Theoretical and Applied Climatology

, Volume 90, Issue 1–2, pp 65–82 | Cite as

Simulating maximum and minimum temperature over Greece: a comparison of three downscaling techniques

  • E. Kostopoulou
  • C. Giannakopoulos
  • C. Anagnostopoulou
  • K. Tolika
  • P. Maheras
  • M. Vafiadis
  • D. Founda


Statistical downscaling techniques have been developed for the generation of maximum and minimum temperatures in Greece. This research focuses on the four conventional seasons, and three downscaling approaches, Multiple Linear Regression using a circulation type approach (MLRct), Canonical Correlation Analysis (CCA) and Artificial Neural Networks (ANNs), are employed and compared to assess their performance skills. Models were developed individually for each variable (Tmax, Tmin), station and season. The accuracy of downscaled values has been quantified in terms of a number of performance criteria, such as differences of the mean and standard deviation ratios between observed and modelled data, the correlation coefficients of the two sets, and also the RMSEs of the downscaled values relative to the observed. All methods revealed that during the cool season Tmax tends to be better reproduced, whereas Tmin is overestimated, particularly over western Greece, which is characterised by higher orography. With respect to the warm season, the simulation of Tmax reveals greater divergence, whereas Tmin is better generated. The distinction between the three techniques is somewhat blurred. None of the methods were found to be superior to the others and each has been shown to be a good estimator in some cases. This study concludes that all proposed methods comprise useful tools for simulating daily temperatures, as the high correlation coefficients, between observed and downscaled values, have demonstrated. However, the importance of local factors, which affect the natural variability of temperature, has been emphasised indicating that the geography of a region constitutes an important and rather complex factor, which should be included in models to improve their performance.


Root Mean Square Error General Circulation Model Canonical Correlation Analysis Validation Period Statistical Downscaling 
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.


