The seasonal cycle as a mode to diagnose biases in modelled CO2 fluxes in the Southern Ocean

• Examined the seasonal cycle of CO2 fluxes for observations and an ocean model.
• Proposed a framework to diagnose the drivers behind these differences.
• Explained seasonal cycle anomalies by comparing the rates of change of SST and DIC.
• SST was driver of seasonal cycle pCO2 in the model whereas DIC regulated it in the data.
• Diagnosed the dynamics of the CO2 fluxes and complementary to Taylor diagrams.

The Southern Ocean forms a key component of the global carbon budget, taking up about 1.0 Pg C yr−1 of anthropogenic CO2 emitted annually (∼10.7 ± 0.5 Pg C yr−1 for 2012). However, despite its importance, it still remains undersampled with respect to surface ocean carbon flux variability, resulting in weak constraints for ocean carbon and carbon – climate models. As a result, atmospheric inversion and coupled physics-biogeochemical ocean models still play a central role in constraining the air-sea CO2 fluxes in the Southern Ocean. A recent synthesis study (Lenton et al., 2013a), however, showed that although ocean biogeochemical models (OBGMs) agree on the mean annual flux of CO2 in the Southern Ocean, they disagree on both amplitude and phasing of the seasonal cycle and compare poorly to observations. In this study, we develop and present a methodological framework to diagnose the controls on the seasonal variability of sea-air CO2 fluxes in model outputs relative to observations. We test this framework by comparing the NEMO-PISCES ocean model ORCA2-LIM2-PISCES to the Takahashi 2009 (T09) CO2 dataset. Here we demonstrate that the seasonal cycle anomaly for CO2 fluxes in ORCA2LP is linked to an underestimation of winter convective CO2 entrainment as well as the impact of biological CO2 uptake during the spring-summer season, relative to T09 observations. This resulted in sea surface temperature (SST) becoming the dominant driver of seasonal scale of the partial pressure of CO2 (pCO2) variability and hence of the differences in the seasonality of CO2 sea-air flux between the model and observations.