We acknowledge the modeling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and the WCRP's Working Group on Coupled Modelling (WGCM) for their roles in making available the WCRP CMIP5 multimodel dataset. Support of this dataset is provided by the Office of Science, U.S. Department of Energy. The U.S. authors acknowledge the support of NOAA Climate Program Office “Modeling, Analysis, Predictions and Projections” (MAPP Grant NA11OAR4310094) Program as part of the CMIP5 Task Force. This research is also supported partly by the CAS/SAFEA International Partnership Program for Creative Research Teams (KZZD-EW-TZ-03) and WKC foundation. We are thankful to two anonymous reviewers for their constructive and insightful suggestions. We are thankful to the two anonymous reviewers whose constructive comments strengthened this paper.
Arora, V. K., and Coauthors, 2011: Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases. Geophys. Res. Lett., 38, L05805, doi:10.1029/2010GL046270.
Collins, M., S. F. B. Tett, and C. Cooper, 2001: The internal climate variability of HadCM3, a version of the Hadley Centre coupled model without flux adjustments. Climate Dyn., 17, 61–81.
Dai, A., K. E. Trenberth, and T. R. Karl, 1999: Effects of clouds, soil moisture, precipitation, and water vapor on diurnal temperature range. J. Climate, 12, 2451–2473.
Donner, L. J., and Coauthors, 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3. J. Climate, 24, 3484–3519.
Dunne, J. P., and Coauthors, 2012: GFDL's ESM2 global coupled climate–carbon earth system models. Part I: Physical formulation and baseline simulation characteristics. J. Climate, 25, 6646–6665.
Durre, I., and J. M. Wallace, 2001: Factors influencing the cold-season diurnal temperature range in the United States. J. Climate, 14, 3263–3278.
Folland, C. K., and Coauthors, 2002: Observed climate variability and change. Climate Change 2001: The Scientific Basis, J. T. Houghton et al., Eds., Cambridge University Press, 99–181.
Hourdin, F., and Coauthors, 2006: The LMDZ4 general circulation model: Climate performance and sensitivity to parametrized physics with emphasis on tropical convection. Climate Dyn.,27, 787–813.
Jones, C. D., and Coauthors, 2011: The HadGEM2-ES implementation of CMIP5 centennial simulations. Geosci. Model Dev., 4, 543–570, doi:10.5194/gmd-4-543-2011.
Karl, T. R., and Coauthors, 1993: A new perspective on recent global warming: Asymmetric trends of daily maximum and minimum temperature. Bull. Amer. Meteor. Soc., 74, 1007–1024.
Kumar, S., J. L. Kinter III, P. A. Dirmeyer, Z. Pan, and J. Adams, 2013a: Multi-decadal climate variability and the “warming hole” in North America: Results from CMIP5 twentieth- and twenty-first-century climate simulations. J. Climate,26, 3511–3527.
Kumar, S., V. Merwade, S. Rao, B. C. Pijanowski, 2013b: Characterizing long-term land use/cover change in the United States from 1850 to 2000 using a nonlinear bi-analytical model. Ambio,42, 285–297, doi:10.1007/s13280-012-0354-6.
Kunkel, K. E., X.-Z. Liang, J. Zhu, and Y. Lin, 2006: Can CGCMs simulate the twentieth century “warming hole” in the central United States. J. Climate, 19, 4137–4153.
Leibensperger, E. M., and Coauthors, 2011: Climatic effects of 1950–2050 changes in US anthropogenic aerosols—Part 1: Aerosol trends and radiative forcing. Atmos. Chem. Phys. Discuss., 11, 24 085–24 125, doi:10.5194/acpd-11-24085-2011.
Liang, X.-Z., J. Pan, J. Zhu, K. E. Kunkel, J. X. L. Wang, and A. Dai, 2006: Regional climate model downscaling of the U.S. summer climate and future change. J. Geophys. Res., 111, D10108, doi:10.1029/2005JD006685.
Liu, X. D., and B. D. Chen, 2000: Climatic warming in the Tibetan Plateau during recent decades. Int. J. Climatol., 20, 1729–1742.
Mantua, N. J., S. R. Hare, Y. Zhang, J. M. Wallace, and R. C. Francis, 1997: A Pacific interdecadal climate oscillation with impacts on salmon production. Bull. Amer. Meteor. Soc., 78, 1069–1079.
Meehl, G. A., W. M. Washington, C. M. Ammann, J. M. Arblaster, T. M. L. Wigley, and C. Tebaldi, 2004: Combinations of natural and anthropogenic forcings in twentieth-century climate. J. Climate, 17, 3721–3727.
Meehl, G. A., J. M. Arblaster, and G. Branstator, 2012: Mechanisms contributing to the warming hole and the consequent U.S. east–west differential of heat extremes. J. Climate, 25, 6394–6408.
Miller, A., D. Cayan, T. Barnett, N. Graham, and J. Oberhuber, 1994: The 1976–77 climate shift of the Pacific Ocean. Oceanography, 7, 21–26.
Moss, R. H., and Coauthors, 2010: The next generation of scenarios for climate change research and assessment. Nature, 463, 747–756, doi:10.1038/nature08823.
New, M. G., M. Hulme, and P. D. Jones, 2000: Representing twentieth-century space–time climate variability. Part II: Development of 1901–96 monthly grids of terrestrial surface climate. J. Climate, 13, 2217–2238.
