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Climate Dynamics

, Volume 41, Issue 5–6, pp 1117–1137 | Cite as

Evaluation of the regional climate model ALADIN to simulate the climate over North America in the CORDEX framework

  • Philippe Lucas-Picher
  • Samuel Somot
  • Michel Déqué
  • Bertrand Decharme
  • Antoinette Alias
Article

Abstract

In this study, an ensemble of four multi-year climate simulations is performed with the regional climate model ALADIN to evaluate its ability to simulate the climate over North America in the CORDEX framework. The simulations differ in their driving fields (ERA-40 or ERA-Interim) and the nudging technique (with or without large-scale nudging). The validation of the simulated 2-m temperature and precipitation with observationally-based gridded data sets shows that ALADIN performs similarly to other regional climate models that are commonly used over North America. Large-scale nudging improves the temporal correlation of the atmospheric circulation between ALADIN and its driving field, and also reduces the warm and dry summer biases in central North America. The differences between the simulations driven with different reanalyses are small and are likely related to the regional climate model’s induced internal variability. In general, the impact of different driving fields on ALADIN is smaller than that of large-scale nudging. The analysis of the multi-year simulations over the prairie and the east taiga indicates that the ALADIN 2-m temperature and precipitation interannual variability is similar or larger than that observed. Finally, a comparison of the simulations with observations for the summer 1993 shows that ALADIN underestimates the flood in central North America mainly due to its systematic dry bias in this region. Overall, the results indicate that ALADIN can produce a valuable contribution to CORDEX over North America.

Keywords

Regional climate model CORDEX framework North America Multi-year climate simulations Large-scale nudging Flood 

Notes

Acknowledgments

This study was supported by a grant from Fonds de recherche du Québec—Nature et technologies and a visiting scientist position at Meteo-France to the 1st author. This study is a contribution to the CORDEX project.

