• Barnes, E. A., and D. L. Hartmann, 2010: Dynamical feedbacks and the persistence of the NAO. J. Atmos. Sci., 67, 851865, https://doi.org/10.1175/2009JAS3193.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barnes, E. A., and L. M. Polvani, 2013: Response of the midlatitude jets and of their variability to increased greenhouse gases in the CMIP5 model. J. Climate, 26, 71177135, https://doi.org/10.1175/JCLI-D-12-00536.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bony, S., G. Bellon, D. Klocke, S. Sherwood, S. Fermepin, and S. Denvil, 2013: Robust direct effect of carbon dioxide on tropical circulation and regional precipitation. Nat. Geosci., 6, 447451, https://doi.org/10.1038/ngeo1799.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bony, S., B. Stevens, D. Coppin, T. Becker, K. A. Reed, A. Voigt, and B. Medeiros, 2016: Thermodynamic control of anvil cloud amount. Proc. Natl. Acad. Sci. USA, 113, 89278932, https://doi.org/10.1073/pnas.1601472113.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Butler, A. H., D. Thompson, and R. Heikes, 2010: The steady-state atmospheric circulation response to climate change–like thermal forcings in a simple general circulation model. J. Climate, 23, 34743496, https://doi.org/10.1175/2010JCLI3228.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ceppi, P., and D. L. Hartmann, 2016: Clouds and the atmospheric circulation response to warming. J. Climate, 29, 783799, https://doi.org/10.1175/JCLI-D-15-0394.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ceppi, P., and T. G. Shepherd, 2017: Contributions of climate feedbacks to changes in atmospheric circulation. J. Climate, 30, 90979118, https://doi.org/10.1175/JCLI-D-17-0189.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ceppi, P., Y.-T. Hwang, D. M. W. Frierson, and D. L. Hartmann, 2012: Southern Hemisphere jet latitude biases in CMIP5 models linked to shortwave cloud forcing. Geophys. Res. Lett., 39, L19708, https://doi.org/10.1029/2012GL053115.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ceppi, P., M. D. Zelinka, and D. L. Hartmann, 2014: The response of the Southern Hemispheric eddy-driven jet to future changes in shortwave radiation in CMIP5. Geophys. Res. Lett., 41, 32443250, https://doi.org/10.1002/2014GL060043.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, G., and I. M. Held, 2007: Phase speed spectra and the recent poleward shift of Southern Hemisphere surface westerlies. Geophys. Res. Lett., 34, L21805, https://doi.org/10.1029/2007GL031200.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, G., J. Lu, and D. Frierson, 2008: Phase speed spectra and the latitude of surface westerlies: Interannual variability and global warming trend. J. Climate, 21, 59425959, https://doi.org/10.1175/2008JCLI2306.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collins, W., and Coauthors, 2008: Evaluation of HadGEM2 model. Hadley Centre Tech. Note 74, 47 pp.

