Advertisement

Climate Dynamics

, Volume 30, Issue 2–3, pp 113–132 | Cite as

Evaluation of uncertainties in the CRCM-simulated North American climate

  • Ramón de ElíaEmail author
  • Daniel Caya
  • Hélène Côté
  • Anne Frigon
  • Sébastien Biner
  • Michel Giguère
  • Dominique Paquin
  • Richard Harvey
  • David Plummer
Article

Abstract

This work is a first step in the analysis of uncertainty sources in the RCM-simulated climate over North America. Three main sets of sensitivity studies were carried out: the first estimates the magnitude of internal variability, which is needed to evaluate the significance of changes in the simulated climate induced by any model modification. The second is devoted to the role of CRCM configuration as a source of uncertainty, in particular the sensitivity to nesting technique, domain size, and driving reanalysis. The third study aims to assess the relative importance of the previously estimated sensitivities by performing two additional sensitivity experiments: one, in which the reanalysis driving data is replaced by data generated by the second generation Coupled Global Climate Model (CGCM2), and another, in which a different CRCM version is used. Results show that the internal variability, triggered by differences in initial conditions, is much smaller than the sensitivity to any other source. Results also show that levels of uncertainty originating from liberty of choices in the definition of configuration parameters are comparable among themselves and are smaller than those due to the choice of CGCM or CRCM version used. These results suggest that uncertainty originated by the CRCM configuration latitude (freedom of choice among domain sizes, nesting techniques and reanalysis dataset), although important, does not seem to be a major obstacle to climate downscaling. Finally, with the aim of evaluating the combined effect of the different uncertainties, the ensemble spread is estimated for a subset of the analysed simulations. Results show that downscaled surface temperature is in general more uncertain in the northern regions, while precipitation is more uncertain in the central and eastern US.

Keywords

Domain Size Internal Variability NCEP Reanalysis Ensemble Spread Couple General Circulation Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors want to thank Claude Desrochers and Mourad Labassi for maintaining a user-friendly local computing environment at the Ouranos Consortium. We also would like to thank Dorothée Charpentier and Jillian Tomm for their help in the final formatting and editing of the manuscript. We would like to express our gratitude to the ECMWF, whose ERA40 data used in this study were obtained from the ECMWF data server. The collaboration of the Canadian Centre for Climate Modelling and Analysis (CCCma) in Victoria, BC is warmly acknowledged; without access to CCCma’s software, this project would not have been possible. René Laprise and Francis Zwiers have generously devoted time to the discussion of some sections of this manuscript. In addition, we would like to thank the three anonymous reviewers, whose suggestions contributed to improve the manuscript. This research was financially supported by the Ouranos Consortium.

