Statistical downscaling of daily precipitation over Sweden using GCM output

  • Fredrik WetterhallEmail author
  • András Bárdossy
  • Deliang Chen
  • Sven Halldin
  • Chong-yu Xu
Original Paper


A classification of Swedish weather patterns (SWP) was developed by applying a multi-objective fuzzy-rule-based classification method (MOFRBC) to large-scale-circulation predictors in the context of statistical downscaling of daily precipitation at the station level. The predictor data was mean sea level pressure (MSLP) and geopotential heights at 850 (H850) and 700 hPa (H700) from the NCEP/NCAR reanalysis and from the HadAM3 GCM. The MOFRBC was used to evaluate effects of two future climate scenarios (A2 and B2) on precipitation patterns on two regions in south-central and northern Sweden. The precipitation series were generated with a stochastic, autoregressive model conditioned on SWP. H850 was found to be the optimum predictor for SWP, and SWP could be used instead of local classifications with little information lost. The results in the climate projection indicated an increase in maximum 5-day precipitation and precipitation amount on a wet day for the scenarios A2 and B2 for the period 2070–2100 compared to 1961–1990. The relative increase was largest in the northern region and could be attributed to an increase in the specific humidity rather than to changes in the circulation patterns.


Circulation Pattern Precipitation Amount Moisture Flux Statistical Downscaling Precipitation Model 
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.



The precipitation data in this study were made available through the SWECLIM program supported by MISTRA and SMHI. NCEP reanalysis data were provided by NCEP/NCAR. The GCM data from HadAM3P were provided by the Hadley Centre for Climate Prediction and Research, UK Met Office, regridded and supplied by the STARDEX project. Swedish Research Council and Swedish Rescue Services Agency were acknowledged for their support to Deliang Chen.


