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Räisänen, Jouni (2007)
Publisher: Co-Action Publishing
Journal: Tellus A
Languages: English
Types: Article
Subjects:
How much can we trust model-based projections of future anthropogenic climate change? This review attempts to give an overview of this important but difficult topic by using three main lines of evidence: the skill of models in simulating present-day climate, intermodel agreement on future climate changes, and the ability of models to simulate climate changes that have already occurred. A comparison of simulated and observed present-day climates shows good agreement for many basic variables, particularly at large horizontal scales, and a tendency for biases to vary in sign between different models, but there is a risk that these features might be partly a result of tuning. Overall, the connection between model skill in simulating present-day climate and the skill in simulating future climate changes is poorly known. An intercomparison of future climate changes between models shows a better agreement for changes in temperature than that for precipitation and sea level pressure, but some aspects of change in the latter two variables are also quite consistent between models. A comparison of simulations with observed climate changes is, in principle, a good test for the models, but there are several complications. Nonetheless, models have skilfully simulated many large-scale aspects of observed climate changes, including but not limited to the evolution of the global mean surface air temperature in the 20th century. Furthermore, although there is no detailed agreement between the simulated and observed geographical patterns of change, the grid box scale temperature, precipitation and pressure changes observed during the past half-century generally fall within the range of model results. Considering the difficulties associated with other sources of information, the variation of climate changes between different models is probably the most meaningful measure of uncertainty that is presently available. In general, however, this measure is more likely to underestimate than overestimate the actual uncertainty.
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    • Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P. and coauthors. 2003. The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present). J. Hydrometeor. 4, 1147-1167.
    • Allan, R. J. and Ansell, T. J. 2006. A new globally complete monthly historical gridded mean sea level pressure data set (HadSLP2): 1850- 2004. J. Climate, in press.
    • Allen, M. R. and Ingram, W. J. 2002. Constraints on future changes in climate and the hydrologic cycle. Nature 419, 224-232.
    • Allen, M. R., Stott, P. A., Mitchell, J. F. B., Schnur, R. and Delworth, T. L. 2000. Quantifying the uncertainty in forecasts of anthropogenic climate change. Nature 407, 617-620.
    • Anderson, T. L., Charlson, R. J., Schwartz, S. E., Knutti, R., Boucher, O. and co-authors. 2003. Climate forcing by aerosols - a hazy picture. Science 300, 1103-1104.
    • Andreae, M. O., Jones, C. D. and Cox, P. M. 2005. Strong present-day aerosol cooling implies a hot future. Nature 435, 1187-1190.
    • Andronova, N. G. and Schlesinger, M. E. 2001. Objective estimation of the probability density function of climate sensitivity. J. Geophys. Res. 106, 22605-22611.
    • Annan, J. D. and Hargreaves, J. C. 2006. Using multiple observationallybased constraints to estimate climate sensitivity. Geophys. Res. Lett. 33, L06704.
    • Annan, J. D., Hargreaves, J. C., Ohgaito, R., Abe-Ouchi, A. and Emori, S. 2005. Efficiently constraining climate sensitivity with paleoclimate simulations. Scientific Online Letters on the Atmosphere 1, 181- 184.
    • Barnett, T. P. and Schlesinger, M. E. 1987. Detecting changes in global climate induced by greenhouse gases. J. Geophys. Res. 92, 14772- 14780.
    • Barnett, T. P., Pierce, D. W., AchutaRao, K. M., Gleckler, P. J., Santer, B. D. and co-authors. 2005. Penetration of human-induced warming into the world's oceans. Science 309, 284-287.
    • Berger, A. 1978. Long-term variations of caloric solar radiation resulting from the Earth's orbital elements. Quaternary Res. 9, 139-167.
    • Bertrand, C., van Ypersele, J.-P. and Berger, A. 2002. Are natural climate forcings able to counteract the projected anthropogenic global warming? Climatic Change 55, 413-427.
    • Boer, G. 2000. Analysis and verification of model climate. In: Numerical Modeling of the Global Atmosphere in the Climate System (eds P. Mote and A. O'Neill). Kluwer Academic Publishers, Dordrecht, 59- 82.
    • Boer, G. J. and Yu, B. 2003. Climate sensitivity and climate state. Climate Dyn. 21, 167-176.