  • Deser, C., and A. S. Phillips, 2009: Atmospheric circulation trends, 1950–2000: The relative roles of sea surface temperature forcing and direct atmospheric radiative forcing. J. Climate, 22, 396413, https://doi.org/10.1175/2008JCLI2453.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dufresne, J.-L., and Coauthors, 2013: Climate change projections using the IPSL-CM5 Earth system model: From CMIP3 to CMIP5. Climate Dyn., 40, 21232165, https://doi.org/10.1007/s00382-012-1636-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fermepin, S., and S. Bony, 2014: Influence of low-cloud radiative effects on tropical circulation and precipitation. J. Adv. Model. Earth Syst., 6, 513526, https://doi.org/10.1002/2013MS000288.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fläschner, D., T. Mauritsen, B. Stevens, and S. Bony, 2018: The signature of shallow circulations, not cloud radiative effects, in the spatial distribution of tropical precipitation. J. Climate, 31, 94899505, https://doi.org/10.1175/JCLI-D-18-0230.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frierson, D., 2008: Midlatitude static stability in simple and comprehensive general circulation models. J. Atmos. Sci., 65, 10491062, https://doi.org/10.1175/2007JAS2373.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grise, K. M., and L. M. Polvani, 2014: Southern Hemisphere cloud–dynamics biases in CMIP5 models and their implications for climate projections. J. Climate, 27, 60746092, https://doi.org/10.1175/JCLI-D-14-00113.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grise, K. M., and L. M. Polvani, 2017: Understanding the time scales of the tropospheric circulation response to abrupt CO2 forcing in the Southern Hemisphere: Seasonality and the role of the stratosphere. J. Climate, 30, 84978515, https://doi.org/10.1175/JCLI-D-16-0849.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hall, N. M. J., B. J. Hoskins, P. J. Valdes, and C. A. Senior, 1994: Storm tracks in a high-resolution GCM with doubled carbon dioxide. Quart. J. Roy. Meteor. Soc., 120, 12091230, https://doi.org/10.1002/qj.49712051905.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hartmann, D. L., and K. Larson, 2002: An important constraint on tropical cloud-climate feedback. Geophys. Res. Lett., 29, 1951, https://doi.org/10.1029/2002GL015835.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Held, I. M., and M. J. Suarez, 1994: A proposal for the intercomparison of the dynamical cores of atmospheric general circulation models. Bull. Amer. Meteor. Soc., 75, 18251830, https://doi.org/10.1175/1520-0477(1994)075<1825:APFTIO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hourdin, F., and Coauthors, 2013a: Impact of the LMDZ atmospheric grid configuration on the climate and sensitivity of the IPSL-CM5A coupled model. Climate Dyn., 40, 21672192, https://doi.org/10.1007/s00382-012-1411-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hourdin, F., and Coauthors, 2013b: LMDZ5B: The atmospheric component of the IPSL climate model with revisited parameterizations for clouds and convection. Climate Dyn., 40, 21932222, https://doi.org/10.1007/s00382-012-1343-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kidston, J., and E. P. Gerber, 2010: Intermodel variability of the poleward shift of the austral jet stream in the CMIP3 integrations linked to biases in 20th century climatology. Geophys. Res. Lett., 37, L09708, https://doi.org/10.1029/2010GL042873.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuang, Z., and D. L. Hartmann, 2007: Testing the fixed anvil temperature hypothesis in a cloud-resolving model. J. Climate, 20, 20512057, https://doi.org/10.1175/JCLI4124.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kushner, P. J., I. M. Held, and T. L. Delworth, 2001: Southern Hemisphere atmospheric circulation response to global warming. J. Climate, 14, 22382249, https://doi.org/10.1175/1520-0442(2001)014<0001:SHACRT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Y., D. W. J. Thompson, and S. Bony, 2015: The influence of atmospheric cloud radiative effects on the large-scale atmospheric circulation. J. Climate, 28, 72637278, https://doi.org/10.1175/JCLI-D-14-00825.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Y., D. W. J. Thompson, and Y. Huang, 2017: The influence of atmospheric cloud radiative effects on the large-scale stratospheric circulation. J. Climate, 30, 56215635, https://doi.org/10.1175/JCLI-D-16-0643.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lorenz, D. J., 2014: Understanding midlatitude jet variability and change using Rossby wave chromatography: Poleward-shifted jets in response to external forcing. J. Atmos. Sci., 71, 23702389, https://doi.org/10.1175/JAS-D-13-0200.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lorenz, D. J., and E. T. DeWeaver, 2007: Tropopause height and zonal-wind response to global warming in the IPCC scenario integrations. J. Geophys. Res., 112, D10119, https://doi.org/10.1029/2006JD008087.

