Advertisement

Environmental and Ecological Statistics

, Volume 20, Issue 3, pp 445–465 | Cite as

Improved statistical downscaling models based on canonical correlation analysis, for generating temperature scenarios over Greece

  • Anastasios Skourkeas
  • Fotini Kolyva-Machera
  • Panagiotis Maheras
Article

Abstract

This study attempts to improve upon statistical downscaling (Sd) models based on the classical approach which uses canonical correlation analysis, in order to generate temperature scenarios over Greece. Considering the long-term trends of the predictor variables (1,000–500 hPa thickness field geopotential heights—using NCEP data) and the predictand variables (observed mean maximum summer temperatures over Greece), a new Sd model is constructed. Regression models using generalized least square estimators are developed in order to eliminate the trends within the time series. The advantages of the suggested method compared to the classical method are quantified in terms of a number of distinct performance criteria, e.g., Mean squared error which is the basic criterion of the estimated downscaled values relative to the observed. Finally, the suggested Sd models are used to evaluate the effects of a future climate scenario (IPCC-SRES: A2) on mean maximum summer temperatures over Greece. The results from the climate projection indicate a temperature increase for the period 2070–2100 which is smaller than the corresponding increase from the classical approach.

Keywords

CCA Climate change scenarios Downscaling method Trend estimation 

Mathematics Subject Classification (2000)