    • Bony, S., Dufresne, J. L., Le Treut, H., Morcrette, J. J. and Senior, C. A. 2004. On dynamic and thermodynamic components of cloud changes. Climate Dyn. 22, 71-86.
    • Boucher, O. and Haywood, J. 2001. On summing the components of radiative forcing of climate change. Climate Dyn. 18, 297-302.
    • Braganza, K., Karoly, D. J. and Arblaster, J. M. 2004. Diurnal temperature range as an index of global climate change during the twentieth century. Geophys. Res. Lett. 31, D13217, doi:10.1029/ 2004GL019998.
    • Broccoli, A. J., Dixon, K. W., Delworth, T. L., Knutson, T. R., Stouffer, R. J. and Zeng, F. 2003. Twentieth-century temperature and precipitation trends in ensemble climate simulations including natural and anthropogenic forcing. J. Geophys. Res. 108, D4798, doi:10.1029/2003JD003812.
    • CCSP (US Climate Change Science Program) 2006. Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differences. United States Climate Science Program and the Subcommittee on Global Change Research, Washington DC, USA, 164 pp.
    • Cess, R. D., Potter, G. L., Blanchet, J. P., Boer, G. J., Del Genio, A. D. and co-authors. 1990. Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. J. Geophys. Res. 95, 16601-16615.
    • Cess, R. D., Zhang, M. H. Ingram, W. J., Potter, G. L., Alekseev, V. and co-authors. 1996. Cloud feedback in atmospheric general circulation models: an update. J. Geophys. Res. 101, 12791-12794.
    • Charney, J. G. 1979. Carbon Dioxide and Climate: A Scientific Assessment. National Academy, Washington, DC, USA, 22 pp.
    • Claussen, M. Mysak, L. A., Weaver, A. J., Crucifix, M., Fichefet, T. and co-authors. 2002. Earth system models of intermediate complexity: closing the gap in the spectrum of climate system models. Climate Dyn. 18, 579-586.
    • Colman, R. 2003. A comparison of climate feedbacks in general circulation models. Climate Dyn. 20, 865-873.
    • Covey, C., Achuta Rao, K. M., Cubasch, U., Jones, P., Lambert, S. J. and co-authors. 2003. An overview of results from the Coupled Model Intercomparison Project. Global Planet. Change 37, 103-133.
    • Cox, P. M., Betts, R. A., Jones, C. D., Spall, S. A. and Totterdell, I. J. 2000. Acceleration of global warming due to carbon cycle feedbacks in a coupled climate model. Nature 408, 184-187.
    • Cubasch, U., Meehl, G. A., Boer, G. J., Stouffer, R. J., Dix, M. and co-authors. 2001. Projections of future climate change. In: Climate change 2001. The Scientific Basis (eds J. T. Houghton, Y. Ding, D. J. Griggs, M. Noguer, P. J. van der Linden, X. Dai, K. Maskell and C. A. Johnson). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 525-582.
    • Delworth, T. L. and Knutson, T. R. 2000. Simulation of early 20th century global warming. Science 287, 2246-2250.
    • Feddema, J. I., Oleson, K. W., Bonan, G. B., Mearns, L. O., Buja, L. E. and co-authors. 2005. The importance of land-cover change in simulating future climates. Science 310, 1674-1678.
    • Folland, C. K., Karl, T. R., Christy, J. R., Clarke, R. A., Gruza, G. V. and co-authors. 2001a. Observed climate variability and change. In: Climate change 2001. The Scientific Basis (eds J. T. Houghton, Y. Ding, D. J. Griggs, M. Noguer, P. J. van der Linden, X. Dai, K. Maskell, and C. A. Johnson). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 99-181.
    • Folland, C. K., Rayner, N. A., Brown, S. J., Smith, T. M., Shen, S. S. P. and co-authors. 2001b. Global temperature change and its uncertainties since 1861. Geophys. Res. Lett. 28, 2621-2624.
    • Forest, C. E., Stone, P. H., Sokolov, A. P., Allen, M. R. and Webster, M. D. 2002. Quantifying uncertainties in climate system properties with the use of recent climate observations. Science 295, 113-117.
    • Forest, C. E., Stone, P. H. and Sokolov, A. P. 2006. Estimated PDFs of climate system properties including natural and anthropogenic forcing. Geophys. Res. Lett. 33, L01705, doi:10.1029/2005GL023977.