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  1. Alexandersson, H 1986A homogeneity test applied to precipitation dataJ Climate6661675CrossRefGoogle Scholar
  2. Bárdossy, A, Duckstein, L, Bogardi, I 1995Fuzzy rule-based classification of atmospheric circulation patternsInt J Climatol1510871097CrossRefGoogle Scholar
  3. Bárdossy, A, Stehlík, J, Caspary, HJ 2002Automated objective classification of daily circulation patterns for precipitation and temperature downscaling based on optimized fuzzy rulesClim Res231122Google Scholar
  4. Barnett, T, Preisendorfer, R 1987Origin and levels of monthly and seasonal forecast skill for United States surface air temperatures determined by canonical correlation analysisMon Wea Rev11518251850CrossRefGoogle Scholar
  5. Busuioc, A, von Storch, H, Schnur, R 1999Verification of GCM-generated regional seasonal precipitation for current climate and of statistical downscaling estimates under changing climate conditionsJ Climate12258272Google Scholar
  6. Busuioc, A, Chen, D, Hellström, C 2001Temporal and spatial variability of precipitation in Sweden and its link with the large scale atmospheric circulationTellus53348367CrossRefGoogle Scholar
  7. Cavazos, T 1997Downscaling large-scale circulation to local rainfall in North-Eastern MexicoInt J Climatol1710691082CrossRefGoogle Scholar
  8. Cavazos, T, Hewitson, BC 2005Performance of NCEP–NCAR reanalysis variables in statistical downscaling of daily precipitationClim Res2895107Google Scholar
  9. Chen, DL, Chen, YM 2003Association between winter temperature in China and upper air circulation over East Asia revealed by canonical correlation analysisGlobal Planet Change37315325CrossRefGoogle Scholar
  10. Conway, D, Jones, PD 1998The use of weather types and air flow indices for GCM downscalingJ Hydrol231348361CrossRefGoogle Scholar
  11. Corte-Real, J, Xu, H, Qian, BD 1999A weather generator for obtaining daily precipitation scenarios based on circulation patternsClim Res136175Google Scholar
  12. Easterling, DR 1999Development of regional climate scenarios using a downscaling ApproachClim Change41615634CrossRefGoogle Scholar
  13. Fahlman S (1988) Faster-learning variations on back-propagation: an empirical study. In: Sejnowski TJ, Hinton GE, Touretzky DS (eds) Proceedings of 1988 Connectionist Models Summer School, Morgan Kaufmann, San Mateo, CA, pp 38–51Google Scholar
  14. Giorgi, F 1990Simulation of regional climate using a limited area model nested in a general circulation modelJ Climate3941963CrossRefGoogle Scholar
  15. Giorgi, F, Marinucci, MR, Visconti, G 1990Use of a limited-area model nested in a general circulation model for regional climate simulation over EuropeJ Geophys Res951841318431CrossRefGoogle Scholar
  16. Goodess, CM, Palutikof, JP 1998Development of daily rainfall scenarios for southeast Spain using a circulation-type approach to downscalingInt J Climatol1810511083CrossRefGoogle Scholar
  17. Goodess CM, Anagnostopoulou C, Bárdossy A, Frei C, Harpham C, Haylock MR, Hundecha Y, Maheras P, Ribalaygua J, Schmidli J, Schmith T, Tolika K, Tomozeiu R, Wilby RL (2005) An intercomparison of statistical downscaling methods for Europe and European regions – assessing their performance with respect to extreme temperature and precipitation events. Clim Change PRUDENCE special issue (submitted)Google Scholar
  18. Gonzalez-Rouco, JF, Heyen, H, Zorita, E, Valero, E 2000Agreement between observed rainfall trends and climate change simulations in the southwest of EuropeJ Climate1330573065CrossRefGoogle Scholar
  19. Hanson CE, Palutikof JP, Livermore MTJ, Barring L, Bindi M, Corte-Real J, Duaro R, Giannakopoulos C, Holt T, Kundzewicz Z, Leckebusch G, Radziejewski M, Santos J, Schlyter P, Schwarb M, Stjernquist I, Ulbrich U (2005) Modelling the Impact of Climate Extremes: An overview of the MICE Project. Clim Change PRUDENCE special issue (submitted)Google Scholar
  20. Hanssen-Bauer, I, Førland, EJ 1998Long-term trends in precipitation and temperature in the Norwegian Arctic: can they be explained by changes in atmospheric circulation patterns?Clim Res10143153Google Scholar
  21. Hay, LE, Clark, MP 2003Use of statistically and dynamically downscaled atmospheric model output for hydrologic simulations in three mountainous basins in the western United StatesJ Hydrol2825675CrossRefGoogle Scholar
  22. Heyen, H, Zorita, E, von Storch, H 1996Statistical downscaling of monthly mean North Atlantic air-pressure to sea level anomalies in the Baltic SeaTellus48312323CrossRefGoogle Scholar
  23. Hewitson, BC, Crane, RG 1996Climate downscaling: techniques and applicationClim Res78595Google Scholar
  24. Huth, R 1997Potential of continental-scale circulation for the determination of local daily surface variablesTheor Appl Climatol56165186CrossRefGoogle Scholar
  25. Huth, R 1999Statistical downscaling in central Europe: Evaluation of methods and potential predictorClim Res1391101Google Scholar
  26. Huth, R 2002Statistical downscaling of daily temperature in central EuropeJ Clim1517311742CrossRefGoogle Scholar
  27. IPCC (2001) Climate Change 2001: The Scientific Basis. In: Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Maskell K, Johnson CA (eds) Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press, 881 ppGoogle Scholar
  28. Kalnay, E, Kanamitsu, M, Kistler, R, Collins, W, Deaven, D, Gandin, L, Iredell, M, Saha, S, White, G, Woollen, J, Zhu, Y, Chelliah, M, Ebisuzaki, W, Higgins, W, Janowiak, J, Mo, KC, Ropelewski, C, Wang, J, Leetmaa, A, Reynolds, R, Jenne, R, Joseph, D 1996The NCEP/NCAR 40-year reanalysis projectBull Amer Meteor Soc77437471CrossRefGoogle Scholar
  29. Kidson, JW, Thompson, CS 1998A comparison of statistical and model-based downscaling techniques for estimating local climate variationsJ Clim11735753CrossRefGoogle Scholar
  30. Kilsby, CG, Cowpertwait, PSP, O’Connell, PE, Jones, PD 1998Predicting rainfall statistics in England and Wales using atmospheric circulation variablesInt J Climatol18523539CrossRefGoogle Scholar
