A multimodel study of parametric uncertainty in predictions of climate response to rising greenhouse gas concentrations

Journal of Climate

Volumn 24, Issue 5, 2011, Pages 1362-1377

  Sanderson, Benjamin M ^a  

^a NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

Author keywords

Climate change; Climate prediction; Ensembles; General circulation models; Greenhouse gases

Indexed keywords

ATMOSPHERE MODELS; CLIMATE PREDICTION; CLIMATE SENSITIVITY; COMMUNITY ATMOSPHERE MODEL; DIVERSE RANGE; ENSEMBLES; FUTURE CLIMATE; GAS CONCENTRATION; GENERAL CIRCULATION MODEL; GENERAL CIRCULATION MODELS; HIGH LATITUDES; LONG WAVES; MULTI-MODEL; PARAMETERIZATIONS; PARAMETRIC UNCERTAINTIES; POSITIVE FEEDBACK; RADIATIVE FLUXES; REGIONAL LEVELS; WATER VAPOR CONCENTRATION;

CLIMATOLOGY; COMPUTER SIMULATION; FEEDBACK; GLOBAL WARMING; GREENHOUSE GASES; MODELS; WATER VAPOR;

CLIMATE MODELS;

CLIMATE CHANGE; CLIMATE PREDICTION; COMPUTER SIMULATION; ENSEMBLE FORECASTING; GENERAL CIRCULATION MODEL; GREENHOUSE GAS; UNCERTAINTY ANALYSIS; WATER VAPOR;

EID: 79954998482     PISSN: 08948755     EISSN: None     Source Type: Journal    
DOI: 10.1175/2010JCLI3498.1     Document Type: Article

References (35)

