Cloud variability, radiative forcing and meridional temperature gradients in a general circulation model

References

• Alexeev, V. A. 2003. Sensitivity to CO2 doubling of an atmospheric GCM coupled to an oceanic mixed layer: a linear analysis. Clim. Dyn. 20, 775–787.
   Web of Science ®Google Scholar
• Alexeev, V. A., Langen, P. L. and Bates, J. R. 2005. Polar amplification of surface warming on an aquaplanet in “ghost forcing” experiments without sea ice feedbacks.Clim. Dyn. 10.1007/s00382-005-0018-3.
   Google Scholar
• Barker, H. W., Stephens, G. L., Partain, P. T., Bergman, J. W., Bonnel, B., and co-authors. 2003. Assessing 1D atmospheric solar radiative transfer models: interpretation and handling of unresolved clouds. J. Climate 16, 2676-2699.
   Google Scholar
• Barkstrom, B. R. 1984. The earth radiation budget experiment (ERBE). Bull. Amer Meteor Soc. 65, 1170–1185.
   Web of Science ®Google Scholar
• Bergman, J. W. and Salby, M. L. 1997. The role of cloud diurnal variations in the time-mean energy budget. J. Climate 10, 1114–1124.
   Web of Science ®Google Scholar
• Bony, S., Colman, R., Kattsov, V. M., Allan, R. P., Bretherton, C. S., and co-authors. 2006. How well do we understand and evaluate climate change feedback processes? J. Climate 19, 3445-3482.
   Google Scholar
• Briegleb, B. P. 1992. Delta-eddington approximation for solar radiation in the NCAR Community Climate Model. J. Geophys. Res. 97(D7), 7603–7612.
   Web of Science ®Google Scholar
• Caballero, R. and Langen, P. L. 2005. The dynamic range of poleward energy transport in an atmospheric general circulation model. Geophys. Res. Lett. 32, L02705, 10.1029/2004GL021581.
   Web of Science ®Google Scholar
• Cess, R. D. and Potter, G. L. 1987. Exploratory studies of cloud radiative forcing with a general circulation model. Tellus 39A, 460–473.
   Google Scholar
• Cess, R. D., Genio, A. D., Dix, M., Esch, M., Fowler, L., and co-authors. 1996. Cloud feedback in atmospheric general circulation models: an update.J. Geophys. Res. 101D, 12 791–12 794.
   Google Scholar
• Collins, W. D. 2001. Parameterization of generalized cloud overlap for radiative calculations in general circulation models. J. Atmos. Sc i. 58, 3224–3242.
   Google Scholar
• Colman, R., Fraser, J. and Rotstayn, L. 2001. Climate feedbacks in a general circulation model incorporating prognostic clouds.Clim. Dyn. 18, 103-122.
   Google Scholar
• Geleyn, J. F. and Hollingsworth, A. 1979. An economical analytical method for the computation of the interaction between scattering and line absorption of radiation.Contrib. Atmos. Phys. 52, 1-16.
   Google Scholar
• Harshvardhan G. and Randall, D. A. 1985. Comments on “The parame-terization of radiation for numerical weather prediction and climate models”. Mon. Wea. Re v. 113, 1832–1833.
   Google Scholar
• Houghton, J. T., Ding, Y., Griggs, D. J., Noguer, M., van der Linden, P. J. and co-editors. 2001. IPCC, Climate Change 2001: The Scientific Basis. Cambridge University Press, Cambridge, UK, 944 pp.
   Google Scholar
• Kiehl, J. T., Hack, J. J., Bonan, G. B., Boville, B. A., Briegleb, B. P., and co-authors. 1996. Description of the NCAR Community Climate Model (CCM3). Technical Report TN-420, CGD, National Center for Atmospheric Research.
   Google Scholar
• Langen, P. L. 2005. Polar amplification of surface temperature change in a warming climate. PhD thesis, Niels Bohr Institute, University of Copenhagen, Denmark.
   Google Scholar
• Langen, P. L. and Alexeev, V. A. 2004. Multiple equilibria and asymmetric climates in the CCM3 coupled to an oceanic mixed layer with thermodynamic sea ice.Geophys. Res. Lett. 31, 10.1029/2003GL019039.
   Google Scholar
• Lapeyre, G. and Held, I. M. 2004. The role of moisture in the dynamics and energetics of turbulent baroclinic eddies. J. Atmos. Sc i. 61, 1693–1710.
