Compensatory effects conceal large uncertainties in the modelled processes behind the relationship between the El Niño–Southern Oscillation (ENSO) and CO2

Abstract

Listen

Translate article

Abstract. A large fraction of the interannual variation in the global carbon cycle can be explained and predicted by the impact of the 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 models (ESMs). In this work, we look beyond the top-down ENSO–CO2 relationship by describing the characteristic ENSO–NBP pathways in 22 Coupled Model Intercomparison Project Phase 6 (CMIP6) ESMs. These pathways result from the configuration of three interacting processes that 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 exhibit very high uncertainty with regard to its magnitude, with a global NBP anomaly of −0.15 to −2.13 Pg C yr−1 per standardised El Niño event. The largest source of uncertainty lies in the differences in the sensitivity of NBP to climate. This uncertainty among the ESMs increases 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 for by ENSO strength. A similar phenomenon occurs regarding the distribution of ENSO-induced climate anomalies. We show that even models that agree on global NBP anomalies exhibit strong disagreement with regard to the contributions 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. These alternative ENSO–NBP pathways can lead to a false confidence in the reproduction of CO2 by assimilating the ocean and the dismissal of predictive performance offered through ENSO. We suggest improving 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 that could lead to a better representation of the processes driving interannual variability in the global carbon cycle.