Calibrating ocean biogeochemistry (BGC) parameters in Earth System Models is challenging because there are multiple sources of error, and the parameters' sensitivities are interlinked. Reducing the bias in the ocean physical component of the Norwegian Earth System Model (NorESM) diminishes the BGC state bias at intermediate depth but leads to a greater bias increase near the surface. This suggests that BGC parameters are currently tuned to compensate for the ocean physics biases. We successfully apply the iterative ensemble smoother data assimilation technique to re-calibrate BGC parameters in NorESM with reduced bias in its ocean physics component.  We calibrated BGC parameters from the monthly climatological error of nitrate, phosphate, and oxygen in a coupled reanalysis of NorESM that assimilates monthly climatology of temperature and salinity.  First, we compare the performance of globally and spatially varying parameter estimations. Both approaches reduce BGC bias obtained with default parameters, even for variables not assimilated in the parameter estimation (such as CO2 fluxes and primary production). While spatial parameter estimation performs locally best, it also increases biases in areas with few observations, and overall performs poorer than global parameter estimation. A second iteration further reduces the bias in the near-surface BGC with global parameter estimation. Finally, we verify the global estimated parameters in a 30-year coupled reanalysis, which assimilates time-varying temperature and salinity observations. This reanalysis reduces error by  10-20% for phosphate, nitrate, oxygen, and dissolved inorganic carbon compared to a reanalysis done with default parameters.  

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.