62P12 62H20 62H25 62J05 62M10 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alexandersson H (1986) A homogeneity test applied to precipitation data. J Clim 6: 661–675CrossRefGoogle Scholar
  2. Barnett T, Preisendorfer R (1987) Origin and levels of monthly and seasonal forecast skill for united states surface air temperatures determined by canonical correlation analysis. Mon Weather Rev 115: 1825–1850CrossRefGoogle Scholar
  3. Benestad RE, Hanssen-Bauer I, Chen D (2008) Empirical-statistical downscaling. World Scientific Publishing Company, SingaporeCrossRefGoogle Scholar
  4. Benestad RE (2001) A comparison between two empirical downscaling strategies. Int J Climatol 21(13):1645–1668. doi: 10.1002/joc.703 Google Scholar
  5. Brockwell PJ, Davis RA (2002) Introduction to time series and forecasting, 2nd edn. Springer, NYCrossRefGoogle Scholar
  6. Burkhardt U (1999) Alpine precipitation in a tripled CO2 climate. Tellus A 51: 289–903CrossRefGoogle Scholar
  7. Busuioc A, Tomozeiu R, Cacciamani C (2008) Statistical downscaling model based on canonical correlation analysis for winter extreme precipitation events in the Emilia-Romagna region. Int J Climatol 28:449–464. doi: 10.1002/joc Google Scholar
  8. Busuioc A, Chen D, Hellström C (2001) Performance of statistical downscaling models in GCM validation and regional climate change estimates: application for Swedish precipitation. Int J Climatol 21: 557–578CrossRefGoogle Scholar
  9. Chu J, Xia J, Xu CU, Singh V (2010) Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China. Theor Appl Climatol 99(1): 149–161CrossRefGoogle Scholar
  10. Cubasch U, Meehl GA, Boer GJ, Stouffern MD, Noda A, Senior CA, Raper S, Yap KS (2001) Projections of Future Climate Change. In: Houghton JT, Ding Y, Griggs DJ, Noguer M, Linden PJ, Dai X, Maskell K, Johnson CAClimate change 2001: the scientific basis. Contribution of working Group I to the third assessment report of international panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  11. Draper NR, Smith H (1998) Applied regression analysis, 3rd edn. Wiley, NYGoogle Scholar
  12. Eaton ML, Perlman MD (1973) The non-singularity of generalized sample covariance matrices. Ann Stat 1(4): 710–717CrossRefGoogle Scholar
  13. Everitt B (2005) An R and S-Plus companion to multivariate analysis. Springer, London. doi: 10.10O7/b138954
  14. Flocas HA, Tolika K, Anagnostopoulou Chr, Patrikas I, Maheras P, Vafiadis M (2005) Evaluation of maximun and minimum temperature of NCEP-NCAR reanalysis data over Greece. Theor Appl Climatol 80:49–65. doi: 10.1007/s00704-004-0078-z
  15. Fox J (2002) An R and S-plus companion to applied regression. Sage Publications, USAGoogle Scholar
  16. Gilbert RO (1987) Statistical methods for environmental pollution monitoring. Van Nostrand Reinhold, NYGoogle Scholar
  17. Giorgi F, Hewitson B, Christensen J, Hulme M, Von Storch H, Whetto P, Jones R, Mearns L, Fu C (2001) Regional climate information-evaluation and projections. Chapter 10, IPCC 2001Google Scholar
  18. Hair JF Jr, Anderson RE, Tathamb RL, Black WC (1998) Multivariate data analysis, 5th edn. Prentice Hall, Upper Saddle RiverGoogle Scholar
  19. Hellström C, Chen D, Achberger C, Räisänen J (2001) Comparison of climate change scenarios for Sweden based on statistical and dynamical downscaling of monthly precipitation. Clim Res 19: 45–55CrossRefGoogle Scholar
  20. Hollander M, Wolfe DA (1999) Non parametric statistical methods, 2nd edn. Wiley, NYGoogle Scholar
  21. Huth R (2004) Sensitivity of local daily temperature change estimates to the selection of downscaling models and predictors. J Clim 17:640–652. doi: 10.1175/1520-0442(2004)017<0640:SOLDTC>2.0.CO;2 Google Scholar
  22. Huth R (2002) Statistical downscaling of daily temperature in Central Europe. J Clim 15:1731–1742. doi: 10.1175/1520-0442(2002)015<1731:SDODTI>2.0.CO;2 Google Scholar
  23. Huth R (1999) Statistical downscaling in Central Europe: evaluation of methods and potential predictors. Clim Res 13: 91–101CrossRefGoogle Scholar
  24. Huth R (1997) Potential of continental-scale circulation for the determination of local daily surface variables. Theor Appl Climatol 56: 165–186CrossRefGoogle Scholar
  25. IPCC (2001) Climate change (2001): the scientific basis. In: Houghton JT et al (eds) Contribution of working group i to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  26. Johnson RA, Wichern DW (2007) Applied multivariate statistical analysis, 5th edn. Prentice Hall, Upper Saddle RiverGoogle Scholar
  27. Jones R, Murphy J, Hassel D, Taylor R (2001) Ensemble mean changes in a simulation of the European climate of 2071–2100 using the New Hadley Centre regional modeling system HadAM3H /HadRM3. Hadley Centre Meteorological Office, BracknellGoogle Scholar
  28. Kalnay E, Kanamitsou M, Kistler R, Collins W, Deaven D, Gandil L, Irebell M, Saha S, White G, Woolen J, Zhu Y, Leetmaa A, Reynolds R, Chelliah M, Ebisuzaki W, Huggins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteor Soc 77: 437–471CrossRefGoogle Scholar
  29. Kapsomenakis I, Zanis P, Douvis K, Filandras C, Nikolakis D, Zerefos C, Tselioudis G (2009) Future projections of climate change for Greece based on regional and Global climate models. In: Proccedings of the 9th COMECAP, Thessaloniki, Greece, pp 377–384Google Scholar
  30. Kjellström E, Bärring L, Gollvik S, Hansson U, Jones C, Samuelsson P, Rummukainen M, Ullersting A, Willèn U, Wyser K (2006) A 140-year simulation of European climate with the new version of the Rossby centre regional atmospheric climate model (RCA3). RMK 108. SMHI, NorrkopingGoogle Scholar
  31. Kostopoulou E, Giannakopoulos C, Anagnostopoulou C, Tolika K, Maheras P, Vafiadis M, Founda D (2007) Simulating maximum and minimum temperatures over Greece: a comparison of three downscaling techniques. Theor Appl Clim 90:65–82. doi: 10.1007/s00704-006-0269-x Google Scholar