1. Boville, B. A., P. J. Rasch, J. J. Hack, and J. R. McCaa, 2006: Representation of clouds and precipitation processes in the Community Atmosphere Model version 3 (CAM3). J. Climate, 19, 2184-2198.
2. Cess, R. D., and G. L. Potter, 1988: A methodology for understanding and intercomparing atmospheric climate feedback processes in general circulation models. J. Geophys. Res., 93, 8305-8314.
3. Collins, W. D., and Coauthors, 2006: The Community Climate System Model version 3 (CCSM3). J. Climate, 19, 2122-2143.
4. Gent, P., S. Yeager, R. Neale, S. Levis, and D. Bailey, 2009: Improvements in a half degree atmosphere/land version of the CCSM.ClimateDyn., 34, 819-833, doi:10.1007/s00382-009-0614-8.
5. Gettelman, A., and Q. Fu, 2008: Observed and simulated uppertropospheric water vapor feedback. J. Climate, 21, 3282-3289.
6. Gregory, D., and P. R. Rowntree, 1990: A mass flux convection scheme with representation of cloud ensemble characteristics and stability-dependent closure. Mon. Wea. Rev., 118, 1483-1506.
7. Hack, J. J., 1994: Parameterization of moist convection in the National Center for Atmospheric Research community climate model (CCM2). J. Geophys. Res., 99, 5551-5568.
8. Heymsfield, A., 1977: Precipitation development in stratiform ice clouds: A microphysical and dynamical study. J. Atmos. Sci., 34, 367-381.
9. Jackson, C., M. Sen, G. Huerta, Y. Deng, and K. Bowman, 2008: Error reduction and convergence in climate prediction. J. Climate, 21, 6698-6709.
10. Joshi, M. M., M. J. Webb, A. C. Maycock, and M. Collins, 2010: Stratospheric water vapour and high climate sensitivity in a version of the HadSM3 climate model. Atmos. Chem. Phys. Discuss., 10, 6241-6255, doi:10.5194/acpd-10-6241-2010.
11. Knight, C. G., and Coauthors, 2007: Association of parameter, software, and hardware variation with large-scale behavior across 57,000 climate models. Proc. Natl. Acad. Sci. USA, 104, 12 259-12 264.
12. Knutti, R., G. A. Meehl, M. R. Allen, and D. A. Stainforth, 2006: Constraining climate sensitivity from the seasonal cycle in surface temperature. J. Climate, 19, 4224-4233.
13. Knutti, R., and Coauthors, 2008: A review of uncertainties in global temperature projections over the twenty-first century. J. Climate, 21, 2651-2663.
14. Lin, S.-J., 2004:A "vertically Lagrangian" finite-volume dynamical core for global models. Mon. Wea. Rev., 132, 2293-2307.
15. Locatell, J., and P. Hobbs, 1974: Fall speeds and masses of solid precipitation particles. J. Geophys. Res., 79, 2185-2197.
16. Murphy, J. M., D. M. H. Sexton, D. N. Barnett, G. S. Jones, M. J. Webb, M. Collins, and D. A. Stainforth, 2004: Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature, 430, 768-772.
17. Murphy, J. M., B. B. B. Booth, M. Collins, G. R. Harris, D. M. H. Sexton, and M. J. Webb, 2007:Amethodology for probabilistic predictions of regional climate change from perturbed physics ensembles. Philos. Trans. Roy. Soc. London, A365, 1993.
18. Neale, R., J. Richter, and M. Jochum, 2008: The impact of convection on ENSO: From a delayed oscillator to a series of events. J. Climate, 21, 5904-5924.
19. Oleson,K.W., andCoauthors, 2008: Improvements to theCommunity Land Model and their impact on the hydrological cycle. J. Geophys Res., 113, G01021, doi:10.1029/2007JG000563.
20. Piani, C., D. J. Frame, D. A. Stainforth, and M. R. Allen, 2005: Constraints on climate change from a multi-thousand member ensemble of simulations. Geophys. Res. Lett., 32, L23825, doi:10.1029/2005GL024452.
21. Raval, A., and V. Ramanathan, 1989: Observational determination of the greenhouse effect. Nature, 342, 758-761.
22. Raymond, D., and A.Blyth, 1992: Extension of the stochasticmixing model to cumulonimbus clouds. J. Atmos. Sci., 49, 1968-1983.
23. Richter, J., and P. Rasch, 2008: Effects of convective momentum transport on the atmospheric circulation in the Community Atmosphere Model, version 3. J. Climate, 21, 1487-1499.
24. Sanderson, B., and Coauthors, 2008a: Constraints on model response to greenhouse gas forcing and the role of subgrid-scale processes. J. Climate, 21, 2384-2400.
25. Sanderson, B., C. Piani, W. Ingram, D. Stone, and M. Allen, 2008b: Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations. Climate Dyn., 30, 175-190.
26. Sanderson, B., K. Shell, and W. Ingram, 2009: Climate feedbacks determined using radiative kernels in a multi-thousand member ensemble of AOGCMs. Climate Dyn., 35, 1219-1236.
27. Stainforth, D. A., and Coauthors, 2005: Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature, 433, 403-406.
28. Stöckli, R., and Coauthors, 2008: Use of FLUXNET in the Community Land Model development. J. Geophys Res., 113, G01025, doi:10.1029/2007JG000562.
29. Trenberth, K. E., and J. T. Fasullo, 2009: Global warming due to increasing absorbed solar radiation. Geophys. Res. Lett., 36, L07706, doi:10.1029/2009GL037527.
30. Webb, M. J., C. Senior, S. Bony, and J.-J. Morcrette, 2001: Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models. Climate Dyn., 17, 905-922.
31. Webb, M. J., and Coauthors, 2006: On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles. Climate Dyn., 27, 17-38.
32. Wetherald, R., and S. Manabe, 1988: Cloud feedback processes in a general circulation model. J. Atmos. Sci., 45, 1397-1416.
33. Wu, X., L. Deng, X. Song, and G. Zhang, 2007: Coupling of convective momentum transport with convective heating in global climate simulations. J. Atmos. Sci., 64, 1334-1349.
34. 2 increase between two perturbed physics ensembles. J. Climate, 23, 1392-1410.
35. Zhang, G. J., and N. A. McFarlane, 1995: Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre general circulation model. Atmos.-Ocean, 33, 407-446.