   Google Scholar
• Le Treut, H., Li, Z. X. and Forichon, M. 1994. Sensitivity of the LIVID general circulation model to greenhouse forcing associated with two different cloud water parameterizations. J. Climate 7, 1827–1841.
   Web of Science ®Google Scholar
• Manabe, S. and Strickler, R. F. 1964. Thermal equilibrium of the atmosphere with a convective adjustment.J. Atmos. Sci. 21, 361-385.
   Google Scholar
• Oreopoulos, L. and Khairoutdinov, M. 2003. Overlap properties of clouds generated by a cloud-resolving model.J. Geophys. Res. 108, 10.1029/2002JD003329.
   Google Scholar
• Ramanathan, V., Cess, R. D., Harrison, E. F., Minnis, R, Barlcstrom, B. R., and co-authors. 1989. Cloud-radiative forcing and climate: results from the earth radiation budget experiment.Science 243, 57-63.
   Google Scholar
• Randall, D., Khairoutdinov, M., Aralcawa, A. and Grabowski, W. 2003. Breaking the cloud parameterization deadlock. Bull. Amer Meteor Soc. 84, 1547–1564.
   Web of Science ®Google Scholar
• Ringer, M. A., McAvaney, B. J., Andronova, N., Buja, L. E., Esch, M., and co-authors. 2006. Global mean cloud feedbacks in idealized climate change experiments. Geophys. Res. Lett. 33, L07718, 10.1029/2005GL025370.
   Google Scholar
• Rossow, W. B. and Schiffer, R. A. 1991. ISCCP cloud data products. Bull. Am. Met. Soc. 72, 2–20.
   Web of Science ®Google Scholar
• Schneider, E. K., Kirtman, B. P. and Lindzen, R. S. 1999. Tropospheric water vapor and climate sensitivity. J. Atmos. Sc i. 56, 1649–1658.
   Google Scholar
• Sloan, L. C. and Pollard, D. 1998. Polar stratospheric clouds: A high latitude warming mechanism in an ancient greenhouse world. Geophys. Res. Lett. 25, 3517–3520.
   Web of Science ®Google Scholar
• Soden, B. J., Broccoli, A. J. and Hemler, R. S. 2004. On the use of cloud forcing to estimate cloud feedback. J. Climate 17, 3661–3665.
   Web of Science ®Google Scholar
• Soden, B. J. and Held, I. M. 2006. An assessment of climate feedbacks in coupled ocean atmosphere models. J. Climate 19, 3354–3360.
   Web of Science ®Google Scholar
• Stephens, G. L. 2005. Cloud feedbacks in the climate system: a critical review. J. Climate 18, 237–273.
   Web of Science ®Google Scholar
• Stephens, G. L., Wood, N. B. and Gabriel, P. M. 2004. An assessment of the parameterization of subgrid-scale cloud effects on radiative transfer. Part I: vertical overlap. J. Atmos. Sc i. 61, 715–732.
   Google Scholar
• Taylor, K. E. and Ghan, S. J. 1992. An analysis of cloud liquid water feedback and global climate sensitivity in a general circulation model. J. Climate 5, 907–919.
   Web of Science ®Google Scholar
• Vavrus, S. J. 2004. The impact of cloud feedbacks on arctic climate under greenhouse forcing. J. Climate 17, 603–615.
   Web of Science ®Google Scholar
• Wetherald, R. T. and Manabe, S. 1988. Cloud feedback processes in a general circulation model. J. Atmos. Sc i. 45, 1397–1415.
   Web of Science ®Google Scholar
• Yin, J. H. 2005. A consistent poleward shift of the storm tracks in simulations of 21st century climate. Geophys. Res. Lett. 32, L18701.
   Web of Science ®Google Scholar
• Webb, M. J., Senior, C. A., Sexton, D. M. H., Ingram, W.J., Williams, K. D., and co-authors. 2006. On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles. Clim. Dyn. 27, 17-38.
   Google Scholar
• Zhang, M. H., Hack, J. J., Kiehl, J. T. and Cess, R. D. 1994. Diagnostic study of climate feedback processes in atmospheric general circulation models. J. Geophys. Res. 99 (18), 5525-5538.
   Web of Science ®Google Scholar