    • Search Google Scholar
    • Export Citation
  • Polvani, L. M., and P. Kushner, 2002: Tropospheric response to stratospheric perturbations in a relatively simple general circulation model. Geophys. Res. Lett., 29, 1114, https://doi.org/10.1029/2001GL014284.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Popke, D., B. Stevens, and A. Voigt, 2013: Climate and climate change in a radiative-convective equilibrium version of ECHAM6. J. Adv. Model. Earth Syst., 5, 114, https://doi.org/10.1029/2012MS000191.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Santer, B. D., and Coauthors, 2003: Contributions of anthropogenic and natural forcing to recent tropopause height changes. Science, 301, 479483, https://doi.org/10.1126/science.1084123.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sherwood, S. C., S. Bony, O. Boucher, C. Bretherton, P. M. Forster, J. M. Gregory, and B. Stevens, 2015: Adjustments in the forcing-feedback framework for understanding climate change. Bull. Amer. Meteor. Soc., 96, 217228, https://doi.org/10.1175/BAMS-D-13-00167.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Simpson, I. R., and L. M. Polvani, 2016: Revisiting the relationship between jet position, forced response, and annular mode variability in the southern midlatitudes. Geophys. Res. Lett., 43, 28962903, https://doi.org/10.1002/2016GL067989.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Simpson, I. R., T. A. Shaw, and R. Seager, 2014: A diagnosis of the seasonally and longitudinally varying midlatitude circulation response to global warming. J. Atmos. Sci., 71, 24892515, https://doi.org/10.1175/JAS-D-13-0325.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Singh, M., and P. O’Gorman, 2012: Upward shift of the atmospheric general circulation under global warming: Theory and simulations. J. Climate, 25, 82598276, https://doi.org/10.1175/JCLI-D-11-00699.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stevens, B., and S. Bony, 2013: What are climate models missing? Science, 340, 10531054, https://doi.org/10.1126/science.1237554.

  • Stevens, B., S. Bony, and M. Webb, 2012: Clouds On-Off Klimate Intercomparison Experiment (COOKIE). 12 pp., http://www.euclipse.eu/downloads/Cookie.pdf.

    • Search Google Scholar
    • Export Citation
  • Sun, L., G. Chen, and J. Lu, 2013: Sensitivities and mechanisms of the zonal mean atmospheric circulation response to tropical warming. J. Atmos. Sci., 70, 24872504, https://doi.org/10.1175/JAS-D-12-0298.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tandon, N. F., E. P. Gerber, A. H. Sobel, and L. M. Polvani, 2013: Understanding Hadley cell expansion versus contraction: Insights from simplified models and implications for recent observations. J. Climate, 26, 43044321, https://doi.org/10.1175/JCLI-D-12-00598.1.

    • Crossref
    • 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, 485498, https://doi.org/10.1175/BAMS-D-11-00094.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, D. W. J., S. Bony, and Y. Li, 2017: Thermodynamic constraint on the depth of the global tropospheric circulation. Proc. Natl. Acad. Sci. USA, 114, 81818186, https://doi.org/10.1073/pnas.1620493114.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vallis, G., P. Zurita-Gotor, C. Cairns, and J. Kidston, 2015: Response of the large-scale structure of the atmosphere to global warming. Quart. J. Roy. Meteor. Soc., 141, 14791501, https://doi.org/10.1002/qj.2456.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voigt, A., and T. A. Shaw, 2015: Radiative changes of clouds and water vapor shape circulation response to global warming. Nat. Geosci., 8, 102106, https://doi.org/10.1038/ngeo2345.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voigt, A., and T. A. Shaw, 2016: Impact of regional atmospheric cloud radiative changes on shifts of the extratropical jet stream in response to global warming. J. Climate, 29, 83998421, https://doi.org/10.1175/JCLI-D-16-0140.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voldoire, A., and Coauthors, 2013: The CNRM-CM5.1 global climate model: Description and basic evaluation. Climate Dyn., 40, 20912121, https://doi.org/10.1007/s00382-011-1259-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Watt-Meyer, O., and D. M. W. Frierson, 2017: Local and remote impacts of atmospheric cloud radiative effects onto the eddy-driven jet. Geophys. Res. Lett., 44, 10 03610 044, https://doi.org/10.1002/2017GL074901.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Webb, M. J., and Coauthors, 2017: The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6. Geosci. Model Dev., 10, 359384, https://doi.org/10.5194/gmd-10-359-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yin, J. H., 2005: A consistent poleward shift of the storm tracks in simulations of 21st century climate. Geophys. Res. Lett., 32, L18701, https://doi.org/10.1029/2005GL023684.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yukimoto, S., and Coauthors, 2012: A new global climate model of the Meteorological Research Institute: MRI-CGCM3—Model description and basic performance. J. Meteor. Soc. Japan, 90A, 2364, https://doi.org/10.2151/jmsj.2012-A02.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zelinka, M. D., and D. L. Hartmann, 2010: Why is longwave cloud feedback positive? J. Geophys. Res., 115, D16117, https://doi.org/10.1029/2010JD013817.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zelinka, M. D., S. Klein, K. Taylor, T. Andrews, M. Webb, J. Gregory, and P. Forster, 2013: Contributions of different cloud types to feedbacks and rapid adjustments in CMIP5. J. Climate, 26, 50075027, https://doi.org/10.1175/JCLI-D-12-00555.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 461 266 16
PDF Downloads 458 288 17