References

  1. Alexandru A, de Elía R, Laprise R (2007) Internal variability in a regional climate model. Mon Weather Rev, in PressGoogle Scholar
  2. Bechtold P, Bazile E, Guichard F, Mascart P, Richard E (2001) A Mass flux convection scheme for regional and global models. Q J R Meteor Soc 127:869–886CrossRefGoogle Scholar
  3. Caya D, Biner S (2004) Internal variability of RCM simulations over an annual cycle. Clim Dyn 22:33–46CrossRefGoogle Scholar
  4. Caya D, Laprise R (1999) A semi-implicit semi-Lagrangian regional climate model: the Canadian RCM. Mon Weather Rev 127:341–362CrossRefGoogle Scholar
  5. Christensen OB, Gaertner MA, Prego JA, Polcher J (2001) Internal variability of regional climate models. Clim Dyn 17:875–887CrossRefGoogle Scholar
  6. Christensen JH, Carter TR, Giorgi F (2002) PRUDENCE employs new methods to assess European climate change. EOS 83:147CrossRefGoogle Scholar
  7. Davies HC (1976) A lateral boundary formulation for multi-level prediction models. Q J Roy Meteor Soc 102:405–418Google Scholar
  8. Déqué M, Marquet P, Jones RG (1998) Simulation of climate change over Europe using a global variable resolution general circulation model. Clim Dyn 14:173–189CrossRefGoogle Scholar
  9. Dessai S, Hulme M (2004) Does climate policy adaptation need probabilities? Clim Policy 4:107–128CrossRefGoogle Scholar
  10. Fiorino M (1997) AMIP II sea surface temperature and sea ice concentration observations. http://www-pcmdi.llnl.gov/projects/amip2/AMIP2EXPDSN/BCS/amip2bcs.html#Introduction
  11. Flato GM, Boer GJ (2001) Warming asymmetry in climate change simulations. Geophys Res Lett 28:195–198CrossRefGoogle Scholar
  12. Fox-Rabinovitz MS, Takacs LL, Govindaraju RC, Suarez MJ (2001) A variable-resolution stretched-grid general circulation model: regional climate simulation. Mon Weather Rev 129:453–469CrossRefGoogle Scholar
  13. Fu CB, Wang SY, Xiong Z, Gutowski WJ, Lee DK, McGregor J, Sato Y, Kato H, Kim JW, Su MS (2005) Regional climate model intercomparison project for Asia (RMIP). Bull Am Meteor Soc 86:257–266CrossRefGoogle Scholar
  14. Gal-Chen T, Somerville RCJ (1975) On the use of a coordinate transformation for the solution of the Navier-Stokes equations. J Comput Phys 17:209–228CrossRefGoogle Scholar
  15. Giorgi F, Bi X (2000) A study of internal variability of regional climate model. J Geophys Res 105:29503–29521CrossRefGoogle Scholar
  16. Giorgi F, Francisco R (2000) Uncertainties in regional climate change prediction: a regional analysis of ensemble simulations with the HADCM2 coupled AOGCM. Clim Dyn 16:169–182CrossRefGoogle Scholar
  17. Giorgi F, Mearns LO (1999) Introduction to special section: regional climate modeling revisited. J Geophys Res 104:6335–6352CrossRefGoogle Scholar
  18. Giorgi F, Mearns LO (2002) Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the “reliability ensemble averaging” (REA) method. J Clim 15:1141–1158CrossRefGoogle Scholar
  19. Giorgi F, Mearns LO, Shields C, McDaniel L (1998) Regional nested model simulations of present day and 2×CO2 climate over the Central Plains of the US. Clim Change 40:457–493CrossRefGoogle Scholar
  20. Goyette S, McFarlane NA, Flato GM (2000) Application of the Canadian regional climate model to the Laurentian Great Lakes region: implementation of a Lake Model. Atmos Ocean 38:481–503Google Scholar
  21. Gutowski WJ, Otieno FO, Raymond AW, Takle ES, Pan Z (2004) Diagnosis and attribution of a seasonal precipitation deficit in a US regional climate simulation. J Hydrometeor 5:230–242CrossRefGoogle Scholar
  22. Han J, Roads JO (2004) US climate sensitivity simulated with NCEP regional spectral model. Clim Change 62:115–154CrossRefGoogle Scholar
  23. Hagedorn R, Doblas-Reyes FJ, Palmer TN (2005) The rationale behind the success of multi-model ensembles in seasonal forecasting—I. Basic Concept Tellus 57A:219–233Google Scholar
  24. Jacob D, Podzun R (1997) Sensitivity study with the Regional Climate Model REMO. Meteor Atmos Phys 63:119–129CrossRefGoogle Scholar
  25. Jiao Y, Caya D (2006) An investigation of the summer precipitation simulated by the Canadian Regional Climate Model. Mon Weather Rev, in PressGoogle Scholar
