Climate Change pp 181-199 | Cite as

Considerations of Domain Size and Large-Scale Driving for Nested Regional Climate Models: Impact on Internal Variability and Ability at Developing Small-Scale Details

  • René Laprise
  • Dragana Kornic
  • Maja Rapaić
  • Leo Šeparović
  • Martin Leduc
  • Oumarou Nikiema
  • Alejandro Di Luca
  • Emilia Diaconescu
  • Adelina Alexandru
  • Philippe Lucas-Picher
  • Ramón de Elía
  • Daniel Caya
  • Sébastien Biner
Conference paper

Abstract

The premise of dynamical downscaling is that a high-resolution, nested Regional Climate Model (RCM), driven by large-scale atmospheric fields at its lateral boundary, generates fine scales that are dynamically consistent with the large scales. An RCM is hence expected to act as a kind of magnifying glass that will reveal details that could not be resolved on a coarse mesh. The small scales represent the main potential added value of a high-resolution RCM.

Several issues remain with respect to nested RCMs: are the large scales perfectly replicated, degraded or improved by an RCM? For a given set of lateral boundary conditions, is the course of an RCM simulation uniquely defined? Is lateral-boundary driving sufficient to control RCM simulations? What domain size and location should be used for a given application? Almost 20 years after the inception of RCMs, and despite recognition that RCMs’ results are sensitive to the choice of domain and driving technique, these questions have still not been fully answered.

A series of methodical investigations spread over the course of several years have been performed to address these issues in an unambiguous manner, following a strict experimental protocol: the Big-Brother Experiment. The results to date point to the advantage of using rather large domains that permit the full spin-up of small scales, acknowledging however that such configuration permits the intermittent occurrence of divergence in phase space and large internal variability in RCM simulations. Alternative driving techniques to the traditional imposition of lateral boundary conditions, which allow forcing the large scales throughout the domain, appear to offer definite advantages.

