Table of Contents Author Guidelines Submit a Manuscript
Advances in Meteorology
Volume 2016, Article ID 1478514, 17 pages
http://dx.doi.org/10.1155/2016/1478514
Research Article

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

1APEC Climate Center (APCC), 12 Centum 7-ro, Haeundae-gu, Busan 612-020, Republic of Korea
2Étude et Simulation du Climat à l’Échelle Régionale (ESCER), University of Québec at Montreal, 201 Président Kennedy Avenue, Montréal, QC, Canada H2X 3Y7

Received 19 August 2015; Revised 27 October 2015; Accepted 17 November 2015

Academic Editor: Xiaofeng Li

Copyright © 2016 Hyung-Il Eum et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. F. Hamlet and D. P. Lettenmaier, “Effects of 20th century warming and climate variability on flood risk in the western US,” Water Resources Research, vol. 43, no. 6, Article ID W06427, 2007. View at Publisher · View at Google Scholar · View at Scopus
  2. H.-I. Eum, P. Gachon, and R. Laprise, “Developing a likely climate scenario from multiple regional climate model simulations with an optimal weighting factor,” Climate Dynamics, vol. 43, no. 1-2, pp. 11–35, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. L. A. Vincent, X. L. Wang, E. J. Milewska, H. Wan, F. Yang, and V. Swail, “A second generation of homogenized Canadian monthly surface air temperature for climate trend analysis,” Journal of Geophysical Research: Atmospheres, vol. 117, no. 17, Article ID D18110, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. CCSP, Weather and Climate Extremes in a Changing Climate, NOAA’s National Climate Data Center, Washington, DC, USA, 2008.
  5. B. R. Bonsal, R. Aider, P. Gachon, and S. Lapp, “An assessment of Canadian prairie drought: past, present, and future,” Climate Dynamics, vol. 41, no. 2, pp. 501–516, 2013. View at Publisher · View at Google Scholar · View at Scopus
  6. IPCC, Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, 2012, edited by: C. B. Field, V. Barros, T. F. Stocker, D. Qin, D. J. Dokken, K. L. Ebi, M. D. Mastrandrea, K. J. Mach, G.-K. Plattner, S. K. Allen, M. Tignor, P. M.
  7. L. R. Leung and S. J. Ghan, “Pacific Northwest climate sensitivity simulated by a regional climate model driven by a GCM. Part II: 2×CO2 simulations,” Journal of Climate, vol. 12, no. 7, pp. 2031–2053, 1999. View at Publisher · View at Google Scholar · View at Scopus
  8. P. van der and J. F. B. Linden, ENSEMBLES: Climate Change and its Impacts: Summary of Research and Results from the ENSEMBLES Project, Met Office Hadley Centre, Exeter, UK, 2009.
  9. D. Jacob, A. Elizalde, A. Haensler et al., “Assessing the transferability of the regional climate model REMO to different coordinated regional climate downscalilng experiment (CORDEX) regions,” Atmosphere, vol. 3, no. 1, pp. 181–199, 2012. View at Publisher · View at Google Scholar · View at Scopus
  10. P. B. Duffy, R. W. Arritt, J. Coquard et al., “Simulations of present and future climates in the western United States with four nested regional climate models,” Journal of Climate, vol. 19, no. 6, pp. 873–895, 2006. View at Publisher · View at Google Scholar · View at Scopus
  11. P. Gachon and Y. Dibike, “Temperature change signals in northern Canada: convergence of statistical downscaling results using two driving GCMs,” International Journal of Climatology, vol. 27, no. 12, pp. 1623–1641, 2007. View at Publisher · View at Google Scholar · View at Scopus
  12. J. H. Christensen, T. R. Carter, M. Rummukainen, and G. Amanatidis, “Evaluating the performance and utility of regional climate models: the PRUDENCE project,” Climatic Change, vol. 81, supplement 1, pp. 1–6, 2007. View at Publisher · View at Google Scholar · View at Scopus
