Climate Dynamics

, Volume 32, Issue 7, pp 1097–1106

Improved confidence in climate change projections of precipitation evaluated using daily statistics from the PRUDENCE ensemble

  • Fredrik Boberg
  • Peter Berg
  • Peter Thejll
  • William J. Gutowski
  • Jens H. Christensen
Article

DOI: 10.1007/s00382-008-0446-y

Cite this article as:
Boberg, F., Berg, P., Thejll, P. et al. Clim Dyn (2009) 32: 1097. doi:10.1007/s00382-008-0446-y

Abstract

An ensemble of regional climate modelling simulations from the European framework project PRUDENCE are compared across European sub-regions with observed daily precipitation from the European Climate Assessment dataset by characterising precipitation in terms of probability density functions (PDFs). Models that robustly describe the observations for the control period (1961–1990) in given regions as well as across regions are identified, based on the overlap of normalised PDFs, and then validated, using a method based on bootstrapping with replacement. We also compare the difference between the scenario period (2071–2100) and the control period precipitation using all available models. By using a metric quantifying the deviation over the entire PDF, we find a clearly marked increase in the contribution to the total precipitation from the more intensive events and a clearly marked decrease for days with light precipitation in the scenario period. This change is tested to be robust and found in all models and in all sub-regions. We find a detectable increase that scales with increased warming, making the increase in the PDF difference a relative indicator of climate change level. Furthermore, the crossover point separating decreasing from increasing contributions to the normalised precipitation spectrum when climate changes does not show any significant change which is in accordance with expectations assuming a simple analytical fit to the precipitation spectrum.

Keywords

Regional climate change Extreme events Precipitation Probability distributions Bootstrapping with replacement Crossing-point statistics 

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Fredrik Boberg
    • 1
  • Peter Berg
    • 1
  • Peter Thejll
    • 1
  • William J. Gutowski
    • 2
  • Jens H. Christensen
    • 1
  1. 1.Danish Climate CentreDanish Meteorological InstituteCopenhagen ØDenmark
  2. 2.Department of Geological and Atmospheric SciencesIowa State UniversityAmesUSA

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