoichiometry of organic matter in the surface ocean. However, our model study is unique. It investigates the effects of stoichiometric changes both at the surface and in the subsurface ocean that also involve stoichiometric interaction between phytoplankton and zooplankton.
We use a 3D numerical model to illustrate how C:P variability in the twilight zone can significantly modulate the strength of carbon sequestration and atmospheric CO2. We used the biogeochemical model MOPS (Kriest and Oschlies, Geosci. Model Dev., 8, 2929–2957, 2015) coupled to ECCO Transport Matrices.
This repository contains model input and output files for each sensitivity run outlined in the paper. The run ID corresponds to different sensitivity run. See README for more details.
National Science Foundation, Award: OCE‐1827948