  26. Juang HMH, Hong SY (2001) Sensitivity of the NCEP Regional Spectral model to domain size and nesting strategy. Mon Weather Rev 129:2904–2922CrossRefGoogle Scholar
  27. Jones RG, Murphy JM, Noguer M (1995) Simulation of climate change over Europe using a nested regional-climate model. I:Assessment of control climate, including sensitivity to location of lateral boundaries. Q J R Meteor Soc 121:1413–1449Google Scholar
  28. Kalnay E, Coauthors (1996) The NCEP-NCAR 40-year reanalyses project. Bull Am Meteor Soc 77:437–471CrossRefGoogle Scholar
  29. Kunkel KE, Andsager K, Liang X-Z, Arritt RW, Takle ES, Gutowski WJ, Pan Z (2002) Observations and regional climate model simulations of heavy precipitation events and seasonal anomalies: a comparison. J Hydrometeor 3:322–334CrossRefGoogle Scholar
  30. Laprise R, Caya D, Bergeron G, Giguère M (1997) The formulation of André Robert MC2 (mesoscale compressible community) model. Atmos Ocean 35:195–220Google Scholar
  31. Laprise R, Caya D, Giguère M, Bergeron G, Côté H, Blanchet J-P, Boer GJ, McFarlane NA (1998) Climate and climate change in western Canada as simulated by the Canadian Regional Climate Model. Atmos Ocean 36:119–167Google Scholar
  32. Laprise R, Caya D, Frigon A, Paquin D (2003) Current and perturbed climate as simulated by the second-generation Canadian Regional Climate Model (CRCM-II) over northwestern North America. Clim Dyn 21:405–421CrossRefGoogle Scholar
  33. Liang X-Z, Li L, Kunkel K (2004) Regional climate simulation of US precipitation during 1982–2002. Part I Annual cycle. J Clim 17:3510–3529CrossRefGoogle Scholar
  34. Lorant VN McFarlane N, Laprise R (2002) A numerical study using the Canadian Regional Climate Model for the PIDCAP period. Boreal Environ Res 7(3):203–210Google Scholar
  35. Lucas-Picher P, Caya D, Biner S (2004) RCM’s internal variability as function of domain size. Research activities in atmospheric and oceanic modelling, WMO/TD. J Côté Ed 1220(34):7.27–7.28Google Scholar
  36. Mearns L (2004) NARCCAP North American Regional Climate Change Assessment Program A Multiple AOGCM and RCM Climate Scenario Project over North America. AGU Fall Meeting, San FransiscoGoogle Scholar
  37. Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Clim 25:693–712CrossRefGoogle Scholar
  38. Moss RH, Schneider SH (2000) Uncertainties in guidance papers on the cross cutting issues of the third assessment report of the IPCC. Pachauri R, Tanaguchi T, Tanaka K (eds) World Meteorological Organisation, pp 33–51Google Scholar
  39. McFarlane NA, Boer GJ, Blanchet J-P, Lazare M (1992) The Canadian climate centre second-generation general circulation model and its equilibrium climate. J Clim 5:1013–1044CrossRefGoogle Scholar
  40. Miguez-Macho G, Stenchikov GL, Robock A (2004) Spectral nudging to eliminate the effects of domain position and geometry in regional climate simulations. J Geophys Res 109:D13104CrossRefGoogle Scholar
  41. Murphy JM, Sexton DMH, Barnett DN, Jones GS, Webb MJ, Collins M, Stainforth DA (2004) Quantification of uncertainties in a large ensemble of climate change simuations. Nature 430:768–772CrossRefGoogle Scholar
  42. Noguer M, Jones RG, Murphy JM (1998) Sources of systematic errors in the climatology of a regional climate model over Europe. Clim Dyn 14:691–712CrossRefGoogle Scholar
  43. Paquin D, Laprise R (2003) Traitement du bilan d’humidité interne au MRCC. Ouranos, Simulations group, Internal report No 2, 26 pp [available from D. Paquin, Ouranos, 550 Sherbrooke st west, 19 floor, Montreal, QC, Canada H3A 1B9]Google Scholar
  44. Pan Z, Christensen JH, Arritt RW, Gutowski WJ, Takle ES, Otieno F (2001) Evaluation of uncertainties in regional climate change simulations. J Geophys Res 106:17735–17751CrossRefGoogle Scholar
  45. Plummer DA, Caya D, Frigon A, Côté H, Giguère M, Paquin D, Biner S, Harvey R, de Elia R (2006) Climate and climate change over North America as simulated by the Canadian RCM. J Clim 19(13):3112–3132CrossRefGoogle Scholar
  46. Puckrin E, Evans WFJ, Li J, Lavoie H (2004) Comparison of clear-sky surface radiative fluxes simulated with radiative transfer models. Can J Remote Sens 30:903–912Google Scholar
