Jump to ContentJump to Main Navigation
Show Summary Details
In This Section

Quaestiones Geographicae

The Journal of Adam Mickiewicz University

4 Issues per year

CiteScore 2016: 0.43

SCImago Journal Rank (SJR) 2015: 0.286
Source Normalized Impact per Paper (SNIP) 2015: 0.722

Open Access
See all formats and pricing
In This Section

How Reliable Are Selected Methods Of Projections Of Future Thermal Conditions? A Case From Poland

Joanna Wibig
  • Corresponding author
  • Department of Meteorology and Climatology, University of Łódź, Poland
  • Email:
/ Joanna Jędruszkiewicz
  • Institute of Geography, Pedagogical University, Kraków, Poland
Published Online: 2015-12-30 | DOI: https://doi.org/10.1515/quageo-2015-0025


The aim of the paper was to assess the robustness of four bias correction techniques: simple bias correction, distribution based bias correction, delta change and distribution based delta change. Data from nine RCM simulations of CORDEX project and 41 Polish weather stations were used. The methods were calibrated in the period 1971–1985 and evaluated in 1991–2005. The improvement in mean, 10th and 90th percentiles was shown, without significant differences among methods. For 1st and 99th percentiles the improvement was generally weaker and simple methods seem to be more robust than the distribution based ones. Strong differences between individual models were found, so the use of model ensemble is recommended.

Keywords: bias correction; delta change; regional climate models; temperature; Poland


  • Alexandersson H., Moberg A., 1997. Homogenization of Swedish temperature data. Part 1: Homogeneity test for linear trends. International Journal of Climatology 17: 25–34. [Crossref]

  • Boberg F., Christensen J.H., 2012. Overestimation of Mediterranean summer temperature projections due to model deficiencies. Nature Climate Change 2: 433–436. [Web of Science]

  • Christensen J.H., Boberg F., Christensen O.B., Lucas-Picher P., 2008. On the need for bias correction of regional climate change projections of temperature and precipitation, Geophysical Research Letters 35: L.20709. DOI: 10.1029/2008GL035694. [Crossref] [Web of Science]

  • Christensen J.H., Christensen O.B., 2007. A summary of the PRUDENCE model projections of changes in European climate by the end of the century. Climatic Change 81 (Suppl. 1): 7–30. [Crossref] [Web of Science]

  • Christensen J.H., Hewitson B., Busuioc A., Chen A., Gao X., Held I., Jones R., Kolli R.K., Kwon W.-T., Laprise R., Magaňa Rueda V., Mearns L., Menéndez C.G., Räisänen J., Rinke A., Sarr A., Whetton P., 2007. Regional climate projections. In:. Solomon S. et al. (ed.), Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

  • Déqué M., 2007. Frequency of precipitation and temperature extremes over France in an antrophogenic scenario: Model results and statistical correction according to observed values. Global and Planetary Change 57: 16–26. [Web of Science] [Crossref]

  • Déqué M., Rowell D.P., Lüthi D., Giorgi F., Christensen J.H., Rockel B., Jacob D., Kjelström E., De Castro M., van den Hurk B., 2007. An intercomparison of regional climate simulations for Europe: assessing uncertainties in model projections. Climatic Change 81 (Suppl. 1): 53–70. [Crossref] [Web of Science]

  • Deser C., Knutti R., Solomon S., Phillips A.S., 2012. Communication of the role of natural variability in future North American climate. Nature Climate Change 2: 775–779.

  • Hay L.E., Wilby R.L., Leavesley G.H., 2000. A comparison of delta change and downscaled GCM scenarios for three mountainous basins in the United States. Journal of American Water Resources Association 36: 387–398. [Crossref]

  • Jacob D., Bärring L., Christensen O.B., Christensen J.H., de Castro M., Déqué M., Giorgi F., Hagemann S., Hirschi M., Jones R., Kjellström E., Lenderink G., Rockel B., Sánchez E., Schär C., Seneviratne S.I., Somot S., van Ulden A., van den Hurk B., 2007. An intercomparison of regional climate models for Europe: model performance in present-day climate. Climatic Change 81: 31–52. [Crossref]

  • Jaczewski A., Brzóska B., Wibig J., 2014. Comparison of temperature indices for three IPCC SRES scenarios based on RegCM simulations for Poland in 2011–2030 period. Meteorologische Zeitschrift 21: 99–106. [Web of Science]

  • Lafon T., Dadson S., Buys G., Prudhomme C., 2013. Bias correction of daily precipitation simulated by regional climate model: a comparison of methods. International Journal of Climatology 33: 1367–1381. DOI: 10.1002/joc.3518. [Web of Science] [Crossref]

  • Lenderink G., Buishand A., van Deursen W., 2007. Estimates of future discharges of the river Rhine using two scenario methodologies: direct versus delta approach. Hydrology and Earth System Science 11: 1145–1159.

  • Maraun D., 2012. Nonstationarities of regional climate model biases in European seasonal mean temperature and precipitation sums. Geophysical Research Letters 39: L06706. DOI: 10.1029/2012GL051210. [Crossref]

  • Maraun D., Wetterhall F., Chandler R.E., Kendon E.J., Widmann M., Brienen S., Rust H.W., Sauter T., Themeβl M., Venema V.K.C., Chun K.P., Goodess C.M., Jones R.G., Onof C., Vrac M., Thiele-Eich I., 2010. Precipitation downscaling under climate change: Recent developements to bridge the gap between dynamical models and the end user. Reviews of Geophysics 48: 2009RG000314. [Web of Science] [Crossref]

  • Piani C., Haerter J.O., Coppola E., 2010. Statistical bias correction for daily precipitation in regional climate models over Europe. Theoretical and Applied Climatology 99: 187–192. [Web of Science] [Crossref]

  • Rummukainen M., 2010. State-of-the-art with regional climate models. Wiley Interdisciplinary Reviews: Climate Change 1: 82–96.

  • Samuelsson P., Jones C.G., Willén U., Ullerstig A., Gollvik S., Hansson U., Jansson C., Kjellström E., Nikulin G., Weser K., 2011. The Rossby Centre Regional Climate Model RCA3: Model description and performance. Tellus A 63: 4–23. DOI: 10.1111/j.1600-0870.2010.00478.x. [Crossref]

  • van Roosmalen L., Sonnenborg T.O., Jensen K.H., Christensen J.H., 2011. Comparison of hydrological simulations of climate change using perturbation of observation and distribution-based scaling. Vadose Zone Journal 10: 136–150. [Web of Science] [Crossref]

  • Xu C., Widen E., Halldin S., 2005. Modelling Hydrological Consequences of Climate Change – Progress and Challenges. Advances of Atmospheric Sciences 22: 789–797.

  • Yang W., Andreasson J., Graham L.P., Olsson J., Rosberg J., Wetterhall F., 2010. Distribution based scaling to improve usability of RCM regional climate projections for hydrological climate change impact studies. Hydrological Research 42: 211–220. [Crossref]

About the article

Received: 2014-05-31

Revised: 2015-07-31

Published Online: 2015-12-30

Published in Print: 2015-09-01

Citation Information: Quaestiones Geographicae, ISSN (Online) 2081-6383, DOI: https://doi.org/10.1515/quageo-2015-0025. Export Citation

© 2015 Faculty of Geographical and Geological Sciences, Adam Mickiewicz University. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. (CC BY-NC-ND 3.0)

Comments (0)

Please log in or register to comment.
Log in