  1. Achberger C, Chen D (2006) Trend of extreme precipitation in Sweden and Norway during 1961–2004. Research Report C72, ISSN 1400-383X. Earth Sciences Centre, Göteborg University, Göteborg, Sweden, 58 ppGoogle Scholar
  2. Bárdossy A, Plate EJ (1992) Space-time model for daily rainfall using atmospheric circulation patterns. Water Resour Res 28(5):1247–1259CrossRefGoogle Scholar
  3. Bárdossy A, Stehlik J, Caspary H-J (2001) Generating of areal precipitation series in the Upper Neckar Catchment. Phys Chem Earth B2(69);683–687Google Scholar
  4. Bárdossy A, Stehlík J, Caspary H-J (2002) Automated objective classification of daily circulation patterns for precipitation and temperature downscaling based on optimized fuzzy rules. Clim Res 23:11–22CrossRefGoogle Scholar
  5. Baur F, Hess P, Nagel H (1944) Kalender der Grosswetterlagen Europas 1881–1939. Bad Homburg, p 35Google Scholar
  6. Bonham-Carter GF (1994) Geographic information systems for geoscientists: modelling with GIS. Pergamon, Oxford, UK, 398 ppGoogle Scholar
  7. 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
  8. Chen D (2000) A monthly circulation climatology for Sweden and its application to a winter temperature case study. Int J Climatol 20:1067–1076CrossRefGoogle Scholar
  9. Chen D, Achberger C, Räisänen J, Hellström C (2006) Using statistical downscaling to quantify the GCM-related uncertainty in regional climate change scenarios: a case study of Swedish precipitation. Adv Atmos Sci 23:154–60CrossRefGoogle Scholar
  10. Christensen JH, Carter TR, Rummukainen M, Amanatididis G (2007) Evaluating the performance and utility of regional climate models: the PRUDENCE project. Clim Change 81(Suppl):1–6CrossRefGoogle Scholar
  11. Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 27:1547–1578CrossRefGoogle Scholar
  12. Hanssen-Bauer I, Förland E (2000) Temperature and precipitation variations in Norway 1900–1994 and their links to atmospheric circulation. Int J Climatol 20:1693–1708CrossRefGoogle Scholar
  13. Hanssen-Bauer I, Achberger C, Benestad R, Chen D, Førland E (2005) Empirical-statistical downscaling of climate scenarios over Scandinavia: a review. Clim Res 29:255–268CrossRefGoogle Scholar
  14. Hellström C (2005) Atmospheric conditions during extreme and non-extreme precipitation events in Sweden. Int J Climatol 25:631–648CrossRefGoogle Scholar
  15. Hellström C, Chen D (2003) Statistical downscaling based on dynamically downscaled predictors: application to monthly precipitation in Sweden. Adv Atmos Sci 20:951–958CrossRefGoogle Scholar
  16. Hellström C, Malmgren B (2004) Spatial analysis of extreme precipitation in Sweden 1961–2000. Ambio 33:187–192Google Scholar
  17. Hellström C, Chen D, Achberger C, Räisänen J (2001) A comparison of climate change scenarios for Sweden based on statistical and dynamical downscaling of monthly precipitation. Clim Res 19:45–55CrossRefGoogle Scholar
  18. Johns TC, Gregory JM, Ingram WJ, Johnson CE, Jones A, Lowe JA, Mitchell JFB, Roberts DL, Sexton DMH, Stevenson DS, Tett SFB, Woodage MJ (2003) Anthropogenic climate change for 1860 to 2100 simulated with the HadCM3 model under updated emission scenarios. Clim Dyn 20:583–612Google Scholar
  19. 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 (1996) NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471CrossRefGoogle Scholar
  20. Linderson M-L, Achberger C, Chen D (2004) Statistical downscaling and scenario construction of precipitation in Scania, southern Sweden. Nordic Hydrol 35:261–278Google Scholar
  21. Loaiciga HA, Valdes JB, Vogel R, Garvey J, Schwarz H (1996) Global warming and the hydrologic cycle. J Hydrol 174:83–127CrossRefGoogle Scholar
  22. Moberg A, Jones PD, Lister D, Walther A, Brunet M, Jacobeit J, Saladie O, Sigro J, Aguilar E, Della-Marta P, Luterbacher J, Yiou P, Alexander LV, Chen D, Klein Tank AMG, Alexandersson H, Almarza C, Auer I, Barriendos M, Begert M, Bergström H, Böhm R, Butler J, Caesar J, Drebs A, Founda D, Gerstengarbe F-W, Giusi M, Jónsson T, Maugeri M, Österle H, Pandzic K, Petrakis M, Srnec L, Tolasz R, Tuomenvirta H, Werner PC, Linderholm H, Philipp A, Wanner H, Xoplaki E (2006) Indices for daily temperature and precipitation extremes in Europe analysed for the period 1901–2000. J Geophys Res 111, D22106. DOI  10.1029/2006JD007103 CrossRefGoogle Scholar
  23. Nijssen B, Bowling LC, Lettenmaier DP, Clark DB, Maayar ME, Essery R, Goers S, Gusev YM, Habets F, van den Hurk B, Jin J, Kahan D, Lohmann D, Ma X, Mahanama S, Mocko D, Nasonova O, Niu G-Y, Samuelsson P, Shmakin AB, Takata K, Verseghy D, Viterbo P, Xia Y, Xue Y, Yangu Z-L (2003) Simulation of high latitude hydrological processes in the Torne-Kalix basin: PILPS Phase 2(e) 2: comparison of model results with observations. Glob Planet Change 38:31–53CrossRefGoogle Scholar
  24. Pope DV, Gallani M, Rowntree R, Stratton A (2000) The impact of new physical parameterizations in the Hadley Centre climate model: HadAM3. Clim Dyn 16:123–146CrossRefGoogle Scholar
  25. Rummukainen M, Bergström S, Persson G, Rodhe J, Tjernström M (2004) The Swedish regional climate modelling programme, SWECLIM: a review. Ambio 33(4-5):176–182Google Scholar
  26. Smith SM, Legler DM, Verzone KV (2001) Quantifying uncertainties in NCEP reanalyses using high-quality research vessel observations. J Clim 14:4062–4072CrossRefGoogle Scholar
  27. STARDEX (2001) Statistical and regional dynamical downscaling of extremes for European regions. Description of work. stardex/description.pdf. Accessed 17 August 2005
  28. STARDEX (2005) Deliverable D13: recommendations on the most reliable predictor variables and evaluation of inter-relationships. Accessed 15 May 2005
  29. Stehlik J, Bardossy A (2002) Multivariate stochastic downscaling model for generating daily precipitation series based on atmospheric circulation. J Hydrol 256:120–141CrossRefGoogle Scholar
  30. Stehlik J, Bardossy A (2003) Statistical comparison of European circulation patterns and development of a continental scale classification. Theor Appl Climatol 76:31–46CrossRefGoogle Scholar
  31. Wetterhall F, Halldin S, Xu C-Y (2005) Statistical downscaling of precipitation in Sweden using the analogue method. J Hydrol 306:174–190CrossRefGoogle Scholar
  32. Wetterhall F, Bardossy A, Chen D, Halldin S, Xu C-Y (2006) Daily precipitation-downscaling techniques in three Chinese regions. Water Resour Res 42, W11423. DOI  10.1029/2005WR004573 CrossRefGoogle Scholar
  33. Wetterhall F, Halldin S, Xu C-Y (2007) Seasonality properties of four statistical-downscaling methods in central Sweden. Theor Appl Climatol 87(1-4):123–137CrossRefGoogle Scholar
  34. Wilby RL, Wigley TML (1997) Downscaling general circulation model output: a review of methods and limitations. Prog Phys Geogr 21:530–548CrossRefGoogle Scholar
  35. Wilby RL, Hay LE, Leavesley GH (1999) A comparison of downscaled and raw GCM output: implications for climate change scenarios in the San Juan River Basin, Colorado. J Hydrol 225:67–91CrossRefGoogle Scholar
  36. Wilby RL, Wigley TML (2000) Precipitation predictors for downscaling: observed and general circulation model relationships. Int J Climatol 20:641–661CrossRefGoogle Scholar
  37. Xu C-Y (1999a) From GCMs to river flow: a review of downscaling methods and hydrologic modeling approaches. Prog Phys Geogr 23:229–249Google Scholar
  38. Xu C-Y (1999b) Climate change and hydrologic models: a review of existing gaps and recent research developments. Water Resour Manage 13:369–382CrossRefGoogle Scholar
  39. Yang W (2008) Discrete-continuous downscaling model for generating daily precipitation time series. PhD Thesis, Universität Stuttgart, GermanyGoogle Scholar
  40. Zorita E, von Storch H (1999) The analogue method as a simple statistical downscaling technique: comparison with more complicated methods. J Clim 12:2474–2489CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Fredrik Wetterhall
    • 1
    • 2
    Email author
  • András Bárdossy
    • 3
  • Deliang Chen
    • 4
  • Sven Halldin
    • 2
  • Chong-yu Xu
    • 5
  1. 1.Swedish Meteorological and Hydrological InstituteNorrköpingSweden
  2. 2.Air and Water Science, Department of Earth SciencesUppsala UniversityUppsalaSweden
  3. 3.Institut fur WasserbauStuttgart UniversityStuttgartGermany
  4. 4.Regional Climate group, Earth Sciences CentreGöteborg UniversityGöteborgSweden
  5. 5.Department of GeosciencesUniversity of OsloOsloNorway

Personalised recommendations