References

  1. Alexandru A, de Elía R, Laprise R (2007) Internal variability in regional climate downscaling at the seasonal time scale. Mon Weather Rev 135(9):3221–3238CrossRefGoogle Scholar
  2. Alexandru A, de Elía R, Laprise R, Šeparović L, Biner S (2009) Influence of large-scale nudging on ensemble simulations with a regional climate model. Mon Weather Rev 137(5):1668–1688CrossRefGoogle Scholar
  3. Annamalai H, Slingo JM, Sperber KR, Hodges K (1999) The mean evolution and variability of the Asian summer monsoon: comparison of ECMWF and NCEP-NCAR reanalyses. Mon Weather Rev 127(6):1157–1186CrossRefGoogle Scholar
  4. Anthes RA, Kuo Y-H, Benjamin SG, Li Y-F (1982) The evolution of the mesoscale environment of severe local storms: preliminary modeling results. Mon Weather Rev 110:1187–1213CrossRefGoogle Scholar
  5. Anthes RA, Kuo Y-H, Hsie E-Y, Low-Nam S, Bettge TW (1989) Estimation of skill and uncertainty in regional numerical models. Quart J R Meteorol Soc 115:763–806CrossRefGoogle Scholar
  6. Antic S, Laprise R, Denis B, de Elía R (2005) Testing the downscaling ability of a one-way nested regional climate model in regions of complex topography. Clim Dyn 23:473–493CrossRefGoogle Scholar
  7. Bärring L, Laprise R (eds) (2005) High-resolution climate modelling: assessment, added value and applications. Extended abstracts of a WMO/WCRP-sponsored regional-scale climate modelling Workshop, 29 Mar–2 Apr 2004, Lund, Sweden. Lund University electronic reports in physical geography, 132pp. (http://www.nateko.lu.se/ELibrary/Lerpg/5/Lerpg5Article.pdf)
  8. Biner S, Caya D, Laprise R, Spacek L (2000) Nesting of RCMs by imposing large scales. In: Research activities in atmospheric and oceanic modelling, WMO/TD – No. 987, Report No. 30, 7.3-7.4Google Scholar
  9. Bresson R, Laprise R (2009) Scale-decomposed atmospheric water budget over North America as simulated by the Canadian regional climate model for current and future climates. Clim Dyn 1–20. doi:10.1007/s00382-009-0695-4
  10. Castro CL, Pielke RA Sr, Leoncini G (2005) Dynamical downscaling: an assessment of value added using a regional climate model. J Geophys Res (Atmospheres) 110:05108. doi:10.1029/2004JD004721 CrossRefGoogle Scholar
  11. Caya D, Biner S (2004) Internal variability of RCM simulations over an annual cycle. Clim Dyn 22(1):33–46CrossRefGoogle Scholar
  12. Caya D, Laprise R (1999) A semi-Lagrangian semi-implicit regional climate model: the Canadian RCM. Mon Weather Rev 127(3):341–362CrossRefGoogle Scholar
  13. Christensen OB, Gaertner MA, Prego JA, Polcher J (2001) Internal variability of regional climate models. Clim Dyn 17:875–887CrossRefGoogle Scholar
  14. Cocke S, LaRow TE (2000) Seasonal predictions using a regional spectral model embedded within a coupled ocean-atmosphere model. Mon Weather Rev 128:689–708CrossRefGoogle Scholar
  15. Davies HC (1976) A lateral boundary formulation for multi-level prediction models. Quart J R Meteorol Soc 102:405–418Google Scholar
  16. de Elía R, Laprise R (2003) Distribution-oriented verification of limited-area models forecast in a perfect-model framework. Mon Weather Rev 131:2492–2509CrossRefGoogle Scholar
  17. de Elía R, Laprise R, Denis B (2002) Forecasting skill limits of nested, limited-area models: a perfect-model approach. Mon Weather Rev 130:2006–2023CrossRefGoogle Scholar
  18. de Elía R, Plummer D, Caya D, Frigon A, Côté H, Giguère M, Paquin D, Biner S, Harvey R (2007) Evaluation of uncertainties in the CRCM-simulated North American climate. Clim Dyn. doi:10.1007/s00382-007-0288-z
  19. Denis B, Côté J, Laprise R (2002a) Spectral decomposition of two-dimensional atmospheric fields on limited-area domains using discrete cosine transforms (DFT). Mon Weather Rev 130(7):1812–1829CrossRefGoogle Scholar
  20. Denis B, Laprise R, Caya D, Côté J (2002b) Downscaling ability of one-way-nested regional climate models: the Big-Brother experiment. Clim Dyn 18:627–646CrossRefGoogle Scholar
  21. Denis B, Laprise R, Caya D (2003) Sensitivity of a regional climate model to the spatial resolution and temporal updating frequency of the lateral boundary conditions. Clim Dyn 20:107–126Google Scholar
  22. Déqué M, Rowell DP, Lüthi D, Giorgi F, Christensen JH, Rockel B, Jacob D, Kjellström E, de Castro M, van den Hurk B (2006) An intercomparison of regional climate simulations for Europe: assessing uncertainties in model projections. Clim Chang 81(1):53–70. doi:10.1007/s10584-006-9228-x CrossRefGoogle Scholar
  23. Di Luca A, de Elía R, Laprise R (2011) Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations. Clim Dyn doi: 10.1007/s00382-011-1068-3
  24. Diaconescu EP, Laprise R, Sushama L (2007) The impact of lateral boundary data errors on the simulated climate of a nested regional climate model. Clim Dyn 28(4):333–350CrossRefGoogle Scholar
  25. Díez E, Primo C, García-Moya JA, Gutiérrez JM, Orfila B (2005) Statistical and dynamical downscaling of precipitation over Spain from DEMETER seasonal forecasts. Tellus 57A:409–423Google Scholar
  26. Dimitrijevic M, Laprise R (2005) Validation of the nesting technique in an RCM and sensitivity tests to the resolution of the lateral boundary conditions during summer. Clim Dyn 25:555–580CrossRefGoogle Scholar
  27. Errico RM (1985) Spectra computed from a limited area grid. Mon Weather Rev 113:1554–1562CrossRefGoogle Scholar
  28. Fennessy MJ, Shukla J (2000) Seasonal prediction over North America with a regional model nested in a global model. J Clim 13:2605–2627CrossRefGoogle Scholar
  29. Feser F (2006) Enhanced detectability of added value in limited area model results separated into different spatial scales. Mon Weather Rev 134(8):2180–2190CrossRefGoogle Scholar