Thermodynamic Control on the Poleward Shift of the Extratropical Jet in Climate Change Simulations: The Role of Rising High Clouds and Their Radiative Effects

View More View Less
  • 1 Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado
  • | 2 Laboratoire de Météorologie Dynamique, IPSL, CNRS, Université Pierre et Marie Curie, Paris, France
  • | 3 Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada
Restricted access

Abstract

Extratropical eddy-driven jets are predicted to shift poleward in a warmer climate. Recent studies have suggested that cloud radiative effects (CRE) may enhance the amplitude of such shifts. But there is still considerable uncertainty about the underlying mechanisms, whereby CRE govern the jet response to climate change. This study provides new insights into the role of CRE in the jet response to climate change by exploiting the output from six global warming simulations run with and without atmospheric CRE (ACRE). Consistent with previous studies, it is found that the magnitude of the jet shift under climate change is substantially increased in simulations run with ACRE. It is hypothesized that ACRE enhance the jet response to climate change by increasing the upper-tropospheric baroclinicity due to the radiative effects of rising high clouds. The lifting of the tropopause and high clouds in response to surface warming arises from the thermodynamic constraints placed on water vapor concentrations. Hence, the influence of ACRE on the jet shift in climate change simulations may be viewed as an additional “robust” thermodynamic constraint placed on climate change by the Clausius–Clapeyron relation. The hypothesis is tested in simulations run with an idealized dry GCM, in which the model is perturbed with a thermal forcing that resembles the ACRE response to surface warming. It is demonstrated that 1) the enhanced jet shifts found in climate change simulations run with ACRE are consistent with the atmospheric response to the radiative warming associated with rising high clouds, and 2) the amplitude of the jet shift scales linearly with the amplitude of the ACRE forcing.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Ying Li, ying.li@colostate.edu

Abstract

Extratropical eddy-driven jets are predicted to shift poleward in a warmer climate. Recent studies have suggested that cloud radiative effects (CRE) may enhance the amplitude of such shifts. But there is still considerable uncertainty about the underlying mechanisms, whereby CRE govern the jet response to climate change. This study provides new insights into the role of CRE in the jet response to climate change by exploiting the output from six global warming simulations run with and without atmospheric CRE (ACRE). Consistent with previous studies, it is found that the magnitude of the jet shift under climate change is substantially increased in simulations run with ACRE. It is hypothesized that ACRE enhance the jet response to climate change by increasing the upper-tropospheric baroclinicity due to the radiative effects of rising high clouds. The lifting of the tropopause and high clouds in response to surface warming arises from the thermodynamic constraints placed on water vapor concentrations. Hence, the influence of ACRE on the jet shift in climate change simulations may be viewed as an additional “robust” thermodynamic constraint placed on climate change by the Clausius–Clapeyron relation. The hypothesis is tested in simulations run with an idealized dry GCM, in which the model is perturbed with a thermal forcing that resembles the ACRE response to surface warming. It is demonstrated that 1) the enhanced jet shifts found in climate change simulations run with ACRE are consistent with the atmospheric response to the radiative warming associated with rising high clouds, and 2) the amplitude of the jet shift scales linearly with the amplitude of the ACRE forcing.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Ying Li, ying.li@colostate.edu
Save