References

  1. Achberger C, Linderson M-L, Chen D (2003) Performance of the Rossby center regional atmospheric model in southern Sweden: comparison of simulated and observed precipitation. Theor Appl Climatol 76:219–234. doi: 10.1007/s00704-003-0015-6 CrossRefGoogle Scholar
  2. Alexandru A, de Elia R, Laprise R, Separovic L, Biner S (2009) Sensitivity study of regional climate model simulations to large-scale nudging parameters. Mon Wea Rev 137:1666–1686. doi: 10.1175/2008MWR2620.1 CrossRefGoogle Scholar
  3. Anderson CJ et al (2003) Hydrological processes in regional climate model simulations of the Central United States Flood of June–July 1993. J Hydrometeor 4:584–598. doi: 10.1175/1525-7541(2003)004<0584:HPIRCM>2.0.CO;2 CrossRefGoogle Scholar
  4. Anderson CJ, Arritt RW, Kain JS (2007) An alternative mass flux profile in the Kain–Fritsch convective parameterization and its effects in seasonal precipitation. J Hydrometeor 8:1128–1140. doi: 10.1175/JHM624.1 CrossRefGoogle Scholar
  5. Biner S, Caya D, Laprise R, Spacek L (2000) Nesting of RCM by imposing large scales. WMO/TD 987(30):7.3–7.4Google Scholar
  6. Brands S, Gutiérrez JM, Herrera S, Cofiño AS (2012) On the use of reanalysis data for downscaling. J Climate 25:2517–2526. doi: 10.1175/JCLI-D-11-00251.1 CrossRefGoogle Scholar
  7. Bromwich DH, Fogt RL, Hodges KI, Walsh JE (2007) A tropospheric assessment of the ERA-40, NCEP, and JRA-25 global reanalyses in the polar regions. J Geophys Res 112:D10111. doi: 10.1029/2006JD007859 CrossRefGoogle Scholar
  8. Bukovsky MS (2011) Masks for the Bukovsky regionalization of North America, Regional Integrated Sciences Collective, Institute for Mathematics Applied to Geosciences, National Center for Atmospheric Research, Boulder, CO. Downloaded 2012-02-23. http://www.narccap.ucar.edu/contrib/bukovsky/
  9. Bukovsky MS (2012) Temperature trends in the NARCCAP regional climate models. J Climate 25:3985–3991. doi: 10.1175/JCLI-D-11-00588.1 CrossRefGoogle Scholar
  10. Bukovsky MS, Karoly DJ (2011) A regional modeling study of climate change impacts on warm-season precipitation in the central US. J Clim 24:1985–2002. doi: 10.1175/2010JCLI3447.1 CrossRefGoogle Scholar
  11. Castro CL, Pielke RA Sr, Leoncini G (2005) Dynamical downscaling: assessment of value retained and added using the regional atmospheric modeling system (RAMS). J Geophys Res 110:D05108. doi: 10.1029/2004JD004721 CrossRefGoogle Scholar
  12. Castro CL, Pielke RA Sr, Adegoke JO (2007) Investigation of the summer climate of the contiguous United States and Mexico using the Regional Atmospheric Modeling System (RAMS). Part I: model climatology (1950–2002). J Climate 20:3844–3865. doi: 10.1175/JCLI4211.1 CrossRefGoogle Scholar
  13. Christensen JH, Machenhauer B, Jones RG, Schar C, Ruti PM, Castro M, Visconti G (1997) Validation of present-day regional climate simulations over Europe: LAM simulations with observed boundary conditions. Clim Dyn 13:489–506. doi: 10.1007/s003820050178 CrossRefGoogle Scholar
  14. Colin J, Déqué M, Radu R, Somot S (2010) Sensitivity study of heavy precipitation in limited area model climate simulations: influence of the size of the domain and the use of the spectral nudging technique. Tellus 62:591–604. doi: 10.1111/j.1600-0870.2010.00467.x Google Scholar
  15. de Elia R et al (2008) Evaluation of uncertainties in the CRCM-simulated North American climate. Clim Dyn 30:113–132. doi: 10.1007/s00382-007-0288-z CrossRefGoogle Scholar
  16. Dee DP et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart J R Meteorol Soc 137:553–597. doi: 10.1002/qj.828 CrossRefGoogle Scholar
  17. Déqué M, Somot S (2008) Analysis of heavy precipitation for France using ALADIN RCM simulations. Idojaras Quater J Hung Meteorol Ser 112:179–190Google Scholar
  18. Fouquart Y, Bonnel B (1980) Computations of solar heating of the earth’s atmosphere: a new parametrization. Beitr Phys Atmos 53:35–62Google Scholar
  19. Fu C et al (2005) Regional climate model intercomparison project for Asia. Bull Am Meteor Soc 86:257–266. doi: 10.1175/BAMS-86-2-257 CrossRefGoogle Scholar
