Advertisement

Theoretical and Applied Climatology

, Volume 87, Issue 1–4, pp 123–137 | Cite as

Seasonality properties of four statistical-downscaling methods in central Sweden

  • F. Wetterhall
  • S. Halldin
  • C.-Y. Xu
Article

Summary

Daily precipitation in northern Europe has different statistical properties depending on season. In this study, four statistical downscaling methods were evaluated in terms of their ability to capture statistical properties of daily precipitation in different seasons. Two of the methods were analogue downscaling methods; one using principal component analysis (PCA) and one using gradients in the pressure field (Teweles-Wobus scores, TWS) to select the analogues in the predictor field. The other two methods were conditional-probability methods; one using classification of weather patterns (MOFRBC) and the other using a regression method conditioning a stochastic weather generator (SDSM). The two analogue methods were used as benchmark methods. The study was performed on seven precipitation stations in south-central Sweden and the large-scale predictor was gridded mean-sea-level pressure over Northern Europe. The four methods were trained and calibrated on 25 years of data (1961–1978, 1994–2000) and validated on 15 years (1979–1993). Temporal and spatial limitations were imposed on the methods to find the optimum predictor settings for the downscaling. The quality measures used for evaluating the downscaling methods were the residuals of a number of key statistical properties, and the ranked probability scores (RPS) for precipitation and maximum length of dry and wet spells. The results showed that (1) the MOFRBC and SDSM outperformed the other methods for the RPS, (2) the statistical properties for the analogue methods were better during winter and autumn; for SDSM and TWS during spring; and for MOFRBC during summer, (3) larger predictor areas were needed for summer and autumn precipitation than winter and spring, and (4) no method could well capture the difference between dry and wet summers.

