Editorial Type:
Article
Article Type:
Research Article

The Atmospheric Energy Constraint on Global-Mean Precipitation Change

Angeline G. Pendergrass Department of Atmospheric Sciences, University of Washington, Seattle, Washington

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Dennis L. Hartmann Department of Atmospheric Sciences, University of Washington, Seattle, Washington

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Print Publication:
15 Jan 2014
DOI:
https://doi.org/10.1175/JCLI-D-13-00163.1
Page(s):
757–768
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Abstract

Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) robustly predict that the rate of increase in global-mean precipitation with global-mean surface temperature increase is much less than the rate of increase of water vapor. The goal of this paper is to explain in detail the mechanisms by which precipitation increase is constrained by radiative cooling. Changes in clear-sky atmospheric radiative cooling resulting from changes in temperature and humidity in global warming simulations are in good agreement with the multimodel, global-mean precipitation increase projected by GCMs (~1.1 W m−2 K−1).

In an atmosphere with fixed specific humidity, radiative cooling from the top of the atmosphere (TOA) increases in response to a uniform temperature increase of the surface and atmosphere, while atmospheric cooling by exchange with the surface decreases because the upward emission of longwave radiation from the surface increases more than the downward longwave radiation from the atmosphere. When a fixed relative humidity (RH) assumption is made, however, uniform warming causes a much smaller increase of cooling at the TOA, and the surface contribution reverses to an increase in net cooling rate due to increased downward emission from water vapor. Sensitivity of precipitation changes to lapse rate changes is modest when RH is fixed. Carbon dioxide reduces TOA emission with only weak effects on surface fluxes, and thus suppresses precipitation. The net atmospheric cooling response and thereby the precipitation response to CO2-induced warming at fixed RH are mostly contributed by changes in surface fluxes. The role of clouds is discussed.

Intermodel spread in the rate of precipitation increase across the CMIP5 simulations is attributed to differences in the atmospheric cooling.

Corresponding author address: Angeline G. Pendergrass, University of Washington, Box 351640, Seattle, WA 98195. E-mail: angie@atmos.washington.edu

Abstract

Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) robustly predict that the rate of increase in global-mean precipitation with global-mean surface temperature increase is much less than the rate of increase of water vapor. The goal of this paper is to explain in detail the mechanisms by which precipitation increase is constrained by radiative cooling. Changes in clear-sky atmospheric radiative cooling resulting from changes in temperature and humidity in global warming simulations are in good agreement with the multimodel, global-mean precipitation increase projected by GCMs (~1.1 W m−2 K−1).

In an atmosphere with fixed specific humidity, radiative cooling from the top of the atmosphere (TOA) increases in response to a uniform temperature increase of the surface and atmosphere, while atmospheric cooling by exchange with the surface decreases because the upward emission of longwave radiation from the surface increases more than the downward longwave radiation from the atmosphere. When a fixed relative humidity (RH) assumption is made, however, uniform warming causes a much smaller increase of cooling at the TOA, and the surface contribution reverses to an increase in net cooling rate due to increased downward emission from water vapor. Sensitivity of precipitation changes to lapse rate changes is modest when RH is fixed. Carbon dioxide reduces TOA emission with only weak effects on surface fluxes, and thus suppresses precipitation. The net atmospheric cooling response and thereby the precipitation response to CO2-induced warming at fixed RH are mostly contributed by changes in surface fluxes. The role of clouds is discussed.

Intermodel spread in the rate of precipitation increase across the CMIP5 simulations is attributed to differences in the atmospheric cooling.

Corresponding author address: Angeline G. Pendergrass, University of Washington, Box 351640, Seattle, WA 98195. E-mail: angie@atmos.washington.edu
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  • Allan, R. P., 2006: Variability in clear-sky longwave radiative cooling of the atmosphere. J. Geophys. Res.,111, D22105, doi:10.1029/2006JD007304.

  • Allen, M. R., and W. J. Ingram, 2002: Constraints on future changes in climate and the hydrologic cycle. Nature, 419, 224–232, doi:10.1038/nature01092.

    • Search Google Scholar
    • Export Citation

  • Cess, R. D., 1975: Global climate change: An investigation of atmospheric feedback mechanisms. Tellus, 27, 193–198, doi:10.1111/j.2153-3490.1975.tb01672.x.

    • Search Google Scholar
    • Export Citation

  • Collins, W., and Coauthors, 2006: Radiative forcing by well-mixed greenhouse gases: Estimates from climate models in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). J. Geophys. Res., 111, D14317, doi:10.1029/2005JD006713.

    • Search Google Scholar
    • Export Citation

  • Costa, S. M. S., and K. P. Shine, 2012: Outgoing longwave radiation due to directly transmitted surface emission. J. Atmos. Sci., 69, 1865–1870.

    • Search Google Scholar
    • Export Citation

  • Fu, Q., and K. N. Liou, 1992: On the correlated k-distribution method for radiative transfer in nonhomogeneous atmospheres. J. Atmos. Sci., 49, 2139–2156.

    • Search Google Scholar
    • Export Citation

  • Held, I. M., and B. J. Soden, 2006: Robust responses of the hydrological cycle to global warming. J. Climate, 19, 5686–5699.

