Compensatory effects conceal large uncertainties in the modelled processes behind the ENSO-CO₂ relationship

Abstract. A large fraction of the interannual variations in the global carbon cycle can be explained and predicted by the impact of El Niño Southern Oscillation (ENSO) on net biome production (NBP). It is therefore crucial that the relationship between ENSO and NBP is correctly represented in Earth system model (ESMs). With this work, we look beyond the top-down ENSO-CO₂ relationship in 22 CMIP6 ESMs by describing their characteristic ENSO-NBP pathways. These pathways result from the configuration of three interacting processes which contribute to the overall ENSO-CO₂ relationship: ENSO-strength, ENSO-induced climate anomalies, and the sensitivity of NBP to climate. The analysed ESMs agree on the direction of the sensitivity of global NBP to ENSO, but have very large uncertainty in its magnitude, with a global NBP anomaly of -0.15 PgC yr^-1 to -2.13 PgC yr^-1 per standardised El Niño event. The largest source of uncertainty is the differences in the sensitivity of NBP to climate. The uncertainty among the ESMs grows even further when only the differences in NBP sensitivity to climate are considered. This is because differences in the climate sensitivity of NBP are partially compensated by ENSO strength. There is a similar phenomenon regarding the distribution of ENSO-induced climate anomalies. We show that even model that agree on global NBP anomalies have strong disagreements in the contribution of different regions to the global anomaly. This analysis shows, that while ESMs can have a comparable ENSO-induced CO₂ anomaly, the carbon fluxes contributing to this anomaly originate from different regions and are caused by different drivers. The consequence of these alternative ENSO-NBP pathways can be a false confidence in the reproduction of CO₂ by assimilating the ocean, and the dismissal of predictive performance offered through ENSO. We suggest to improve the underlying processes by using large-scale carbon flux data for model tuning in order to capture the ENSO-induced NBP anomaly patterns. The increasing availability of carbon flux data from atmospheric inversions and remote sensing products makes this a tangible goal and would lead to a better representation of the processes driving the interannual variability of the global carbon cycle.