Keywords

Daily Precipitation Validation Period Statistical Downscaling Analogue Method Residual Function 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bardossy, A, Duckstein, L, Bogardi, I 1995Fuzzy rule-based classification of atmospheric circulation patternsInt J Climatol1510871097Google Scholar
  2. Bardossy, A, Plate, EJ 1992Space-time model for daily rainfall using atmospheric circulation patternsWater Resources Res2812471259CrossRefGoogle Scholar
  3. Barrow, EM, Semenov, MA 1995Climate change scenarios with high spatial and temporal resolution for agricultural applicationsForestry68349360Google Scholar
  4. Baur F, Hess P, Nagel H (1944) Kalender der Grosswetterlagen Europas 1881–1939. Bad Homburg, 35 ppGoogle Scholar
  5. Beckmann, BR, Buishand, TA 2002Statistical downscaling relationships for precipitation in the Netherlands and North GermanyInt J Climatol221532CrossRefGoogle Scholar
  6. Biau, G, Zorita, E, von Storch, H, Wackernagel, H 1999Estimation of precipitation by kriging in the EOF Space of the sea level pressure fieldJ Clim1210701085CrossRefGoogle Scholar
  7. Conway, D, Jones, PD 1998The use of weather types and air flow indices for GCM downscalingJ Hydrol212–213348361CrossRefGoogle Scholar
  8. Cubasch, U, von Storch, H, Waszkewitz, E, Zorita, E 1996Estimates of climate changes in southern Europe using different downscaling techniquesClimate Res7129149Google Scholar
  9. Enke, W, Schneider, F, Deutschländer, T 2005A novel scheme to derive optimized circulation pattern classifications for downscaling and forecast purposesTheor Appl Climatol825163CrossRefGoogle Scholar
  10. Epstein, ES 1969A scoring system for probability forecasts of ranked categoriesJ Appl Meteor8985987CrossRefGoogle Scholar
  11. Eriksson B (1983) Data Rörande Sveriges Nederbördsklimat. Normalvärden för Perioden 1952–1980 (Data concerning the precipitation climate of Sweden. Mean values for the period 1951–1980; in Swedish with English abstract). Swedish Meteorological and Hydrological Institute Norrköping 1983: 28, 92 ppGoogle Scholar
  12. Halldin, S, Gryning, S-E, Gottschalk, L, Jochum, A, Lundin, L-C, Van de Griend, AA 1999Energy, water and carbon exchange in a boreal forest landscape – NOPEX experiencesAgric Forest Meteorol98–99529CrossRefGoogle Scholar
  13. Hanssen-Bauer, I, Førland, EJ 2000Temperature and precipitation variations in Norway and their links to atmospheric circulationInt J Climatol2016931708CrossRefGoogle Scholar
  14. Hay, LE, McCabe, GJ, Wolock, DM, Ayers, MA 1991Simulation of precipitation by weather type analysisWater Resources Res27493501CrossRefGoogle Scholar
  15. Huth, R, Kysely, J 2000Constructing site-specific climate change scenarios on a monthly scale using statistical downscalingTheor Appl Climatol661327CrossRefGoogle Scholar
  16. Johansson, B, Chen, D 2003The influence of wind and topography on precipitation distribution in Sweden: Statistical analysis and modellingInt J Climatol2315231535CrossRefGoogle Scholar
  17. 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 1996NCEP/NCAR 40-year reanalysis projectBull Amer Meteor Soc77437471CrossRefGoogle Scholar
  18. Kilsby, CG, Cowpertwaith, PSP, O’Connell, PE, Jones, PD 1998Predicting rainfall statistics in England and Wales using atmospheric circulation variablesInt J Climatol18523539CrossRefGoogle Scholar
  19. Murphy, AH 1971A note on the ranked probability scoreJ Appl Meteor10155156CrossRefGoogle Scholar
  20. Obled, C, Bontron, G, Garcon, R 2002Quantitative precipitation forecasts: a statistical adaptation of model outputs through an analogues sorting approachAtmos Res63303324CrossRefGoogle Scholar
  21. STARDEX (2001) Statistical and regional dynamical downscaling of extremes for European regions, description of work. http://www.cru.uea.ac.uk/cru/projects/stardex/description.pdf Accessed 2004-02-17
  22. Stehlik, J, Bardossy, A 2002Multivariate stochastic downscaling model for generating daily precipitation series based on atmospheric circulationJ Hydrol256120141CrossRefGoogle Scholar
  23. Stehlik, J, Bardossy, A 2003Statistical comparison of European circulation patterns and development of a continental scale classificationTheor Appl Climatol763146CrossRefGoogle Scholar
  24. Teweles, S,Jr, Wobus, HB 1954Verification of prognostic chartsBull Amer Meteor Soc35455463Google Scholar
  25. Wilby, RL, Dawson, CW, Barrow, EM 2002SDSM – a decision support tool for the assessment of regional climate change impactsEnviron Model Software17147159CrossRefGoogle Scholar
  26. Wilby, RL, Hay, LE, Leavesley, GH 1999A comparison of downscaled and raw GCM output: implications for climate change scenarios in the San Juan River Basin, ColoradoJ Hydrol2256791CrossRefGoogle Scholar
  27. Wilby, RL, Wigley, TML 1997Downscaling general circulation model output: a review of methods and limitationsProgress Phys Geogr21530548Google Scholar
  28. 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 Resources Res3429953008CrossRefGoogle Scholar
  29. Wetterhall, F, Halldin, S, Xu, C-Y 2005Statistical precipitation downscaling in central Sweden with the analogue methodJ Hydrol360174190CrossRefGoogle Scholar
  30. Xu, C-Y 1999From GCMs to river flow: a review of downscaling methods and hydrologic modelling approachesProgress Phys Geogr23229249CrossRefGoogle Scholar
  31. Xu, C-Y, Seibert, J, Halldin, S 1996Regional water balance modelling in the NOPEX area: development and application of monthly water balance modelsJ Hydrol180211236CrossRefGoogle Scholar
  32. Zorita, E, Hughes, JP, Lettenmaier, DP, von Storch, H 1995Stochastic characterization of regional circulation patterns for climate model diagnosis and estimation of local precipitationJ Clim13223234Google Scholar
  33. Zorita, E, von Storch, H 1999The analogue method as a simple statistical downscaling technique: Comparison with more complicated methodsJ Clim1224742489CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • F. Wetterhall
    • 1
  • S. Halldin
    • 1
  • C.-Y. Xu
    • 2
  1. 1.Air and Water Science, Department of Earth SciencesUppsala UniversityVillavägenSweden
  2. 2.Department of GeosciencesUniversity of OsloNorway

Personalised recommendations