  31. Kistler, R, Kalnay, E, Collins, W, Saha, S, White, G, Woollen, J, Chelliah, M, Ebisuzaki, W, Kanamitsu, M, Kousky, V, Van den Dool, H, Jenne, R, Fiorino, M 2001The NCEP–NCAR 50-Year Reanalysis: Monthly Means CD-ROM and DocumentationBull Amer Meteor Soc82247267CrossRefGoogle Scholar
  32. Kostopoulou E (2003) The relationships between atmospheric circulation patterns and surface climatic elements in the eastern Mediterranean. Norwich: University of East Anglia, PhD dissertation, 407 ppGoogle Scholar
  33. Maheras, P, Anagnostopoulou, C 2003Circulation types and their influence on the interannual variability and precipitation changes in GreeceBolle, HJ eds. Mediterranean climate: variability and trendsSpringerBerlin215239Google Scholar
  34. Maheras, P, Patrikas, I, Karacostas, T, Anagnostopoulou, C 2000Automatic classification of circulation types in Greece: methodology, description, frequency, variability and trend analysisTheor Appl Climatol67205223CrossRefGoogle Scholar
  35. Maheras, P, Flocas, HA, Anagnostopoulou, C, Patrikas, I 2002On the vertical structure of composite surface cyclones in the Mediterranean regionTheor Appl Climatol71199217CrossRefGoogle Scholar
  36. Maheras, P, Tolika, K, Anagnostopoulou, C, Vafiadis, M, Patrikas, I, Flocas, H 2004On the relationships between circulation types and changes in rainfall variability in GreeceInt J Climatol2416951712CrossRefGoogle Scholar
  37. Mearns, LO, Rosenzweig, C, Goldberg, R 1997Mean and variance change in climate scenarios: methods, agricultural applications, and measures of uncertaintyClim Change35367396CrossRefGoogle Scholar
  38. Michaelides, SC, Pattichis, CS, Kleovoulou, G 2001Classification of rainfall variability by using artificial neural networksInt J Climatol2114011414CrossRefGoogle Scholar
  39. Murphy, J 1999An evaluation of statistical and dynamical techniques for downscaling local climateJ Climate1222562284CrossRefGoogle Scholar
  40. Olsson, J, Uvo, CB, Jinno, K 2001Statistical atmospheric downscaling of short-term extreme rainfall by neural networksPhys Chem Earth26695700CrossRefGoogle Scholar
  41. Palutikof, JP, Winkler, JA, Goodess, CM, Andresen, JA 1997The simulation of daily temperature time series from GCM output. Part I: Comparison of model data with observationsJ Climate1024972513CrossRefGoogle Scholar
  42. Sailor, DJ, Li, XS 1999A semiempirical downscaling approach for predicting regional temperature impacts associated with Climate ChangeJ Climate12103114Google Scholar
  43. Schoof, JT, Pryor, SC 2001Downscaling temperature and precipitation: a comparison of regression-based methods and artificial neural networksInt J Climatol21773790CrossRefGoogle Scholar
  44. Schubert, S, Henderson-Sellers, A 1997A statistical model to downscale local daily temperature extremes from synoptic-scale atmospheric circulation patterns in the Australian regionClim Dyn13223234CrossRefGoogle Scholar
  45. Trigo, RM, Palutikof, JP 1999Simulation of daily temperatures for climate change scenarios over Portugal: a neural network model approachClim Res134559Google Scholar
  46. Trigo, RM, Palutikof, JP 2001Precipitation scenarios over Iberia: A comparison between direct GCM output and different downscaling techniquesJ Climate1444224446CrossRefGoogle Scholar
  47. von Storch, H 1995Spatial Patterns: EOFs and CCAvon Storch, HNavara, A eds. Analysis of climate variability: application of statistical techniquesSpringerBerlin227258Google Scholar
  48. Wasserman, PD 1989Neural Computing: theory and practiceVan Nostrand ReinholdNew York230Google Scholar
  49. Werner, P, von Storch, H 1993Interannual variability of Central European mean temperature in January/February and its relation to large-scale circulationClim Res3195207Google Scholar
  50. Wilby, RL, Barnsley, N, O’Hare, G 1995Rainfall variability associated with Lamb weather types: the case for incorporating weather frontsInt J Climatol1512411252CrossRefGoogle Scholar
  51. Wilby, RL, Wigley, TML 1997Downscaling general circulation model output: a review of methods and limitationsProgress in Physical Geography21530548Google Scholar
  52. Wilby, RL, Wigley, TML, Conway, D, Jones, PD, Hewitson, BC, Main, J, Wilks, DS 1998Statistical downscaling of general circulation model output: A comparison of methodsWater Resour Res3429953008CrossRefGoogle Scholar
  53. Wilby, RL, Wigley, TML 2000Precipitation predictors for downscaling: observed and general circulation model relationshipsInt J Climatol20641661CrossRefGoogle Scholar
  54. Wilby, RL, Conway, D, Jones, PD 2002Prospects for downscaling seasonal precipitation variability using conditioned weather generator parametersHydrol Process1612151234CrossRefGoogle Scholar
  55. Xoplaki E (2002) Climate variability over the Mediterranean. Bern: Universität Bern, PhD dissertation, 191 ppGoogle Scholar
  56. Xoplaki, E, Gonzalez-Rouco, JF, Gyalistras, D, Luterbacher, J, Rickli, R, Wanner, H 2003Interannual summer air temperature variability over Greece and its connection to the large-scale atmospheric circulation and Mediterranean SSTs 1950–1999Clim Dyn20537554Google Scholar
  57. Zorita, E, Kharin, VV, von Storch, H 1992The atmospheric circulation and sea surface temperature in the North Atlantic area in winter: Their interaction and relevance for Iberian precipitationJ Climate510971108CrossRefGoogle Scholar
  58. Zorita, E, von Storch, H 1999The analog method as a simple statistical downscaling technique: comparison with more complicated methodsJ Climate1224742489CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • E. Kostopoulou
    • 1
  • C. Giannakopoulos
    • 1
  • C. Anagnostopoulou
    • 2
  • K. Tolika
    • 2
  • P. Maheras
    • 2
  • M. Vafiadis
    • 3
  • D. Founda
    • 1
  1. 1.Institute for Environmental Research and Sustainable DevelopmentNational Observatory of Athens, I. Metaxa & V. PavlouPalaia PendeliGreece
  2. 2.Department of Meteorology and ClimatologyAristotle University of Thessaloniki, University CampusThessalonikiGreece
  3. 3.Division of Hydraulics, Faculty of TechnologyUniversity of Thessaloniki, University CampusThessalonikiGreece

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