  32. Kyselý J (2002) Comparisons of extremes in GCM-simulated downscaled and observed central-European temperature series. Clim Res 20: 211–222CrossRefGoogle Scholar
  33. Lee J, Lund R (2004) Revisiting simple linear regression with autocorrelated errors. Biometrika 91(1): 240–245CrossRefGoogle Scholar
  34. Lutz K, Jacobeit J, Phillip A, Seubert S, Kunstmann H, Laux P (2011) Comparison and evaluation of statistical downscaling techniques for station-based precipitation in the Middle-East. Int J Climatol. doi: 10.1002/joc.2381
  35. Maheras P, Tolika K, Roussi E, Kolyva-Machera F (2010) Scénarios de changements des températures extrèmes en Grèce pou la fin du XXIÈME siècle: simulations futures par un modèle du projet “ENSEBLES”. In: Proccedings of the 23ième Colloque de l’ Association Internationale de Climatologie, Rennes 2010, pp 361–366Google Scholar
  36. Maheras P, Flocas H, Tolika K, Anagnostopoulou C, Vafiadis M (2006) Circulation types and extreme temperatures changes in Greece. Clim Res 30: 161–174CrossRefGoogle Scholar
  37. Maheras P, Anagnostopoulou C (2003) Circulation types and their influence on the interannual variability and precipitation changes in Greece. In: Bolle HJMediterranean climate: variability and trends. Springer, Berlin, pp 215–239Google Scholar
  38. Millard PSt, Neerchal NK (2000) Environmental statistics with S-Plus. CRS Press LLC, NW Corporate BlvdCrossRefGoogle Scholar
  39. Neykov N, Neytshev P, Zucchini W, Hristov H (2011) Linking atmospheric circulation to daily precipitation patterns over the territory of Bulgaria. Environ Ecol Stat. doi: 10.1007/s10651-011-0185-9
  40. Nicholas RE, Battisti DS (2012) Empirical downscaling of high-resolution regional precipitation from large-scale reanalysis fields. J Appl Meteor Climatol 51:100–114. doi: 10.1175/JAMC-D-11-04.1 Google Scholar
  41. Quadrelli R, Wallace JM (2004) A simplified linear framework for interpreting patterns of Northern Hemisphere wintertime climate variability. J Clim 17:3728–3744. doi: 10.1175/1520-0442(2004)017<3728:ASLFFI>2.0.CO;2 Google Scholar
  42. Salathè JREP (2003) Comparison of various precipitation downscaling methods for the simulation of streamflow in a Rainshadow River Basin. Int J climatol 23: 887–901CrossRefGoogle Scholar
  43. Schubert S (1998) Downscaling local extreme temperature changes in South-Eastern Australia for the CSIRO MARK2 GCM. Int J Climatol 18: 1419–1438CrossRefGoogle Scholar
  44. Skaugen Engen T (2007) Refinement of dynamically downscaled precipitation and temperature scenarios. Clim Change 84:365–382. doi: 10.1007/s10584-007-9251-6 Google Scholar
  45. Skourkeas A, Kolyva-Machera F, Maheras P (2010) Estimation of mean maximum summer and mean minimum winter temperatures over Greece in 2070–2100 using statistical downscaling methods. Euro Asian J Sustain Energy Dev Policy 2: 33–44Google Scholar
  46. Souvignet M, Heinrich J (2011) Statistical downscaling in the arid central Andes: uncertainty analysis of multi-model simulated temperature and precipitation. Theor Appl Climatol 106:229–244. doi: 10.1007/s00704-011-0430-z
  47. STARDEX (2005) Deliverable D13: recommendations on the most reliable predictor variables and evaluation of inter-relationships. http://www.cru.uea.ac.uk/cru/projects/stardex/deliverables/D13/. Accessed 15 May 2005
  48. Timm NH (2004) Applied multivariate analysis. Springer, NYCrossRefGoogle Scholar
  49. Tolika K, Maheras P, Vafiadis M, Flocas HA, Arseni-Papadimitriou A (2007) Simulation of seasonal precipitation and raindays over Greece: a statistical downscaling technique based on artificial neural networks (ANNs). Int J Climatol 27:861–881. doi: 10.1002/joc1442 Google Scholar
  50. Tomezeiu R, Cacciamani C, Pavan V, Morgillo A, Busuioc A (2006) Climate change scenarios of surface temperature in Emilia-Romagna (Italy) obtained using statistical downscaling. Theor Appl Clim. doi: 10.107/s00704-006-0275-z
  51. Von Storch H, Zwiers FW (1999) Statistical analysis in climate research. Cambridge University Press, CambridgeGoogle Scholar
  52. 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
  53. Wilby RL, Dawson CW, Barrow EM (2002) SDSM-a decision support tool for the assesment of regional clmate change impacts. Environ Model Softw 17(2): 145–157CrossRefGoogle Scholar
  54. Wilby RL, Wigley TML (2000) Precipitation predictors for downscaling: observed and general circulation model relationships. Int J Climatol 20: 641–664CrossRefGoogle Scholar
  55. Xoplaki E, Gonzà àlez-Rouco JF, Gyalistras D, Luterbacher J, Rickli R, Wanner H (2003). International summer air temperature variability over Greece and its connection to the large-scale atmospheric circulation and mediterranean SSTs 1950–1999. Clim Dyn 20:537–554. doi: 10.1007/s00382-002-0291-3 Google Scholar
  56. Xoplaki E (2002) Climate variability over the Mediterranean. Phd Thesis, University of BernGoogle Scholar
  57. Yang W, Bärdossy A, Caspary HJ (2010) Downscaling daily precipitation time series using a combined circulation-and regression-based approach. Theor Appl Climatol 102:439–454. doi: 10.1007/s00704-010-0272-0 Google Scholar
  58. Zorita E, Von Storch H (1999) The analog method as a simple statistical downscaling technique: comparison with more complicated methods. J Clim 12: 2474–2489CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Anastasios Skourkeas
    • 1
  • Fotini Kolyva-Machera
    • 1
  • Panagiotis Maheras
    • 2
  1. 1.Section of Statistics and Operation Research, Mathematics DepartmentAristotle University of Thessaloniki (A.U.Th.)ThessalonikiGreece
  2. 2.Department of Meteorology and Climatology, School of GeologyAristotle University of Thessaloniki (A.U.Th.)ThessalonikiGreece

Personalised recommendations