  30. Feser F, von Storch H (2006) A spatial two-dimensional discrete filter for limited area model evaluation purposes. Mon Weather Rev 133(6):1774–1786CrossRefGoogle Scholar
  31. Feser F, von Storch H (2008) A dynamical downscaling case study for typhoons in SE Asia using a regional climate model. Mon Weather Rev 136:1806–1815CrossRefGoogle Scholar
  32. Feser F, von Storch H, Winterfeldt J, Zahn M (2009) Added value of limited area model results, 2pp. In: 2nd international Lund RCM conference “21st Century Challenges in Regional-scale Climate Modelling”, 4–8 May 2009, Lund, Sweden, pp 43–44. (http://www.baltex-research.eu/RCM2009/Material/RCM2009_Proceedings_print.pdf)
  33. Giorgi F, Bi X (2000) A study of internal variability of a regional climate model. J Geophys Res 105:29503–29521CrossRefGoogle Scholar
  34. Herceg D, Sobel AH, Sun L, Zebiak SE (2006) The big brother experiment and seasonal predictability in the NCEP regional spectral model. Clim Dyn 26(4):1–14. doi:10.1007/s00382-006-0130-z. http://dx.doi.org/10.1007/s00382-006-0130-z)Google Scholar
  35. Ji YM, Vernekar AD (1997) Simulation of the Asian summer monsoons of 1987 and 1988 with a regional model nested in a global GCM. J Clim 10:1965–1979CrossRefGoogle Scholar
  36. 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. Quart J R Meteorol Soc 121:1413–1449Google Scholar
  37. Jones RG, Murphy JM, Noguer M, Keen AB (1997) Simulation of climate change over Europe using a nested regional climate model. II: comparison of driving and regional model responses to a doubling of carbon dioxide. Quart J R Meteorol Soc 123:265–292Google Scholar
  38. Juang H-MH, Hong S-Y (2001) Sensitivity of the NCEP regional spectral model to domain size and nesting strategy. Mon Weather Rev 129:2904–2922CrossRefGoogle Scholar
  39. Kanamaru H, Kanamitsu M (2007) Scale-selective bias correction in a downscaling of global analysis using a regional model. Mon Weather Rev 135:334–350CrossRefGoogle Scholar
  40. Kornic D (2010) Sensibilité des simulations du modèle régional du climat à la taille du domaine et Á la technique de pilotage. M.Sc. Dissertation in Atmospheric Sciences. Department of Earth and Atmospheric Sciences, UQAMGoogle Scholar
  41. Kuo H-C, Williams RT (1992) Boundary effects in regional spectral models. Mon Weather Rev 120:2986–2992CrossRefGoogle Scholar
  42. Kuo H-C, Williams RT (1998) Scale-dependent accuracy in regional spectral models. Mon Weather Rev 126:2640–2647CrossRefGoogle Scholar
  43. Laprise R (2007) Regional climate modelling. J Comput Phys 227:3641–3666, Special issue on “Predicting weather, climate and extreme events”CrossRefGoogle Scholar
  44. 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 XXXVI(2):119–167CrossRefGoogle Scholar
  45. Laprise R, Jones R, Kirtman B, von Storch H, Wergen W (2002) Atmospheric regional climate models (RCMs): a multiple purpose tool? In: Report of the “Joint WGNE/WGCM ad hoc Panel on Regional Climate Modelling”, 19pp. (available from the corresponding author)Google Scholar
  46. 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
  47. Laprise R, de Elía R, Caya D, Biner S, Lucas-Picher Ph, Diaconescu EP, Leduc M, Alexandru A, Šeparović L (2008) Challenging some tenets of regional climate modelling. Meteorol Atmos Phys 100:3–22. doi:10.1007/s00703-008-0292-9, Special Issue on Regional Climate StudiesCrossRefGoogle Scholar
  48. Leduc M, Laprise R (2009) Regional climate model sensitivity to domain size. Clim Dyn 32(6):833–854. doi:10.1007/s00382-008-0400-z CrossRefGoogle Scholar
  49. Leduc M, Laprise R, Moretti-Poisson M, Morin J-Ph (2011) Sensitivity to domain size of Regional Climate Model simulations in middle latitudes for summer. Clim Dyn 37(1-2), 343–356, doi:10.1007/s00382-011-1008-2
  50. Lucas-Picher Ph, Caya D, de Elía R, Laprise R (2008a) Investigation of regional climate models’ internal variability with a ten-member ensemble of ten-year simulations over a large domain. Clim Dyn 31:927–940. doi:10.1007/s00382-008-0384-8 CrossRefGoogle Scholar
  51. Lucas-Picher Ph, Caya D, Biner S, Laprise R (2008b) Quantification of the lateral boundary forcing in a regional climate model using an ageing tracer. Mon Weather Rev 136:4980–4996. doi:10.1175/2008MWR2448.1 CrossRefGoogle Scholar
  52. McGregor JL (1997) Regional climate modelling. Meteorol Atmos Phys 63:105–117CrossRefGoogle Scholar
  53. Mesinger F, Brill K, Chuang H, DiMego G, Rogers E (2002) Limited area predictability: can upscaling also take place? In: Research activities in atmospheric and oceanic modelling, Report No. 32, WMO/TD – No. 1105, 5.30-5.31Google Scholar
  54. Miguez-Macho G, Stenchikov GL, Robock A (2004) Spectral nudging to eliminate the effects of domain position and geometry in regional climate model simulations. J Geophys Res 109(D13):D13104. doi:10.1029/2003JD004495 CrossRefGoogle Scholar
  55. Miyakoda K, Rosati A (1977) One-way nested grid models: the interface conditions and the numerical accuracy. Mon Weather Rev 105:1092–1107CrossRefGoogle Scholar
  56. Nikièma O, Laprise R (2011) Diagnostic budget study of the internal variability in ensemble simulations of the Canadian Regional Climate Model. Clim Dyn 36(11), 2313–2337, doi:10.1007/s00382-010-0834-y
  57. Nutter P, Stensrud D, Xue M (2004) Effects of coarsely resolved and temporally interpolated lateral boundary conditions on the dispersion of limited-area ensemble forecasts. Mon Weather Rev 132(10):2358–2377CrossRefGoogle Scholar
  58. Oliger J, Sundström A (1978) Theoretical and practical aspects of some initial boundary value problems in fluid dynamics. SIAM J Appl Math 35:419–446CrossRefGoogle Scholar
