Statistical downscaling of daily precipitation over Sweden using GCM output

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

Abstract

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.

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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Fredrik Wetterhall
    • 1
    • 2
  • 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

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