  47. Räisänen J (2001) CO2 induced climate change in CMIP2 experiments: quantification of agreement and role of internal variability. J Clim 14:2088–2104CrossRefGoogle Scholar
  48. Riette S, Caya D (2002) Sensitivity of short simulations to the various parameters in the new CRCM spectral nudging. Res Act Atmos ocean Model 32:7.39–7.40Google Scholar
  49. Robert A, Yakimiw E (1986) Identification and elimination of an inflow boundary computational solution in limited area model integrations. Atmos Ocean 24:369–385Google Scholar
  50. Rojas M, Seth A (2003) Simulation and sensitivity in a nested system for South America. Part II: CGM boundary forcing. J Clim 16:2454–2471CrossRefGoogle Scholar
  51. Rinke A, Marbaix P, Dethloff K (2004) Internal variability in arctic regional climate simulations: case study for the SHEBA year. Clim Res 27:197–209CrossRefGoogle Scholar
  52. Seth A, Giorgi F (1998) The effects of domain choice on summer precipitation simulation and sensitivity in a regional climate model. J Clim 11:2698–2712CrossRefGoogle Scholar
  53. Sheng J, Zwiers F (1998) An improved scheme for time-dependent boundary conditions in atmospheric general circulation models. Clim Dyn 14:609–613CrossRefGoogle Scholar
  54. Takle E, Gutowski WJ, Arritt RW, Pan Z, Anderson CJ, Silva RRD, Caya D, Chen S, Giorgi F, Christensen JH, Hong S, Juang HH, Katzfey J, Lapenta WM, Laprise R, Liston GE, Lopez P, McGregor J, Pielke RA, Roads JO (1999) Project to Intercompare Regional Climate Simulations (PIRCS): description and initial results. J Geophys Res 104:19443–19461CrossRefGoogle Scholar
  55. Tjernstrom M, Zagar M, Svensson G, Cassano J, Pfeifer S, Rinke A, Wyser K, Dethloff K, Jones C, Semmler T, Shaw M (2005): Modelling the Arctic boundary layer: an evaluation of six arcmip regional-scale models using data from the Sheba project. Boundary-Layer Meteor 117:337–381CrossRefGoogle Scholar
  56. Uppala SM, coauthors (2005) The ERA-40 re-analysis. Q J Roy Meteor Soc 131:2961–3012CrossRefGoogle Scholar
  57. Vannitsem S, Chomé F (2005) One-way nested regional climate simulations and domain size. J Clim 18:229–233CrossRefGoogle Scholar
  58. von Storch H, Zwiers FW (2001) Statistical Analysis in Climate Research. 484 ppGoogle Scholar
  59. Verhoff A, Allen SJ, Lloyd CR (1999): Seasonal variation of surface energy balance over two Sahellian surfaces. Int J Clim 19:1267–1277CrossRefGoogle Scholar
  60. von Storch H, Langenberg H, Feser F (2000) A spectral nudging technique for dynamical downscaling purposes. Mon Weather Rev 128:3664–3673CrossRefGoogle Scholar
  61. Webster M (2003) Communicating climate change uncertainty to policy-makers and the public. Clim Change 61:1–8CrossRefGoogle Scholar
  62. Wang Y, Leung LR, McGregor JL, Lee D-K, Wang W-C, Ding Y, Kimura F (2004) Regional climate modeling: progress, challenges, and prospects. J Meteor Soc 82:1599–1628CrossRefGoogle Scholar
  63. Warner TT, Peterson RA, Treadon RE (1997) A tutorial on lateral boundary conditions as a basic and potentially serious limitation to regional numerical weather prediction. Bull Am Meteor Soc 78:2599–2617CrossRefGoogle Scholar
  64. Weisse R, Heyen H, von Storch H (2000) Sensitivity of a regional atmospheric model to a sea state dependent roughness and the need of ensemble calculations. Mon Weather Rev 128:3631–3642CrossRefGoogle Scholar
  65. Wu W, Lynch AH, Rivers A (2005) Estimating the uncertainty in a regional climate model related to initial and boundary conditions. J Clim 18:917–933CrossRefGoogle Scholar
  66. Yang Z, Arritt RW (2002) Tests of a perturbed physics ensemble approach for regional climate modeling. J Clim 15:2881–2896CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Ramón de Elía
    • 1
    Email author
  • Daniel Caya
    • 1
  • Hélène Côté
    • 1
  • Anne Frigon
    • 1
  • Sébastien Biner
    • 1
  • Michel Giguère
    • 1
  • Dominique Paquin
    • 1
  • Richard Harvey
    • 2
  • David Plummer
    • 2
  1. 1.Climate Simulations TeamConsortium OuranosMontrealCanada
  2. 2.Canadian Centre for Climate Modelling and AnalysisMeteorological Service of CanadaVictoriaCanada

Personalised recommendations