  20. Giorgi F, Mearns L, Shields C, Mayer L (1996) A regional model study of the importance of local versus remote controls of the 1988 drought and the 1993 flood over the Central United States. J Climate 9:1150–1162CrossRefGoogle Scholar
  21. Giorgi F, Jones C, Asrar GR (2009) Addressing climate information needs at the regional level: the CORDEX framework. WMO Bull 58:175–183Google Scholar
  22. Gutowski WJ, Otieno FO, Arritt RW, Takle ES, Pan Z (2004) Diagnosis and attribution of a seasonal precipitation deficit in a US regional climate simulation. J Hydrometeor 5:230–242. doi: 10.1175/1525-7541(2004)005<0230:DAAOAS>2.0.CO;2 CrossRefGoogle Scholar
  23. Herrmann M, Somot S, Calmanti S, Dubois C, Sevault F (2011) Representation of spatial and temporal variability of daily wind speed and of intense wind events over the Mediterranean Sea using dynamical downscaling: impact of the regional climate model configuration. Nat Hazards Earth Syst Sci 11:1983–2001. doi: 10.5194/nhess-11-1983-2011 CrossRefGoogle Scholar
  24. Kanamitsu M et al (2002) NCEP/DOE AMIP-II reanalysis (R-2). Bull Am Meteor Soc 83:1631–1643. doi: 10.1175/BAMS-83-11-1631(2002)083<1631:NAR>2.3.CO;2 CrossRefGoogle Scholar
  25. Kjellström E, Boberg F, Castro M, Christensen JH, Nikulin G, Sánchez E (2010) Daily and monthly temperature and precipitation statistics as performance indicators for regional climate models. Clim Res 44:135–150. doi: 10.3354/cr00932 CrossRefGoogle Scholar
  26. Leduc M, Laprise R (2008) Regional climate model sensitivity to domain size. Clim Dyn 32:833–854. doi: 10.1007/s00382-008-0400-z CrossRefGoogle Scholar
  27. Leung LR, Qian Y, Han J, Roads JO (2003) Intercomparison of global reanalyses and regional simulations of cold season water budgets in the western United States. J Hydrometeor 4:1067–1087. doi: 10.1175/1525-7541(2003)004<1067:IOGRAR>2.0.CO;2 CrossRefGoogle Scholar
  28. Liang X-Z, Kunkel KE, Samel AN (2001) Development of a regional climate model for US Midwest applications. Part I: sensitivity to buffer zone treatment. J Climate 14:4363–4378CrossRefGoogle Scholar
  29. Liang X-Z, Li L, Kunkel KE, Ting M, Wang JXL (2004) Regional climate model simulation of US precipitation during 1982–2002. Part I: annual cycle. J Climate 17:3510–3529. doi: 10.1175/1520-0442(2004)017<3510:RCMSOU>2.0.CO;2 CrossRefGoogle Scholar
  30. Lim Y-K, Stefanova LB, Chan SC, Schubert SD, O’Brien JJ (2011) High-resolution subtropical summer precipitation derived from dynamical downscaling of the NCEP/DOE reanalysis: how much small-scale information is added by a regional model? Clim Dyn 37:1061–1080. doi: 10.1007/s00382-010-0891-2 CrossRefGoogle Scholar
  31. Lucas-Picher P, Caya D, de Elia 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
  32. Lucas-Picher P, Caya D, Biner S, Laprise R (2008b) Quantification of the lateral boundary forcing of a regional climate model using an ageing tracer. Mon Wea Rev 136:4980–4996. doi: 10.1175/2008MWR2448.1 CrossRefGoogle Scholar
  33. Lucas-Picher P, Boberg F, Christensen JH, Berg P (2012) Dynamical downscaling with reinitializations: a method to generate fine-scale climate data sets suitable for impact studies. J Hydrometeorol (Submitted to)Google Scholar
  34. Maurer EP, Wood AW, Adam JC, Lettenmaier DP, Nijssen B (2002) A long-term hydrologically-based data set of land surface fluxes and states for the conterminous United States. J Climate 15:3237–3251CrossRefGoogle Scholar
  35. Mearns LO et al (2012) The North American regional climate change assessment program: overview of phase I results. Bull Am Meteor Soc 93:1337–1362. http://dx.doi.org/10.1175/BAMSD-11-00223.1
  36. 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:D13104. doi: 10.1029/2003JD004495 CrossRefGoogle Scholar
  37. Miguez-Macho G, Stenchikov GL, Robock A (2005) Regional climate simulations over North America: interaction of local processes with improved large-scale flow. J Climate 18:1227–1246. doi: 10.1175/JCLI3369.1 CrossRefGoogle Scholar
  38. Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Climatol 25:693–712. doi: 10.1002/joc.1181 CrossRefGoogle Scholar