  59. Plummer DA, Caya D, Frigon A, Côté H, Giguère M, Paquin D, Biner S (2006) Climate and climate change over north America as simulated by the Canadian RCM. J Clim 19:3112–3132CrossRefGoogle Scholar
  60. Rapaić M, Leduc M, Laprise R (2011) Evaluation of internal variability and estimation of the downscaling ability of the Canadian RCM for different domain sizes over the North Atlantic region using the Big-Brother Experimental approach. Clim Dyn 36(9-10), 1979–2001, doi:10.1007/s00382-010-0845-8
  61. Riette S, Caya D (2002) Sensitivity of short simulations to the various parameters in the new CRCM spectral nudging. In: Ritchie (eds) Research activities in atmospheric and oceanic modelling. WMO/TD – No 1105, Report No. 32, 7.39-7.40Google Scholar
  62. Rinke A, Dethloff K (2000) On the sensitivity of a regional Arctic climate model to initial and boundary conditions. Clim Res 14(2):101–113CrossRefGoogle Scholar
  63. 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
  64. Robert A, Yakimiw E (1986) Identification and elimination of an inflow boundary computational solution in limited area model integration. Atmos Ocean 24:369–385CrossRefGoogle Scholar
  65. Rockel B, Castro CL, Pielke RA Sr, von Storch H, Leoncini G (2008) Dynamical downscaling: assessment of model system dependent retained and added variability for two different regional climate models. J Geophys Res Atmospheres 113:D21107. doi:10.1029/2007JD009461 CrossRefGoogle Scholar
  66. Segami A, Kurihara K, Nakamura H, Ueno M, Takano I, Tatsumi Y (1989) Operational mesoscale weather prediction with Japan spectral model. J Meteorol Soc Jpn 67:907–923Google Scholar
  67. Šeparović L, de Elía R, Laprise R (2008) Reproducible and irreproducible components in ensemble simulations of a regional climate model. Clim Dyn 136(12):4942–4961. doi:10.1175/2008MWR2393.1 Google Scholar
  68. Staniforth A (1997) Regional modeling: a theoretical discussion. Meteorol Atmos Phys 63:15–29CrossRefGoogle Scholar
  69. Tatsumi Y (1986) A spectral limited-area model with time dependent lateral boundary conditions and its application to a multi-level primitive equation model. J Meteor Soc Jpn 64:637–663Google Scholar
  70. Thatcher M, McGregor JL (2009) Using a scale-selective filter for dynamical downscaling with the conformal cubic atmospheric model. Mon Weather Rev 137:1742–1752CrossRefGoogle Scholar
  71. Vanvyve E, Hall N, Messager C, Leroux S, van Ypersele J-P (2007) Internal variability in a regional model over West Africa. Clim Dyn 30(2–3):191–202. doi:10.1007/s00382-007-0281-6 Google Scholar
  72. von Storch H (2005) Conceptual basis and applications of regional climate modeling, pp 26–27. In: Bärring L, Laprise R (eds) Extended abstracts “High-resolution climate modelling: Assessment, added value and applications”. WMO/WCRP-sponsored regional-scale climate modelling Workshop, 29 Mar–2 Apr 2004, Lund, Sweden. Lund University electronic reports in physical geography, 132pp. (http://www.nateko.lu.se/ELibrary/Lerpg/5/Lerpg5Article.pdf)
  73. von Storch H, Zorita E, Cubasch U (1993) Downscaling of global climate change estimates to regional scales: an application to Iberian rainfall in wintertime. J Clim 6:1161–1171CrossRefGoogle Scholar
  74. von Storch H, Langenberg H, Feser F (2000) A spectral nudging technique for dynamical downscaling purposes. Mon Weather Rev 128:3664–3673CrossRefGoogle Scholar
  75. Wang Y, Leung LR, McGregor JL, Lee D-K, Wang W-C, Ding Y, Kimura F (2004) Regional climate modelling: progress, challenges, and prospects. J Meteorol Soc Jpn 82(6):1599–1628CrossRefGoogle Scholar
  76. Warner TT, Peterson RA, Treadon RE (1997) A tutorial on lateral conditions as a basic and potentially serious limitation to regional numerical weather prediction. Bull Am Meteorol Soc 78(11):2599–2617CrossRefGoogle Scholar
  77. Weisse R, Feser F (2003) Evaluation of a method to reduce uncertainty in wind hindcasts performed with regional atmosphere models. Coast Eng 48(4):211–225CrossRefGoogle Scholar
  78. Weisse R, Heyen H, von Storch H (2000) Sensitivity of a regional atmospheric model to a sea state-dependent roughness and the need for ensemble calculations. Mon Weather Rev 128(10):3631–3642CrossRefGoogle Scholar
  79. Weisse R, von Storch H, Callies U, Chrastansky A, Feser F, Grabemann I, Guenther H, Pluess A, Stoye T, Tellkamp J, Winterfeldt J, Woth K (2009) Regional meteorological-marine reanalyses and climate change projections: results for Northern Europe and potentials for coastal and offshore applications. Bull Am Meteorol Soc 90:849–860CrossRefGoogle Scholar
  80. Wu W, Lynch AH, Rivers A (2005) Estimating the uncertainty in a regional climate model related to initial and lateral boundary conditions. J Clim 18(7):917–933CrossRefGoogle Scholar
  81. Wyser K, Jones CG, Du P, Girard E, Willén U, Cassano J, Christensen JH, Curry JA, Dethloff K, Haugen J-E, Jacob D, Køltzow M, Laprise R, Lynch A, Pfeifer S, Rinke A, Serreze M, Shaw MJ, Tjernström M, Zagar M (2008) An evaluation of Arctic cloud and radiation processes during the SHEBA year: simulation results from 8 Arctic regional climate models. Clim Dyn 30(2–3):203–223. doi:10.1007/s00382-007-0286-1 CrossRefGoogle Scholar
  82. Yakimiw E, Robert A (1990) Validation experiments for a nested grid-point regional forecast model. Atmos Ocean 28:466–472CrossRefGoogle Scholar
  83. Zahn M, von Storch H, Bakan S (2008) Climate mode simulation of North Atlantic Polar Lows in a limited area model. Tellus A 60:620–631. doi:10.1111/j.1600-0870.2008.00330.x CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Wien 2012

