Improved ocean biogeochemistry (BGC) parameters in Earth System Models can enhance the representation of the global carbon cycle. We aim to demonstrate the potential of parameter estimation (PE) using an ensemble data assimilation method to optimise five key BGC parameters within the Norwegian Earth System Model (NorESM). The optimal BGC parameter values are estimated with an iterative ensemble smoother technique, applied a-posteriori to the error of monthly climatological estimates of nitrate, phosphate and oxygen produced by a coupled reanalysis that assimilates monthly ocean physical observed climatology. Reducing the ocean physics biases while keeping the default parameters (DP) initially reduces BGC state bias in the intermediate depth but deteriorates near the surface, suggesting that the DP are tuned to compensate for physical biases. Globally uniform and spatially varying estimated parameters from the first iteration effectively mitigate the deterioration and reduce BGC errors compared to DP, also for variables not used in the PE (such as C0$_2$ fluxes and primary production). While spatial PE performs superior in specific regions, global PE performs best overall. A second iteration can further improve the performance of global PE for near-surface BGC variables. Finally, we assess the performance of the global estimated parameters in a 30-year coupled reanalysis, assimilating time-varying temperature and salinity observations. It reduces error by 20\%, 18\%, 7\%, and 27\% for phosphate, nitrate, oxygen, and dissolved inorganic carbon, respectively, compared to the default version of NorESM. The proposed PE approach is a promising innovative tool to calibrate ESM in the future.

A document by Pradeebane VAITTINADA''AYAR. Click on the document to view its contents.

Anthropogenic climate change footprints in the ocean go beyond the mixed layer depth, with considerable impacts throughout mesopelagic and deep-ocean ecosystems. Yet, little is known about the timing of these environmental changes, their spatial extent, and the associated timescales of recovery in the ocean interior when strong mitigation strategies are involved. Here, we simulate idealized rapid climate change and mitigation scenarios using the Norwegian Earth System Model (NorESM) to investigate timescales of climate change onset and recovery and the extent of change in the North Atlantic (NAtl) interior relative to Pre-industrial (PI) variability across a suite of environmental drivers (Temperature – T; pH; Dissolved Oxygen – DO; Apparent Oxygen Utilization - AOU; Export Production - EP; and Calcite saturation state - Ωc). We show that, below the subsurface domains, responses of these drivers are asymmetric and detached from the anthropogenic forcing with large spatial variations. Vast regions of the interior NAtl experience detectable anthropogenic signal significantly earlier and over a longer period than those projected for the subsurface. In contrast to surface domains, the NAtl interior remains largely warmer relative to PI (up to +50%) following the mitigation scenario, with anomalously lower EP, pH and Ωc (up to -20%) south of 30°N. Oxygenation in the upper mesopelagic of up to +20% is simulated, mainly driven by a decrease in consumption during remineralization. Our study highlights the need for long-term commitment focused on pelagic and deep-water ecosystem monitoring to fully understand the impact of anthropogenic climate change on the North Atlantic biogeochemistry.