Reconstructions and predictions of the global carbon budget with an emission-driven Earth system model

Abstract

Abstract. The global carbon budget (GCB) – including fluxes of CO2 between the atmosphere, land, and ocean and its atmospheric growth rate – show large interannual to decadal variations. Reconstructing and predicting the variable GCB is essential for tracing the fate of carbon and understanding the global carbon cycle in a changing climate. We use a novel approach to reconstruct and predict the variations in GCB in the next few years based on our decadal prediction system enhanced with an interactive carbon cycle. By assimilating physical atmospheric and oceanic data products into the Max Planck Institute Earth System Model (MPI-ESM), we are able to reproduce the annual mean historical GCB variations from 1970–2018, with high correlations of 0.75, 0.75, and 0.97 for atmospheric CO2 growth, air–land CO2 fluxes, and air–sea CO2 fluxes, respectively, relative to the assessments from the Global Carbon Project (GCP). Such a fully coupled decadal prediction system, with an interactive carbon cycle, enables the representation of the GCB within a closed Earth system and therefore provides an additional line of evidence for the ongoing assessments of the anthropogenic GCB. Retrospective predictions initialized from the simulation in which physical atmospheric and oceanic data products are assimilated show high confidence in predicting the following year's GCB. The predictive skill is up to 5 years for the air–sea CO2 fluxes, and 2 years for the air–land CO2 fluxes and atmospheric carbon growth rate. This is the first study investigating the GCB variations and predictions with an emission-driven prediction system. Such a system also enables the reconstruction of the past and prediction of the evolution of near-future atmospheric CO2 concentration changes. The Earth system predictions in this study provide valuable inputs for understanding the global carbon cycle and informing climate-relevant policy.

A multivariate dynamic statistical model of the global carbon budget 1959–2020

“…These efforts have been based on Earth System modelling. Li et al (2022) connect this approach with the GCB data set in order to arrive at predictions of observational data. Betts et al ( , 2018 propose a statistical forecast model for ΔC as a function of emissions and ENSO3.4 sea-surface temperature anomalies.…”

Breathing Planet Earth: Analysis of Keeling’s Data on CO2 and O2 with Respiratory Quotient (RQ), Part I: Global Respiratory Quotient (RQGlob) of Earth

“…For the first guess, they use results from earlier models. Li et al proposed an emission-driven earth system model for predicting the variations in the global carbon budget (GCB) [35] and presented variations in the GCB (1970-2018). Yakir…”

“…[30]): (i) Model for CO 2 via land use [31], (ii) Computer model for CO 2 flux from land to atm, CO 2 sink from global vegetation (land-based biomass [32]), which includes growth function models, (iii) Global ocean bio-geochemistry models, and (iv) Ocean CO 2 flux model. global carbon budget (GCB) [35] and presented variations in the GCB (1970-2018). Yakir et al summarizes the use of carbonyl sulfide (COS) as a tracer gas to measure changes in CO 2 uptake via PS [36].…”

Ocean biogeochemical reconstructions to estimate historical ocean CO2 uptake

“…In particular, we explore the differences between the standard GCB approach, which exclusively relies on prescribing boundary conditions from atmospheric reanalyses, and the additional assimilation of observed ocean physical variables. Recent work has already highlighted the advantage of using climate reconstructions to complement the GCB (Li et al, 2023). Moreover, past work has investigated the impact of assimilating biogeochemical observations to ocean simulations with uncertain results, mostly due to the scarcity of such observations (Valsala and Maksyutov, 2010;While et al, 2012).…”