  39. Mlawer EJ, Taubman SJ, Brown PD, Iacono MJ, Clough SA (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J Geophys Res 102:16663–16682. doi: 10.1029/97JD00237 CrossRefGoogle Scholar
  40. Onogi K, Tsutsui J, Koide H et al (2007) The JRA-25 reanalysis. J Meteorol Soc Jpn 85:369–432. doi: 10.2151/jmsj.85.369 CrossRefGoogle Scholar
  41. Pohl B, Cretat J, Camberlin P (2011) Testing WRF capability in simulating the atmospheric water cycle over Equatorial East Africa. Clim Dyn 37:1357–1379. doi: 10.1007/s00382-011-1024-2 CrossRefGoogle Scholar
  42. Radu R, Déqué M, Somot S (2008) Spectral nudging in a spectral regional climate model. Tellus 60:885–897. doi: 10.1111/j.1600-0870.2008.00343.x CrossRefGoogle Scholar
  43. Riette S, Caya D (2002) Sensitivity of short simulations to the various parameters in the new CRCM spectral nudging. Research Activities in Atmospheric and Oceanic Modelling, WMO/TD-1105, Rep. 32, H. Ritchie, Ed., WMO, 7.39–7.40Google Scholar
  44. Rummukainen M (2010) State-of-the-art with regional climate models. Wiley Interdisciplinary Reviews, Climate Change 1:82–96. doi: 10.1002/wcc.008
  45. Sanchez-Gomez E, Somot S, Déqué M (2009a) Ability of an ensemble of regional climate models to reproduce the weather regimes during the period 1961–2000. Clim Dyn 33:723–736. doi: 10.1007/s00382-008-0502-7 CrossRefGoogle Scholar
  46. Sanchez-Gomez E, Somot S, Mariotti A (2009b) Future changes in the mediterranean water budget projected by an ensemble of regional climate models. Geophys Res Lett 36:L21401. doi: 10.1029/2009GL040120 CrossRefGoogle Scholar
  47. Sanchez-Gomez E, Somot S, Josey SA, Dubois C, Elguindi N, Déqué M (2011) Evaluation of the Mediterranean Sea water and heat budgets as simulated by an ensemble of high resolution regional climate models. Clim Dyn 37:2067–2086. doi: 10.1007/s00382-011-1012-6 CrossRefGoogle Scholar
  48. Seth A, Giorgi F (1998) The effects of domain choice on summer precipitation simulation and sensitivity in a regional climate model. J Climate 11:2698–2712. doi: 10.1175/1520-0442(1998)011<2698:TEODCO>2.0.CO;2 CrossRefGoogle Scholar
  49. Takle ES et al (1999) Project to intercompare regional climate simulations (PIRCS): description and initial results. J Geophys Res 104(D16):19443–19461. doi: 10.1029/1999JD900352 CrossRefGoogle Scholar
  50. Takle ES, Gutowski WJ, Arritt RW, Roads J, Meinke I, Rockel B, Jones CG, Zadra A (2007) Transferability intercomparison: an opportunity for new insight on the global water cycle and energy budget. Bull Am Meteor Soc 88:375–384. doi: 10.1175/BAMS-88-3-375 CrossRefGoogle Scholar
  51. Uppala SM et al (2005) The ERA-40 re-analysis. Quart J R Meteor Soc 131:2961–3012. doi: 10.1256/qj.04.176 CrossRefGoogle Scholar
  52. Voldoire A, et al. (2012) The CNRM-CM5.1 global climate model: description and basic evaluation. Clim Dyn. online first, doi: 10.1007/s00382-011-1259-y
  53. von Storch H, Langenberg H, Feser F (2000) A spectral nudging technique for dynamical downscaling purposes. Mon Weather Rev 128:3664–3673CrossRefGoogle Scholar
  54. Xue Y, Vasic R, Janjic Z, Mesinger F, Mitchell KE (2007) Assess of dynamical downscaling of the continental US regional climate using the Eta/SSiB regional climate model. J Clim 20:4172–4193. doi: 10.1175/JCLI4239.1 CrossRefGoogle Scholar
  55. Yang Z, Arritt RW (2002) Tests of a perturbed physics ensemble approach for regional climate modeling. J Climate 15:2881–2896. doi: 10.1175/1520-0442(2002)015<2881:TOAPPE>2.0.CO;2 CrossRefGoogle Scholar
  56. Yang H-W, Wang B, Wang B (2012) Reduct of systematic biases in regional climate downscaling through ensemble forcing. Clim Dyn 38:655–665. doi: 10.1007/s00382-011-1006-4 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Philippe Lucas-Picher
    • 1
    • 2
  • Samuel Somot
    • 2
  • Michel Déqué
    • 2
  • Bertrand Decharme
    • 2
  • Antoinette Alias
    • 2
  1. 1.Rossby CentreSwedish Meteorological and Hydrological Institute (SMHI)NorrköpingSweden
  2. 2.Centre National de Recherches Météorologiques (CNRM-GAME)Météo-France/CNRSToulouseFrance

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