Ocean-atmosphere CO2 fluxes: Simulations with the ocean-ecosystem model FESOM2.1-REcoM2

• Main Authors: Gürses, Özgür, Oziel, Laurent, Zeising, Moritz, Sidorenko, Dmitry, Hauck, Judith
• Format: Conference Object
• Language: unknown
• Published: 2022
• Subjects: Sea ice
• Online Access: https://epic.awi.de/id/eprint/55997/; https://hdl.handle.net/10013/epic.755516d8-ff44-4b43-a4de-fbef1a4aa335

Being a vast carbon pool, ocean is an important component of the climate system. It absorbs not only the heat trapped by the greenhouse gasses in the atmosphere, but also a quarter of the anthropogenic carbon dioxide (CO2) emissions itself. Ocean carbon uptake, however, decreases the pH in seawater that has negative implications for marine life. Despite the progress over the last decades, observational data is still sparse in the global oceans. Moreover, there are still gaps in understanding key processes and relevant feedbacks of global ocean carbon source/sink in response to atmospheric CO2 scenarios. Marine biogeochemical models are helpful tools to bridge these gaps. In this study we coupled the Finite-volumE Sea ice-Ocean Model (FESOM2.1) to the Regulated Ecosystem Model (REcoM2). Compared to the previous version FESOM1.4-REcoM2, the model utilizes a new dynamical core based on a finite volume discretization instead of finite elements, but retains the biogeochemical part. Mocsy2.0 computes carbonate chemistry including water vapor correction. It operates on variable mesh resolution. Unlike standard structured-mesh ocean models, the mesh flexibility allows for a realistic representation of small-scale dynamics in key regions at affordable computational cost. Here we present an assessment of the ocean and biogeochemical states simulated with FESOM2.1-REcoM2 in a relatively low spatial resolution global configuration forced with JRA55-do atmospheric reanalysis. A bias present in the previous model version FESOM1.4-REcoM2 in annual mean global ocean-atmosphere CO2 flux can be significantly reduced. Besides, the computational efficiency is about 2-3 times higher than FESOM1.4-REcoM2. Thus, the new coupled model is a promising tool for ocean biogeochemical modelling applications.