Authors and Affiliations

  • René Laprise
    • 1
    • 2
    • 3
  • Dragana Kornic
    • 2
    • 3
    • 4
  • Maja Rapaić
    • 2
    • 3
    • 4
  • Leo Šeparović
    • 2
    • 3
    • 4
  • Martin Leduc
    • 2
    • 3
    • 4
  • Oumarou Nikiema
    • 2
    • 3
    • 4
  • Alejandro Di Luca
    • 2
    • 3
    • 4
  • Emilia Diaconescu
    • 2
    • 3
    • 4
  • Adelina Alexandru
    • 2
    • 3
    • 4
  • Philippe Lucas-Picher
    • 5
  • Ramón de Elía
    • 2
    • 4
    • 6
  • Daniel Caya
    • 2
    • 6
    • 7
    • 8
    • 9
  • Sébastien Biner
    • 6
  1. 1.Centre pour l’Étude et la Simulation du Climat à l’Échelle Régionale (ESCER)UQAMMontréalCanada
  2. 2.Canadian Network for Regional Climate Modelling and Diagnostics (CRCMD)MontréalCanada
  3. 3.Université du Québec à Montréal (UQAM)MontréalCanada
  4. 4.Centre pour l’Étude et la Simulation du Climat à l’Échelle Régionale (ESCER)UQAMMontréalCanada
  5. 5.Danish Meteorological Institute (DMI)CopenhagenDenmark
  6. 6.Consortium OuranosMontréalCanada
  7. 7.Ouranos, Consortium sur la climatologie régionale et l’adaptation aux changements climatiquesMontréalCanada
  8. 8.Centre pour l’Étude et la Simulation du Climat à l’Échelle Régionale (ESCER)Université du Québec à MontréalMontréalCanada
  9. 9.UQAMMontréalCanada

Personalised recommendations