Response of stratospheric water vapour to warming constrained by satellite observations

Nowack, Peer ORCID:, Ceppi, Paulo, Davis, Sean, Chiodo, Gabriel, Ball, Will, Diallo, Mohamadou, Hassler, Birgit, Jia, Yue, Keeble, James and Joshi, Manoj ORCID: (2023) Response of stratospheric water vapour to warming constrained by satellite observations. Nature Geoscience, 16 (7). 577–583. ISSN 1752-0894

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Future increases in stratospheric water vapour risk amplifying climate change and slowing down the recovery of the ozone layer. However, state-of-the-art climate models strongly disagree on the magnitude of these increases under global warming. Uncertainty primarily arises from the complex processes leading to dehydration of air during its tropical ascent into the stratosphere. Here we derive an observational constraint on this longstanding uncertainty. We use a statistical learning approach to infer historical co-variations between the atmospheric temperature structure and tropical lower stratospheric water vapour concentrations. For climate models, we demonstrate that these historically constrained relationships are highly predictive of the water vapour response to increased atmospheric carbon dioxide. We obtain an observationally constrained range for stratospheric water vapour changes per degree of global warming of 0.31 +/- 0.39~ppmv/K. Across 61 climate models, we find that a large fraction of future model projections are inconsistent with observational evidence. In particular, frequently projected strong increases (>1 ppmv/K) are highly unlikely. Our constraint represents a 50% decrease in the 95th percentile of the climate model uncertainty distribution, which has implications for surface warming, ozone recovery, and the tropospheric circulation response under climate change.

Item Type: Article
Additional Information: This paper is dedicated to the authors' coauthor, colleague and friend Will Ball, who passed away in April 2022. He brought this group together, ultimately resulting in this publication. Funding Information: P.N. and P.C. were supported through Imperial College Research Fellowships and the UK Natural Environment Research Council (NERC) grant number NE/V012045/1. P.C. was additionally supported by NERC grant NE/T006250/1. G.C. was supported by the Swiss National Science Foundation through the Ambizione grant number PZ00P2_180043. M.A.D. was funded by the Deutsche Forschungsgemeinschaft (DFG), individual research grant number DI2618/1-1. B.H. was supported by the European Research Council (ERC) Synergy grant ‘Understanding and modelling the Earth System with Machine Learning (USMILE)’ under the Horizon 2020 research and innovation programme (grant agreement number 855187) and by the Helmholtz Society project ‘Advanced Earth System Model Evaluation for CMIP’ (EVal4CMIP). J.K. was supported by the UK Met Office CSSP-China programme through the POzSUM project and by the NERC-funded InHALE project (NE/X003574/1). P.N. used JASMIN, the UK collaborative data analysis facility, and the High Performance Computing Cluster supported by the Research and Specialist Computing Support service at the University of East Anglia. We acknowledge the World Climate Research Programme (WCRP), which through its Working Group on Coupled Modeling, coordinated and promoted CMIP6. Acknowledgements: The authors thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access and the funding agencies that support CMIP6 and ESGF.
Uncontrolled Keywords: earth and planetary sciences(all) ,/dk/atira/pure/subjectarea/asjc/1900
Faculty \ School: Faculty of Science > School of Environmental Sciences
UEA Research Groups: Faculty of Science > Research Groups > Climatic Research Unit
Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences
University of East Anglia Schools > Faculty of Science > Tyndall Centre for Climate Change Research
Faculty of Science > Research Centres > Tyndall Centre for Climate Change Research
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Depositing User: LivePure Connector
Date Deposited: 14 Apr 2023 15:30
Last Modified: 25 Jul 2023 08:30
DOI: 10.1038/s41561-023-01183-6


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