  13. D. Jacob, J. Petersen, B. Eggert et al., “EURO-CORDEX: new high-resolution climate change projections for European impact research,” Regional Environmental Change, vol. 14, no. 2, pp. 563–578, 2014. View at Publisher · View at Google Scholar · View at Scopus
  14. H. Visser, R. J. M. Folkert, J. Hoekstra, and J. J. de Wolff, “Identifying key sources of uncertainty in climate change projections,” Climatic Change, vol. 45, no. 3-4, pp. 421–457, 2000. View at Publisher · View at Google Scholar · View at Scopus
  15. H. J. Fowler and M. Ekström, “Multi-model ensemble estimates of climate change impacts on UK seasonal precipitation extremes,” International Journal of Climatology, vol. 29, no. 3, pp. 385–416, 2009. View at Publisher · View at Google Scholar · View at Scopus
  16. F. Giorgi and E. Coppola, “Does the model regional bias affect the projected regional climate change? An analysis of global model projections: a letter,” Climatic Change, vol. 100, no. 3, pp. 787–795, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. J. H. Christensen, T. R. Carter, and F. Giorgi, “PRUDENCE employs new methods to assess european climate change,” Eos, vol. 83, no. 13, p. 147, 2002. View at Publisher · View at Google Scholar · View at Scopus
  18. L. O. Mearns, W. J. Gutowski, R. Jones et al., “A regional climate change assessment program for North America,” EOS Transactions, vol. 90, no. 36, pp. 311–312, 2012. View at Google Scholar
  19. J. H. Christensen, E. Kjellström, F. Giorgi, G. Lenderink, and M. Rummukainen, “Weight assignment in regional climate models,” Climate Research, vol. 44, no. 2-3, pp. 179–194, 2010. View at Publisher · View at Google Scholar · View at Scopus
  20. E. Coppola, F. Giorgi, S. A. Rauscher, and C. Piani, “Model weighting based on mesoscale structures in precipitation and temperature in an ensemble of regional climate models,” Climate Research, vol. 44, no. 2-3, pp. 121–134, 2010. View at Publisher · View at Google Scholar · View at Scopus
  21. J. Räisänen and J. S. Ylhäisi, “Can model weighting improve probabilistic projections of climate change?” Climate Dynamics, vol. 39, no. 7-8, pp. 1981–1998, 2012. View at Publisher · View at Google Scholar · View at Scopus
  22. H.-I. Eum, P. Gachon, R. Laprise, and T. Ouarda, “Evaluation of regional climate model simulations versus gridded observed and regional reanalysis products using a combined weighting scheme,” Climate Dynamics, vol. 38, no. 7-8, pp. 1433–1457, 2012. View at Publisher · View at Google Scholar · View at Scopus
  23. D. Caya and R. Laprise, “A semi-implicit semi-Lagrangian regional climate model: the Canadian RCM,” Monthly Weather Review, vol. 127, no. 2-3, pp. 341–362, 1999. View at Publisher · View at Google Scholar · View at Scopus
  24. R. Laprise, D. Caya, A. Frigon, and D. Paquin, “Current and perturbed climate as simulated by the second-generation Canadian Regional Climate Model (CRCM-II) over northwestern North America,” Climate Dynamics, vol. 21, no. 5-6, pp. 405–421, 2003. View at Publisher · View at Google Scholar · View at Scopus
  25. N. Nakicenovic, J. Alcamo, G. Davis et al., IPCC Special Report on Emissions Scenarios, Cambridge University Press, Cambridge, UK, 2000.
  26. M. Déqué and J. P. Piedeliévre, “High resolution climate simulation over Europe,” Climate Dynamics, vol. 11, no. 6, pp. 321–339, 1995. View at Publisher · View at Google Scholar · View at Scopus
  27. W. D. Collins, C. M. Bitz, M. L. Blackmon et al., “The Community Climate System Model version 3 (CCSM3),” Journal of Climate, vol. 19, no. 11, pp. 2122–2143, 2006. View at Publisher · View at Google Scholar · View at Scopus
  28. G. M. Flato and G. J. Boer, “Warming asymmetry in climate change simulations,” Geophysical Research Letters, vol. 28, no. 1, pp. 195–198, 2001. View at Publisher · View at Google Scholar · View at Scopus