    • Forster, P. M. de F. and Gregory, J. M. 2006. The climate sensitivity and its components diagnosed from Earth Radiation Budget data. J. Climate 19, 39-52.
    • Frame, D. J., Booth, B. B., Kettleborough, J. A., Stainforth, D. A., Gregory, J. M. and co-authors. 2005. Constraining climate forecasts: the role of prior assumptions. Geophys. Res. Lett. 32, L09702, doi:10.1029/2004GL022241.
    • Friedlingstein, P., Dufresne, J.-L., Cox, P. M. and Rayner, P. 2003. How positive is the feedback between climate change and the carbon cycle? Tellus 55B, 692-700.
    • Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W. and coauthors. 2006. Climate - carbon cycle feedback analysis: results from the C4MIP model intercomparison. J. Climate 19, 3337-3353.
    • Gates, W. 1992. The Atmospheric Model Intercomparison Project. Bull. Amer. Meteor. Soc. 73, 1962-1970.
    • Gates, W. L., Boyle, J., Covey, C., Dease, C., Doutriaux, C. and coauthors. 1999. An overview of the results of the Atmospheric Model Intercomparison Project (AMIP I).Bull. Amer. Meteor. Soc. 80, 29-55.
    • Gillett, N. P., Weaver, A. J., Zwiers, F. W. and Wehner, M. F. 2004. Detection of volcanic influence on global precipitation. Geophys. Res. Lett. 31, L12217, doi: 10.1029/2004GL020044.
    • Gillett, N. P., Allan, R. J. and Ansell, T. J. 2005. Detection of external influence on sea level pressure with a multimodel ensemble. Geophys. Res. Lett. 32, L19714, doi: 10.1029/2005GL023640.
    • Giorgi, F. and Francisco, R. 2000. Evaluating uncertainties in the prediction of regional climate change. Geophys. Res. Lett. 27, 1295-1298.
    • Giorgi, F. and Mearns, L. O. 2002. Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the “reliability ensemble averaging” (REA) method. J. Climate 15, 1141-1158.
    • Giorgi, F. and Mearns, L. O. 2003. Probability of regional climate change based on the Reliability Ensemble Averaging (REA) method. Geophys. Res. Lett. 30, L1629, doi:10.1029/2003GL017130.
    • Giorgi, F., Hewitson, B., Christensen, J., Hulme, M., Von Storch, H. and co-authors. 2001. Regional climate information - evaluation and projections. In: Climate change 2001. The Scientific Basis (eds J. T. Houghton, Y. Ding, D. J. Griggs, M. Noguer, P. J. van der Linden, X. Dai, K. Maskell and C. A. Johnson). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 583-638.
    • Graham, R. J., Gordon, M., McLean, P. J., Ineson, S., Huddleston, M. R. and co-authors. 2005. A performance comparison of coupled and uncoupled versions of the Met Office seasonal prediction general circulation model. Tellus 57A, 320-339.
    • Greene, A. M., Goddard, L. and Lall, U. 2006. Probabilistic multimodel regional temperature change projections. J. Climate 19, 4326-4343.
    • Gregory, J. M., Stott, P. A., Cresswell, D. J., Rayner, N. A., Gordon, C. and Sexton, D. M. H. 2002a. Recent and future changes in Arctic sea ice simulated by the HadCM3 AOGCM. Geophys. Res. Lett. 29, L2175, doi:10.1029/2001GL014575.
    • Gregory, J. M., Stouffer, R. J., Raper, S. C. B., Stott, P. A. and Rayner, N. A. 2002b. An observationally based estimate of the climate sensititivy. J. Climate 15, 3117-3121.
    • Groisman, P. Ya. and Easterling, D. R. 1994. Variability and trends of total precipitation and snowfall over the United States and Canada. J. Climate 7, 184-205.
    • Groisman, P. Ya., Knight, R. W., Easterling, D. R., Karl, T. R., Hegerl, G. C. and Razuvaev, V. N. 2005. Trends in intense precipitation in the climate record. J. Climate 18, 1326-1350.
    • Grotch, S. L. and MacCracken, M. C. 1991. The use of general circulation models to predict regional climate change. J. Climate 4, 286- 303.
    • Hansen, J., Russell, G., Lacis, A., Fung, I. and Rind, D. 1985. Climate response times: dependence on climate sensitivity and ocean mixing. Science 229, 857-859.
