Assessing carbon cycle projections from complex and simple models under SSP scenarios

Irina Melnikova (), Philippe Ciais, Olivier Boucher and Katsumasa Tanaka ()
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Irina Melnikova: Université Paris-Saclay
Philippe Ciais: Université Paris-Saclay
Olivier Boucher: Sorbonne Université / CNRS
Katsumasa Tanaka: Université Paris-Saclay

Climatic Change, 2023, vol. 176, issue 12, No 10, 26 pages

Abstract: Abstract Both full-fledged Earth system models (ESMs) and simple climate models (SCMs) have been used to investigate climate change for future representative CO2 concentration pathways under the sixth phase of the Coupled Model Intercomparison Project. Here, we explore to what extent complex and simple models are consistent in their carbon cycle response in concentration-driven simulations. Although ESMs and SCMs exhibit similar compatible fossil fuel CO2 emissions, ESMs systematically estimate a lower ocean carbon uptake than SCMs in the historical period and future scenarios. The ESM and SCM differences are especially large under low-concentration and overshoot scenarios. Furthermore, ESMs and SCMs deviate in their land carbon uptake estimates, but the differences are scenario-dependent. These differences are partly driven by a few model outliers (ESMs and SCMs) and the procedure of observational constraining that is present in the majority of SCMs but not applied in ESMs. The differences in land uptake arise from the difference in the way land-use change (LUC) emissions are calculated and different assumptions on how the carbon cycle feedbacks are defined, possibly reflecting the treatment of nitrogen limitation of biomass growth and historical calibration of SCMs. The differences in ocean uptake, which are especially large in overshoot scenarios, may arise from the faster mixing of carbon from the surface to the deep ocean in SCMs than in ESMs. We also discuss the inconsistencies that arise when converting CO2 emissions from integrated assessment models (IAMs) to CO2 concentrations inputs for ESMs, which typically rely on a single SCM. We further highlight the discrepancies in LUC emission estimates between models of different complexity, particularly ESMs and IAMs, and encourage climate modeling groups to address these potential areas for model improvement.

Keywords: ESMs; SCMs; CMIP6; RCMIP; Carbon cycle; Compatible emissions; Future scenarios (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10584-023-03639-5

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