Pan, Z., R. W. Arritt, E. S. Takle, W. J. Gutowski Jr., C. J. Anderson, and M. Segal, 2004: Altered hydrologic feedback in a warming climate introduces a “warming hole.” Geophys. Res. Lett., 31, L17109, doi:10.1029/2004GL020528.
Pan, Z., M. Segal, X.-Z. Li, and B. Zib, 2009: Global climate change impact on the Midwestern U.S.—A summer cooling trend. Regional Climate Variability, Predictability, and Change in Midwestern USA, S. Pryor, Ed., Indiana University Press, 29–41.
Portmann, R. W., S. Solomon, and G. C. Hegel, 2009: Spatial and seasonal patterns in climate change, temperatures, and precipitation across the United States. Proc. Natl. Acad. Sci. USA, 106, 7324–7329.
Raddatz, T. J., and Coauthors, 2007: Will the tropical land biosphere dominate the climate–carbon cycle feedback during the twenty first century? Climate Dyn., 29, 565–574, doi:10.1007/s00382-007-0247-8.
Robinson, W. A., R. Reudy, and J. E. Hansen, 2002: General circulation model simulations of recent cooling in the east-central United States. J. Geophys. Res., 107, 4748, doi:10.1029/2001JD001577.
Rotstayn, L., M. Collier, M. Dix, Y. Feng, H. Gordon, S. O'Farrell, I. Smith, and J. Syktus, 2010: Improved simulation of Australian climate and ENSO-related climate variability in a GCM with an interactive aerosol treatment. Int. J. Climatol.,30, 1067–1088, doi:10.1002/joc.1952.
Schmidt, G. A., and Coauthors, 2006: Present day atmospheric simulations using GISS ModelE: Comparison to in situ, satellite and reanalysis data. J. Climate, 19, 153–192.
Schubert, S. D., M. J. Suarez, P. J. Region, R. D. Koster, and J. T. Bacmeister, 2004: On the cause of the 1930s Dust Bowl. Science, 303, 1855–1859.
Sheffield, J., and Coauthors, 2013a: North American climate in CMIP5 experiments. Part I: Evaluation of 20th century continental and regional climatology. J. Climate, in press.
Sheffield, J., and Coauthors, 2013b: North American climate in CMIP5 experiments. Part II: Evaluation of 20th century intra-seasonal to decadal variability. J. Climate, in press.
Solomon, S., D. Qin, M. Manning, M. Marquis, K. Averyt, M. M. B. Tignor, H. L. Miller Jr., and Z. Chen, Eds., 2007: Climate Change 2007: The Physical Science Basis. Cambridge University Press, 996 pp.
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.
Tett, S. F. B., and Coauthors, 2002: Estimation of natural and anthropogenic contributions to twentieth century temperature change. J. Geophys. Res., 107 (D16), doi:10.1029/2000JD000028.
Thomson, A., and Coauthors, 2011: RCP4.5: A pathway for stabilization of radiative forcing by 2100. Climatic Change, 109, 77–94, doi:10.1007/s10584-011-0151-4.
Voldoire, A., and Coauthors, 2013: The CNRM-CM5.1 global climate model: Description and basic evaluation. Climate Dyn., 40, 2091–2121, doi:10.1007/s00382-011-1259-y.
Volodin, E. M., N. A. Dianskii, and A. V. Gusev, 2010: Simulating present-day climate with the INMCM4.0 coupled model of the atmospheric and oceanic general circulations. Atmos. Oceanic Phys., 46, 414–431.
Vose, R. S., D. R. Easterling, and B. Gleason, 2005: Maximum and minimum temperature trends for the globe: An update through 2004. Geophys. Res. Lett., 32, L23822, doi:10.1029/2005GL024379.
Wang, H., S. Schubert, M. Suarez, J. Chen, M. Hoerling, A. Kumar, and P. Pegion, 2009: Attribution of the seasonality and regionality in climate trends over the United States during 1950–2000. J. Climate, 22, 2571–2590.
Watanabe, M., and Coauthors, 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312–6335.
Weaver, S. J., 2013: Factors associated with decadal variability in Great Plains summertime surface temperatures. J. Climate, 26, 343–350.
Wu, T., and Coauthors, 2010: The Beijing Climate Center atmospheric general circulation model: Description and its performance for the present-day climate. Climate Dyn., 34, 123–147.
Yukimoto, S., and Coauthors, 2011: Meteorological Research Institute-Earth System Model version 1 (MRI-ESM1)—Model description. Meteorological Research Institute Tech. Rep. 64, 83 pp. [Available online at www.mri-jma.go.jp/Publish/Technical/DATA/VOL_64/index_en.html.]
Zhou, L., R. E. Dickinson, Y. Tian, R. Vose, and Y. Dai, 2007: Impact of vegetation removal and soil aridation on diurnal temperature range in a semiarid region—Application to the Sahel. Proc. Natl. Acad. Sci. USA, 104, 17 937–17 942.
Zhou, T. J., and Coauthors, 2005: The climate system model FGOALS using LASG/IAP spectral AGCM SAMIL as its atmospheric component (in Chinese). Acta Meteor. Sin., 63, 702–715.
Most studies of GCM intercomparison use mean surface air temperature, masking the difference in maximum and minimum temperatures.
The extent of the member spread may have been underestimated in CMIP5 experiments since the great majority of the models used varying start time only, not the perturbation method.