    • Hansen, J., Sato, M. and Ruedy, R. 1997. Radiative forcing and climate response. J. Geophys. Res. 102, 6831-6864.
    • Hansen, J., Sato, M., Ruedy, R., Nazarenko, L., Lacis, A. and co-authors. 2005. Efficacy of climate forcings. J. Geophys. Res. 110, D18104, doi:10.1029/2005JD005776.
    • Hansen, J. E., Nazarenko, L., Ruedy, R., Sato, M., Willis, J. and coauthors. 2006. Earth's energy imbalance: confirmation and implications. Science 308, 1431-1435.
    • Hansen-Bauer, I., Førland, E. J., Haugen, J. E. and Tveito, O. E. 2003. Temperature and precipitation scenarios for Norway: comparison of results from dynamical and empirical downscaling. Climate Res. 25, 15-27.
    • Harris, G. R., Sexton, D. M. H., Booth, B. B. B., Collins, M., Murphy, J. M. and Webb, M. J. 2006. Frequency distributions of transient regional climate change from perturbed physics ensembles of general circulation model simulations. Climate Dyn. 27, 357-375.
    • Hartmann, D. L. 1994. Global Physical Climatology. Academic Press, San Diego, CA, USA, 411 pp.
    • Harvey, L. D. D. 2004. Characterizing the annual-mean climatic effect of anthropogenic CO2 and aerosol emissions in eight coupled atmosphere-ocean GCMs. Climate Dyn. 23, 569-599.
    • Harvey, L. D. D. and Kaufmann, R. K. 2002. Simultaneously constraining climate sensitivity and aerosol radiative forcing. J. Climate 15, 2837-2861.
    • Harvey, D., Gregory, J., Hoffert, M., Jain, A., Lal, M. and co-authors. 1997. An introduction to simple climate models used in the IPCC Second Assessment Report. IPCC Technical Paper 2 (eds J. T. Houghton, L. G. Meira Filho, D. Griggs and K. Maskell), IPCC, Geneva, Switzerland, 51 pp.
    • Hegerl, G. C., Crowley, T., Hyde, W. T. and Frame, D. 2006. Climate sensitivity constrained by temperature reconstructions over the past seven centuries. Nature 440, 1029-1032.
    • Hellstro¨m, C., Chen, D., Achberger, C. and Ra¨isa¨nen, J. 2001. A Comparison of climate change scenarios for Sweden based on statistical and dynamical downscaling of monthly precipitation. Climate Res. 19, 45-55.
    • Hewitt, C., Senior, C. and Mitchell, J. 2001. The impact of dynamic sea-ice on the climatology and climate sensitivity of a GCM: a study of past present and future climates. Climate Dyn. 17, 655-668.
    • Hoffert, M. I. and Covey, C. 1992. Deriving global climate sensitivity from paleoclimatic reconstructions. Nature 360, 573-576.
    • Houghton, J. 2004. Global Warming. The Complete Briefing, 3rd Edition. Cambridge University Press, Cambridge, 382 pp.
    • Houghton, J. T., Ding, Y., Griggs, D. J., Noguer, M., van der Linden P. J. and Xiaosu, D. (eds) 2001. Climate Change 2001. The Scientific Basis. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 881 pp.
    • Hudson, D. A. and Jones, R. G. 2002. Simulations of present-day and future climate over southern Africa using HadAM3H. Hadley Centre Technical Note 38, Met Office, Bracknell, United Kingdom, 36 pp.
    • Hulme, M., Osborn, T. J. and Johns, T. C. 1998. Precipitation sensitivity to global warming: comparison of observations with HadCM2 simulations. Geophys. Res. Lett. 25, 3379-3382.
    • Huntingford, C. and Cox, P. M. 2000. An analogue model to derive additional climate change scenarios from existing GCM simulations. Climate Dyn. 16, 575-586.
    • IPCC WG1 2004. Workshop report, IPCC Working Group I Workshop on Climate Sensitivity, Paris, France, 26-29 July 2004, 177 pp.
    • Joshi, M., Shine, K., Ponater, M., Stuber, N., Sausen, R. and Li, L. 2003. A comparison of climate response to different radiative forcings in three general circulation models: towards an improved metric of climate change. Climate Dyn. 20, 843-854.
