Contrasting ecosystem constraints on seasonal terrestrial CO2 and mean surface air temperature causality projections by the end of the 21st century

Daniel F.T. Hagan, Han A.J. Dolman, Guojie Wang*, Kenny T.C.Lim Kam Sian, Kun Yang, Waheed Ullah, Runping Shen

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Two centuries of studies have demonstrated the importance of understanding the interaction between air temperature and carbon dioxide (CO2) emissions, which can impact the climate system and human life in various ways, and across different timescales. While historical interactions have been consistently studied, the nature of future interactions and the impacts of confounding factors still require more investigation in keeping with the continuous updates of climate projections to the end of the 21st century. Phase 6 of the Coupled Model Intercomparison Project (CMIP6), like its earlier projects, provides ScenarioMIP multi-model projections to assess the climate under different radiative forcings ranging from a low-end (SSP1-2.6) to a high-end (SSP5-8.5) pathway. In this study, we analyze the localized causal structure of CO2, and near-surface mean air temperature (meanT) interaction for four scenarios from three CMIP6 models using a rigorous multivariate information flow (IF) causality, which can separate the cause from the effect within the interaction (CO2-meanT and meanT-CO2) by measuring the rate of IF between parameters. First, we obtain patterns of the CO2 and meanT causal structures over space and time. We found a contrasting emission-based impact of soil moisture (SM) and vegetation (leaf area index (LAI)) changes on the meanT-CO2 causal patterns. That is, SM influenced CO2 sink regions in SSP1-2.6 and source regions in SSP5-8.5, and vice versa found for LAI influences. On the other hand, they function similarly to constrain the future CO2 impact on meanT. These findings are essential for improving long-term predictability where climate models might be limited.

Original languageEnglish
Article number124019
Pages (from-to)1-10
Number of pages10
JournalEnvironmental Research Letters
Volume17
Issue number12
Early online date30 Nov 2022
DOIs
Publication statusPublished - Dec 2022

Bibliographical note

Funding Information:
This research was funded by the National Natural Science Foundation of China (Grant No. 41875094) and the Jiangsu Postdoctoral Research Funding Program (Grant No. 2021K302C). We are also extremely grateful to Pierre Friedlingstein, X San Liang and the three anonymous reviewers for their very helpful suggestions and comments. We acknowledge the World Climate Research Programme (WCRP)—Working Group on Coupled Modelling for coordinating and promoting CMIP6. We also appreciate the different climate modeling groups for producing and making available their model output, and the Earth System Grid Federation (ESGF) for archiving the data and providing access. The multiple funding agencies supporting CMIP6 and ESGF are also recognized.

Publisher Copyright:
© 2022 The Author(s). Published by IOP Publishing Ltd.

Keywords

  • CMIP6
  • CO-temperature causality
  • information flow causality
  • LAI
  • soil moisture

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