  • Held, I. M., and K. Shell, 2012: Using relative humidity as a state variable in climate feedback analysis. J. Climate, 25, 2578–2582.

  • Inamdar, A., V. Ramanathan, and N. Loeb, 2004: Satellite observations of the water vapor greenhouse effect and column longwave cooling rates: Relative roles of the continuum and vibration-rotation to pure rotation bands. J. Geophys. Res.,109, D06104, doi:10.1029/2003JD003980.

  • Kvalevåg, M. M., B. H. Samset, and G. Myhre, 2013: Hydrological sensitivity to greenhouse gases and aerosols in a global climate model. Geophys. Res. Lett., 40, 1432–1438, doi:10.1002/grl.50318.

    • Search Google Scholar
    • Export Citation

  • Lambert, F. H., and M. J. Webb, 2008: Dependency of global mean precipitation on surface temperature. Geophys. Res. Lett.,35, L16706, doi:10.1029/2008GL034838.

  • Loeb, N. G., J. M. Lyman, G. C. Johnson, R. P. Allan, D. R. Doelling, T. Wong, B. J. Soden, and G. L. Stephens, 2012: Observed changes in top-of-the-atmosphere radiation and upper-ocean heating consistent within uncertainty. Nat. Geosci., 5, 110–113, doi:10.1038/ngeo1375.

    • Search Google Scholar
    • Export Citation

  • Lorenz, D. J., E. T. DeWeaver, and D. J. Vimont, 2010: Evaporation change and global warming: The role of net radiation and relative humidity. J. Geophys. Res.,115, D20118, doi:10.1029/2010JD013949.

  • McCusker, K. E., D. S. Battisti, and C. M. Bitz, 2012: The climate response to stratospheric sulfate injections and implications for addressing climate emergencies. J. Climate, 25, 3096–3116.

    • Search Google Scholar
    • Export Citation

  • Ming, Y., V. Ramaswamy, and G. Persad, 2010: Two opposing effects of absorbing aerosols on global-mean precipitation. Geophys. Res. Lett.,37, L13701, doi:10.1029/2010GL042895.

  • Mitchell, J. F. B., C. A. Wilson, and W. M. Cunnington, 1987: On CO2 climate sensitivity and model dependence of results. Quart. J. Roy. Meteor. Soc., 113, 293–322, doi:10.1002/qj.49711347517.

    • Search Google Scholar
    • Export Citation

  • O’Gorman, P. A., and T. Schneider, 2008: The hydrological cycle over a wide range of climates simulated with an idealized GCM. J. Climate, 21, 3815–3832.

    • Search Google Scholar
    • Export Citation

  • O’Gorman, P. A., R. P. Allan, M. P. Byrne, and M. Previdi, 2012: Energetic constraints on precipitation under climate change. Surv. Geophys., 33, 585–608, doi:10.1007/s10712-011-9159-6.

    • Search Google Scholar
    • Export Citation

  • Pendergrass, A. G., and D. L. Hartmann, 2012: Global-mean precipitation and black carbon in AR4 simulations. Geophys. Res. Lett.,39, L01703, doi:10.1029/2011GL050067.

  • Previdi, M., 2010: Radiative feedbacks on global precipitation. Environ. Res. Lett.,5, 025211, doi:10.1088/1748-9326/5/2/025211.

  • Richter, I., and S.-P. Xie, 2008: Muted precipitation increase in global warming simulations: A surface evaporation perspective. J. Geophys. Res., 113, D24118, doi:10.1029/2008JD010561.

    • Search Google Scholar
    • Export Citation

  • Soden, B. J., and I. M. Held, 2006: An assessment of climate feedbacks in coupled ocean–atmosphere models. J. Climate, 19, 3354–3360.

    • Search Google Scholar
    • Export Citation

  • Stephens, G. L., and T. D. Ellis, 2008: Controls of global-mean precipitation increases in global warming GCM experiments. J. Climate, 21, 6141–6155.

    • Search Google Scholar
    • Export Citation

  • Takahashi, K., 2009a: The global hydrological cycle and atmospheric shortwave absorption in climate models under CO2 forcing. J. Climate, 22, 5667–5675.

    • Search Google Scholar
    • Export Citation

  • Takahashi, K., 2009b: Radiative constraints on the hydrological cycle in an idealized radiative–convective equilibrium model. J. Atmos. Sci., 66, 77–91.

    • Search Google Scholar
    • Export Citation

  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485–498.

    • Search Google Scholar
    • Export Citation

  • Zelinka, M. D., and D. L. Hartmann, 2010: Why is longwave cloud feedback positive? J. Geophys. Res.,115, D16117, doi:10.1029/2010JD013817.

  • Zelinka, M. D., S. A. Klein, and D. L. Hartmann, 2012: Computing and partitioning cloud feedbacks using cloud property histograms. Part II: Attribution to changes in cloud amount, altitude, and optical depth. J. Climate, 25, 3736–3754.

    • Search Google Scholar
    • Export Citation

  • Zhang, M., J. Hack, J. Kiehl, and R. Cess, 1994: Diagnostic study of climate feedback processes in atmospheric general circulation models. J. Geophys. Res., 99 (D3), 5525–5537.

    • Search Google Scholar
    • Export Citation
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