    • Kattenberg, A., Giorgi, F., Grassl, H., Meehl, G. A., Mitchell, J. F. B. and co-authors. 1996. Climate models - projections of future climate. Climate change 1995. The Science of Climate Change (eds J. T. Houghton, L. G. Meira Filho, B. A. Cllander, N. Harris, A. Kattenberg and K. Maskell). Cambridge University Press, Cambridge, 285-357.
    • Kiktev, D., Sexton, D. M. H., Alexander, L. and Folland, C. K. 2003. Comparison of modeled and observed trends in indices of daily climate extremes. J. Climate 16, 3560-3571.
    • Kistler, R., Kalnay, E., Collins, W., Saha, S., White, G. and co-authors. 2001. The NCEP-NCAR 50-Year Reanalysis: Monthly Means CDROM and Documentation. Bull. Amer. Meteor. Soc. 82, 247-268.
    • Kittel, T. G. F., Giorgi, F. and Meehl, G. A. 1998. Intercomparison of regional biases and doubled CO2-sensitivity of coupled atmosphereocean general circulation model experiments. Climate Dyn. 14, 1-15.
    • Knutson, T. R., Delworth, T. L., Dixon, K. W., Held, I. M., Lu, J. and co-authors. 2006. Assessment of twentieth-century regional surface temperature trends using the GFDL CM2 coupled models. J. Climate 19, 1624-1650.
    • Knutti, R., Meehl, G. A., Allen, M. R. and Stainforth, D. A. 2006. Constraining climate sensitivity from the seasonal cycle in surface temperature. J. Climate 19, 4224-4233.
    • Kohfeld, K. E. and Harrison, S. P. 2000. How well can we simulate past climates? Evaluating the models using global palaeoenvironmental datasets. Quaternary Sci. Rev. 19, 321-346.
    • Lambert, S. J. and Boer, G. J. 2001. CMIP1 evaluation and intercomparison of coupled climate models. Climate Dyn. 17, 83-106.
    • Lambert, F. H., Stott, P. A., Allen, M. R. and Palmer, M. A. 2004. Detection and attribution of changes in 20th century land precipitation. Geophys. Res. Lett. 31, L10203, doi:10.1029/2004GL019545.
    • Lambert, F. H., Gillett, N. P., Stone, D. A. and Huntingford, C. 2005. Attribution studies of observed land precipitation changes with nine coupled models. Geophys. Res. Lett. 32, L18704, doi:10.1029/2005GL023654.
    • Levitus, S., Antonov, J., Boyer, T. P. and Stephens, C. 2000. Warming of the world ocean. Science 287, 2225-2229.
    • Levitus, S., Antonov, J. and Boyer, T. 2005. Warming of the world ocean, 1955-2003. Geophys. Res. Lett. 32, L02604, doi:10.1029/2004GL021592.
    • Lindzen, R. S. 1990. Some coolness concerning global warming. Bull. Amer. Meteor. Soc. 71, 288-299.
    • Lindzen, R. S., Chou, M.-D. and Hou, A. Y. 2001. Does the Earth have and adaptive infrared iris? Bull. Amer. Meteor. Soc. 82, 417- 432.
    • Lopez, A., Tebaldi, C., New, M., Stainforth, D. A., Allen, M. R. and Kettleborough, J. A. 2006. Two approaches to quantifying uncertainty in global temperature changes. J. Climate 19, 4785-4796.
    • Lorenz, E. N. 1963. Deterministic nonperiodic flow. J. Atmos. Sci. 20, 130-141.
    • Manabe, S. and Wetherald, R. T. 1987. Large-scale changes of soil wetness induced by an increase in atmospheric carbon dioxide. J. Atmos. Sci. 44, 1211-1235.
    • Manabe, S., Stouffer, R. J., Spelman, M. J. and Bryan, K. 1991. Transient response of a coupled ocean-atmosphere model to gradual changes of atmospheric CO2. Part I: Annual mean response. J. Climate 4, 785- 818.
    • McAvaney, B. J., Covey, C., Joussaume, S., Kattsov, V., Kitoh, A. and co-authors. 2001. Model evaluation. In: Climate change 2001. The Scientific Basis (eds J. T. Houghton, Y. Ding, D. J. Griggs, M. Noguer, P. J. van der Linden, X. Dai, K. Maskell and C. A. Johnson). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 471-523.
