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Stratospheric water vapor: an important climate feedback

  • Antara BanerjeeEmail author
  • Gabriel Chiodo
  • Michael Previdi
  • Michael Ponater
  • Andrew J. Conley
  • Lorenzo M. Polvani
Article

Abstract

The role of stratospheric water vapor (SWV) changes, in response to increasing \(\hbox {CO}_2\), as a feedback component of quantitative significance for climate sensitivity has remained controversial. Here, we calculate the SWV climate feedback under abrupt \(\hbox {CO}_2\) quadrupling in the CMIP5 ensemble of models. All models robustly show a moistening of the stratosphere, causing a global mean net stratosphere adjusted radiative perturbation of \(0.89\pm 0.27\,\hbox {Wm}^{-2}\) at the reference tropopause. The stratospheric temperature adjustment is a crucial component of this radiative perturbation. The associated climate feedback is \(0.17\pm 0.05\,\hbox {Wm}^{-2}\,\hbox{K}^{-1}\), with a considerable inter-model range of 0.12–0.28 \(\hbox {Wm}^{-2}\,\hbox {K}^{-1}\). Taking into account the rise in tropopause height under \(4\times \hbox {CO}_2\) slightly reduces the feedback to \(0.15\pm 0.04\,\hbox {Wm}^{-2}\,\hbox {K}^{-1}\), with a range of 0.10–\(0.26\,\hbox {Wm}^{-2} \,\hbox {K}^{-1}\). The SWV radiative perturbation peaks in the midlatitudes and not the tropics: this is due primarily to increases in SWV in the extratropical lowermost stratosphere, which cause the majority (over three quarters) of the global mean feedback. Based on these results, we suggest an increased focus on understanding drivers of water vapor trends in the extratropical lowermost stratosphere. We conclude that the SWV feedback is important, being on the same order of magnitude as the global mean surface albedo and cloud feedbacks in the multi-model mean.

Keywords

Stratospheric water vapor Climate feedback Climate change Partial radiative perturbation Radiative kernel CMIP5 models 

Notes

Acknowledgements

This work was funded, in part, by grants from the US National Science Foundation (NSF) to Columbia University. The authors would like to thank Andrew Dessler, Yi Huang and an anonymous reviewer for helpful comments on this work. We would like to acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

Supplementary material

382_2019_4721_MOESM1_ESM.pdf (60 kb)
Supplementary material 1 (PDF 59 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Applied Physics and Applied MathematicsColumbia UniversityNew YorkUSA
  2. 2.Cooperative Institute for Research in Environmental SciencesUniversity of Colorado BoulderBoulderUSA
  3. 3.National Oceanic and Atmospheric Administration/Earth System Research Laboratory/Chemical Sciences DivisionBoulderUSA
  4. 4.Department of Earth and Environmental SciencesLamont Doherty Earth ObservatoryNew YorkUSA
  5. 5.Deutsches Zentrum für Luft- und Raumfahrt (DLR)Institut für Physik der AtmosphäreWeßlingGermany
  6. 6.National Center for Atmospheric ResearchBoulderUSA

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