Abstract

Abstract. Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1 % yr−1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean ± standard deviation = 0.97 ± 0.40 PgC ppm−1) and ocean (0.79 ± 0.07 PgC ppm−1), while the carbon–climate feedback over land (−45.1 ± 50.6 PgC ∘C−1) is about 3 times larger than over ocean (−17.2 ± 5.0 PgC ∘C−1). The strength of both feedbacks is an order of magnitude more uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77 ± 0.37 ∘C EgC−1 and is similar to that found in CMIP5 models (1.63 ± 0.48 ∘C EgC−1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.

Highlights

  • The Earth system responds to the perturbation of atmospheric CO2 concentration ([CO2]), caused by anthropogenic emissions of CO2 or any other forcing, via changes in its physical climate

  • The eight models in the A13 study are a subset of 11 models considered in this study they have been updated since Coupled Model Intercomparison Project Phase 5 (CMIP5)

  • Index (LAI), which decreases land surface albedo and increases absorbed solar radiation; and (3) increase in vegetation fraction in models that explicitly simulate competition between their plant functional types (PFTs) over land (NOAA-Geophysical Fluid Dynamics Laboratory (GFDL)-ESM4, MPI-ESM1.2-LR, and UKESM1-0LL), which leads to reduced land surface albedo

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Summary

Introduction

The Earth system responds to the perturbation of atmospheric CO2 concentration ([CO2]), caused by anthropogenic emissions of CO2 or any other forcing, via changes in its physical climate. The response of the Earth’s carbon cycle for both land and ocean components has been characterized in terms of carbon–concentration and carbon–climate feedback parameters which quantify their response to changes in [CO2] and the physical climate, respectively (Friedlingstein et al, 2006; Arora et al, 2013). Intermodel comparisons offer several benefits, including common standards and experiment protocol, coordination, and documentation that facilitate the distribution of model outputs and the characterization of the mean model response (Eyring et al, 2016), as has been shown for multiple model intercomparison projects (MIPs) They allow for the quantification of the contribution of the two feedback processes to allowable anthropogenic emissions for a given CO2 pathway. All participating modelling groups are expected to perform DECK experiments to help document basic characteristics of models across different phases of CMIP (Eyring et al, 2016)

Feedbacks metrics in the coupled climate–carbon system
Reasons for differences in feedback parameters among models
Model descriptions
Global surface CO2 fluxes and temperature change
Carbon budget terms
Feedback parameters
Reasons for differences among models
Summary and conclusions
Additional figures and discussion

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