    • McGuffie, K. and Henderson-Sellers, A. 2005. A Climate Modelling Primer, 3rd Edition. John Wiley & Sons, Chichester, 296 pp.
    • Meehl, G. A., Boer, G. J., Covey, C., Latif, M. and Stouffer, R. J. 2000. The Coupled Model Intercomparison Project (CMIP). Bull. Amer. Meteor. Soc. 81, 313-318.
    • Meehl, G. A., Washington, W. M., Arblaster, J. M. and Hu, A. 2004a. Factors affecting climate sensitivity in global coupled models. J. Climate 17, 1584-1596.
    • Meehl, G. A., Washington, W. M., Ammann, C. M., Arblaster, J. M., Wigley, T. M. L. and Tebaldi, C. 2004b. Combinations of natural and anthropogenic forcings in twentieth-century climate. J. Climate 17, 3721-3727.
    • Miller, R. L., Schmidt, G. A. and Shindell, D. T. 2006. Forced annular variations in the 20th century Intergovernmental Panel on Climate Change Fourth Assessment Report Models. J. Geophys. Res. 111, D18101, doi: 10.129/2005JD006323.
    • Mitchell, T. D. 2003. Pattern scaling: an examination of the accuracy of the technique for describing future climate. Climatic Change 60, 217-242.
    • Mitchell, J., Wilson, C. and Cunnington, W. 1987. On CO2 climate sensitivity and model dependence of results. Q. J. R.. Meteor. Soc. 113, 293-322.
    • Mitchell, J. F. B., Manabe, S., Tokioka, T. and Meleshko, V. 1990. Equilibrium climate change - and its implications for the future. In: Climate Change. The IPCC Scientific Assessment (eds J. T. Houghton, G. J. Jenkins and J. J. Ephraums). Cambridge University Press, Cambridge, United Kingdom, 131-172.
    • Mitchell, J. F. B., Johns, T. C., Eagles, M., Ingram, W. J. and Davis, R. A. 1999. Towards the construction of climate change scenarios. Climatic Change 41, 547-581.
    • Mitchell, T. D., Carter, T. R., Jones, P. D., Hulme, M. and New, M. 2004. A comprehensive set of high-resolution grids of monthly climate for Europe and the globe: the observed record (1901-2000) and 16 scenarios (2001-2100). Tyndall Centre Working Paper 55, 30 pp.
    • Mote, P. and O'Neill, A. (eds) 2000. Numerical Modeling of the Global Atmosphere in the Climate System. Kluwer Academic Publishers, Dordrecht, 517 pp.
    • Murphy, J. M., Sexton, D. M. H., Barnett, D. N., Jones, G. S., Webb, M. J. and co-authors. 2004. Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature 430, 768-772.
    • Nakic´enovic´, N. and Swart, R. (eds) 2000. Emissions Scenarios. A Special Report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 599 pp.
    • Neelin, J. D., Mu¨nnich, M., Su, H., Meyerson, J. E. and Holloway, C. E. 2006. Tropical drying trends in global warming models and observations. Proc. Nat. Acd. Sci. 103, 6110-6115.
    • Noh, Y., Cheon, W. G., Hong, S. Y. and Raasch, S. 2003. Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data. Boundary-Layer Meteorol. 107, 401-427.
    • Palmer, T. N. and Ra¨isa¨nen, J. 2002. Quantifying the risk of extreme seasonal precipitation events in a changing climate. Nature 415, 514- 517.
    • Palmer, T. N., Shutts, G. J., Hagedorn, R., Doblas-Reyes, F. J., Jung, T. and Leutbecher, M. 2005. Representing model uncertainty in weather and climate prediction. Ann. Rev. Earth. Planet. Sci. 33, 163-193.
    • Pan, Z., Christensen, J., Arritt, R., Gutowski, W., Takle, E. and Otieno, F. 2001. Evaluation of uncertainty in regional climate change simulations. J. Geophys. Res. 106, 17735-17751.
    • Petit, J. R., Jouzel, J., Raynaud, N. I., Barkov, N. I., Barnola, J. M. and co-authors. 1999. Climate and atmospheric history of the past 420,000 years from the Vostok ice core, Antarctica. Nature 399, 429-436.
    • Phillips, T. J., Potter, G. L., Williamson, D. L., Cederwall, R. T., Boyle, J. S. and co-authors. 2004. Evaluating parameterizations in general circulation models: climate simulation meets weather prediction. Bull. Amer. Meteor. Soc. 85, 1903-1915.