  29. T. L. Delworth, A. J. Broccoli, A. Rosati et al., “GFDL’s CM2 global coupled climate models. Part I: formulation and simulation characteristics,” Journal of Climate, vol. 19, pp. 643–674, 2006. View at Publisher · View at Google Scholar
  30. C. Gordon, C. Cooper, C. A. Senior et al., “The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments,” Climate Dynamics, vol. 16, no. 2-3, pp. 147–168, 2000. View at Publisher · View at Google Scholar · View at Scopus
  31. A.-L. Gibelin and M. Déqué, “Anthropogenic climate change over the Mediterranean region simulated by a global variable resolution model,” Climate Dynamics, vol. 20, no. 4, pp. 327–339, 2003. View at Google Scholar · View at Scopus
  32. E. Kalnay, M. Kanamitsu, R. Kistler et al., “The NCEP/NCAR 40-year reanalysis project,” Bulletin of the American Meteorological Society, vol. 77, no. 3, pp. 437–471, 1996. View at Publisher · View at Google Scholar · View at Scopus
  33. S. M. Uppala, P. W. Kållberg, A. J. Simmons et al., “The ERA-40 re-analysis,” Quarterly Journal of the Royal Meteorological Society, vol. 131, no. 612, pp. 2961–3012, 2005. View at Publisher · View at Google Scholar · View at Scopus
  34. K. V. Price, R. M. Storn, and J. A. Lampinen, Differential Evolution: A Practical Approach to Global Optimization, Springer, Berlin, Germany, 2005. View at MathSciNet
  35. M. F. Hutchinson, D. W. McKenney, K. Lawrence et al., “Development and testing of Canada-wide interpolated spatial models of daily minimum–maximum temperature and precipitation for 1961–2003,” Journal of Applied Meteorology and Climatology, vol. 48, no. 4, pp. 725–741, 2009. View at Publisher · View at Google Scholar · View at Scopus
  36. M. Cholette, R. Laprise, and J. M. Thériault, “Perspectives for very high-resolution climate simulations with nested models: illustration of potential in simulating St. Lawrence River Valley channelling winds with the fifth-generation Canadian regional climate model,” Climate, vol. 3, no. 2, pp. 283–307, 2015. View at Publisher · View at Google Scholar
  37. C. Wang, R. Jones, M. Perry, C. Johnson, and P. Clark, “Using ultrahigh-resolution regional climate model to predict local climatology,” Quarterly Journal of the Royal Meteorological Society, vol. 139, no. 677, pp. 1964–1976, 2013. View at Publisher · View at Google Scholar · View at Scopus
  38. P. Roy, P. Gachon, and R. Laprise, “Sensitivity of seasonal precipitation extremes to model configuration of the Canadian regional climate model over eastern Canada using historical simulations,” Climate Dynamics, vol. 43, no. 9, pp. 2431–2453, 2014. View at Publisher · View at Google Scholar · View at Scopus
  39. J. H. Christensen, K. Krishna Kumar, E. Aldrian et al., “Climate phenomena and their relevance for future regional climate change,” in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T. F. Stocker, D. Qin, G.-K. Plattner et al., Eds., Cambridge University Press, Cambridge, UK, 2013. View at Google Scholar
  40. Q. Wang, X. Fan, and M. Wang, “Recent warming amplification over high elevation regions across the globe,” Climate Dynamics, vol. 43, no. 1-2, pp. 87–101, 2014. View at Publisher · View at Google Scholar · View at Scopus
  41. C. Jacob, L. Bärring, O. B. Christensen et al., “An inter-comparison of regional climate models for Europe: model performance in present-day climate,” Climatic Change, vol. 81, supplement 1, pp. 31–52, 2007. View at Publisher · View at Google Scholar
  42. F. Giorgi, C. Jones, and G. R. Asrar, “Addressing climate information needs at the regional level: the CORDEX framework,” WMO Bulletin, vol. 58, no. 3, pp. 175–183, 2009. View at Google Scholar