    • Piani, C., Frame, D. J., Stainforth, D. A. and Allen, M. R. 2005. Constraints on climate change from a multi-thousand member ensemble of simulations. Geophys. Res. Lett. 32, L23825, doi:10.1029/2005GL024452.
    • Pierce, D. W., Barnett, T. P., AchutaRao, K. M., Gleckler, P. J., Gregory, J. M. and Washington, W. M. 2006. Anthropogenic warming of the oceans: observations and model results. J. Climate 19, 1873-1900.
    • Ra¨isa¨nen, J. 2001. CO2-induced climate change in CMIP2 experiments. Quantification of agreement and role of internal variability. J. Climate 14, 2088-2104.
    • Ra¨isa¨nen, J. and Palmer, T. N. 2001. A probability and decision model analysis of a multimodel ensemble of climate change simulations. J. Climate 14, 3212-3226.
    • Ra¨isa¨nen, J., Hansson, U., Ullerstig, A., Do¨scher, R., Graham, L. P. and co-authors. 2004. European climate in the late twenty-first century: regional simulations with two driving global models and two forcing scenarios. Climate Dyn. 22, 13-31.
    • Ramaswamy, V., Boucher, O., Haigh, J., Hauglustaine, D., Haywood, J. and co-authors. 2001. Radiative forcing of climate change. In: Climate change 2001. The Scientific Basis (eds J. T. Houghton, Y. Ding, D. J. Griggs, M. Noguer, P. J. van der Linden, X. Dai, K. Maskell, and C. A. Johnson), Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 349-416.
    • Ramaswamy, V., Schwarzkopf, M. D., Randel, W. J., Santer, B. D., Soden, B. J. and Stenchikov, G. L. 2006. Anthropogenic and natural influences in the evolution of lower stratospheric cooling. Science 311, 1138-1141.
    • Roeckner, E., Bengtsson, L., Feichter, J., Lelieveld, J. and Rodhe, H. 1999. Transient climate change simulations with a coupled atmosphere-ocean GCM including the tropospheric sulfur cycle. J. Climate 12, 3004-3032.
    • Rowell, D. P. and Jones, R. G. 2006. Causes and uncertainty of future summer drying over Europe. Climate Dyn. 27, 281-299.
    • Ruosteenoja, K., Carter, T. R., Jylha¨, K. and Tuomenvirta, H. 2003. Future climate in world regions: and intercomparison of modelbased projections for the new IPCC emissions scenarios. The Finnish Environment 644, Finnish Environment Institute, Helsinki, Finland, 83 pp.
    • Santer, B. D., Wigley, T. M. L., Schlesinger, M. E. and Mitchell, J. F. B. 1990. Developing climate scenarios from equilibrium GCM results. Report 47, Max-Planck Institut fu¨r Meteorologie, Hamburg, Germany, 29 pp.
    • Santer, B. D., Wigley, T. M. L., Simmons, A. J., Ka˚llberg, P. W., Kelly, G. A. and co-authors. 2004. Identification of anthropogenic climate change using a second-generation reanalysis. J. Geophys. Res. 109, D21104, doi:10.1029/2004JD005075.
    • Sausen, R., Barthels, R. K. and Hasselmann, K. 1988. Coupled oceanatmosphere models with flux correction. Climate Dyn. 2, 154- 163.
    • Savija¨rvi, H. 1995. Error growth in a large numerical forecast system. Mon. Wea. Rev. 123, 212-221.
    • Schneider von Deimling, T., Held, H., Ganopolski, A. and Rahmstorf, S. 2006. Climate sensitivity estimated from ensemble simulations of glacial climate. Climate Dyn. 27, 149-163.
    • Schwartz, S. E. 2004. Uncertainty requirements in radiative forcing of climate change. J. Air Waste Manage. Assoc. 54, 1351- 1359.
    • Selten, F. M., Branstator, G. W., Dijkstra, H. A. and Kliphuis, M. 2004. Tropical origins for recent and future Northern Hemisphere climate change. Geophys. Res. Lett. 31, L21205, doi:10.1029/2004GL020739.
    • Senior, C. A. and Mitchell, J. 2000. The time-dependence of climate sensitivity. Geophys. Res. Lett. 27, 2685-2689.
    • Siegenthaler, U., Stocker, T. F., Monnin, E., L u¨thi, D., Schwander, J. and co-authors. 2005. Stable carbon cycle - climate relationship during the late Pleistocene. Science 310, 1313-1317.
    • Soden, B. J. and Held, I. M. 2006. An assessment of climate feedbacks in coupled ocean-atmosphere models. J. Climate 19, 3354- 3360.
    • Soden, B. J., Jackson, D. L., Ramaswamy, V., Schwarzkopf, M. D. and Huang, X. 2005. The radiative signature of upper tropospheric moistening. Science 310, 841-844.
    • Stainforth, D. A., Aina, T., Christensen, C., Collins, M., Fauli, N. and coauthors. 2005. Uncertainty in the predictions of the climate response to rising levels of greenhouse gases. Nature 433, 403-406.
    • Stott, P. A. and Kettleborough, J. A. 2002. Origins and estimates of uncertainty in predictions of twenty-first century temperature rise. Nature 416, 723-726.
    • Stott, P. A., Tett, S. F. B., Jones, G. J., Allen, M. R., Mitchell, J. F. B. and Jenkins, G. .J. 2000. External control of 20th century temperature by natural and anthropogenic forcings. Science 290, 2133- 2137.
    • Stott, P. A., Mitchell, J. F. B., Allen, M. R., Delworth, T. L., Gregory, J. M. and co-authors 2006a. Observational constraints on past attributable warming and predictions of future global warming. J. Climate 19, 3055-3069.
    • Stott, P. A., Kettleborough, J. A. and Allen, M. R. 2006b. Uncertainty in continental-scale temperature predictions. Geophys. Res. Lett. 33, L02708, doi:10.1029/2005GL024423.
    • Tebaldi, C., Smith, R., Nychka, D. and Mearns, L. O. 2005. Quantifying uncertainty in projections of regional climate change: A Bayesian Approach. J. Climate 18, 1524-1540.
    • Thorne, P. W., Parker, D. E., Christy, J. R. and Mears, C. A. 2005. Uncertainties in climate trends: lessons from upper-air temperature records. Bull. Amer. Meteor. Soc. 87, 1437-1442.
    • Trenberth, K. E. (ed.) 1992. Climate System Modeling. Cambridge University Press, Cambridge, 788 pp.
    • Trenberth, K. E., Fasullo, J. and Smith, L. 2005. Trends and variability in column-integrated atmospheric water vapor. Climate Dyn. 24, 741- 758.
    • Vose, R. S., Easterling, D. R. and Gleason, B. 2005. Maximum and minimum temperature trends for the globe: an update through 2004. Geophys. Res. Lett. 32, L23822, doi:10.1029/2005GL024379.
    • Watterson, I. G. 1998. An analysis of the global water cycle of present and doubled CO2 climate simulated by the CSIRO general circulation model. J. Geophys. Res. 103, 23113-23129.
    • 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. Climate Dyn. 27, 17-38.
    • Whetton, P. H., England, M. H., O'Farrell, S. P., Watterson, I. G. and Pittock, A. B. 1996. Global comparison of the regional rainfall results of enhanced greenhouse coupled and mixed layer ocean experiments: Implications for climate change scenario development. Climatic Change 33, 497-519.
    • Wigley, T. M. L. and Schlesinger, M. E. 1985. Analytical solution for the effect of increasing CO2 on global mean temperature. Nature 315, 649-652.
    • Wigley, T. M. L., Ammann, C. M., Santer, B. D. and Raper, S. C. B. 2005. Effect of climate sensitivity on the response to volcanic forcing. J. Geophys. Res. 110, D09107, doi:10.1029/2004JD005557.
    • Williamson, D. L. and Laprise, R. 2000. Numerical approximations for global atmospheric GCMs. In: Numerical Modeling of the Global Atmosphere in the Climate System (eds P. Mote and A. O'Neill). Kluwer Academic Publishers, Dordrecht, 147-219.
    • Yin, J. H., 2005. A consistent poleward shift of the storm tracks in simulations of 21st century climate. Geophys. Res. Lett. 32, L18701, doi:10.1029/2005GL023684.
    • Zhang, X. and Walsh, J. E. 2006. Toward a Seasonally Ice-Covered Arctic Ocean: Scenarios from the IPCC AR4 Model Simulations. J. Climate 19, 1730-1747.
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