ADGEO Advances in Geosciences ADGEO Adv. Geosci. 1680-7359 Copernicus Publications Göttingen, Germany 10.5194/adgeo-31-75-2012 Statistical bias correction of global climate projections – consequences for large scale modeling of flood flows Eisner S. 1 Voss F. 1 Kynast E. 1 University of Kassel, Center for Environmental Systems Research (CESR), Wilhelmshöher Allee 47, 34109 Kassel, Germany 11 12 2012 31 75 82 Copyright: © 2012 S. Eisner et al. 2012 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://adgeo.copernicus.org/articles/31/75/2012/adgeo-31-75-2012.html The full text article is available as a PDF file from https://adgeo.copernicus.org/articles/31/75/2012/adgeo-31-75-2012.pdf

General circulation models (GCMs) project an increasing frequency and intensity of heavy rainfall events due to global climate change. This rather holds true for regions that are even expected to experience an overall decrease in average annual precipitation. Consequently, this may be attended by an increasing frequency and magnitude of flood events. However, time series of GCMs show a bias in simulating 20th century precipitation and temperature fields and, therefore, cannot directly be used to force hydrological models in order to assess the impact of the projected climate change on certain components of the hydrological cycle. For a posteriori correction, the so-called delta change approach is widely-used which adds the 30-year monthly differences for temperature or ratios for precipitation of the GCM data to each month of a historic climate data set. As the variability of the climate variables in the scenario period is not transferred, this approach is especially questionable if discharge extremes are to be analyzed. In order to preserve the variability given by the GCM, methods of statistical bias correction are applied. This study aims to investigate the impact of two methods of bias correction, the delta change approach and a statistical bias correction, on the large scale modeling of flood discharges, using the example of 25 macroscale catchments in Europe. The discharge simulation is carried out with the global integrated model WaterGAP3 (Water – Global Assessment and Prognosis). Results show that the two bias correction methods lead to distinctively different trends in future flood flows.

 References Alcamo, J., Döll, P., Henrichs, T., Kaspar, F., Lehner, B., Rösch, T., and Siebert, S.: Development and testing of the WaterGAP 2 global model of water use and availability, Hydrolog. Sci. J., 48, 317–337, 2003. Allen, M. R. and Ingram, W. J.: Constraints on future changes in climate and the hydrologic cycle, Nature, 419, 224–232, 2002. Aus der Beek, T. and Teichert, E.: Global permafrost distribution in the past, present and future, Proc. 9th International Conference on Permafrost, Fairbanks, USA, 29.6.–3.7., 2008. Döll, P., Fiedler, K., and Zhang, J.: Global-scale analysis of river flow alterations due to water withdrawals and reservoirs, Hydrol. Earth Syst. Sci., 13, 2413–2432, https://doi.org/10.5194/hess-13-2413-2009, 2009. Döll, P., Kaspar, F., and Lehner, B.: A global hydrological model for deriving water availability indicators: model tuning and validation, J. Hydrol., 270, 105–134, 2003. Graham, L. P.: Climate change effects on river flow to the Baltic Sea, Ambio, 33, 235–241, 2004. Hegerl, G. C., Zwiers, F. W., Braconnot, P., Gillett, N. P., Luo, Y., Marengo Orsini, J. A., Nicholls, N., Penner, J. E., and Stott, P. A.: Understanding and Attributing Climate Change, in: 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, 2007. IPCC: Climate Change 2007, Synthesis Report, Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Geneva, Switzerland, 2007. Lehner, B., Döll, P., Alcamo, J., Henrichs, T., and Kaspar, F.: Estimating the impact of global change on flood and drought risks in Europe: A continental integrated analysis, Climatic Change, 75, 273–299, 2006. Lehner, B., Verdin, K., and Jarvis, A.: New global hydrography derived from spaceborne elevation data, Eos, Transactions, AGU, 89(10), 93–94, 2008. Lettenmaier, D. P., Wood, A. W., Palmer, R. N., Wood, E. F., and Stakhiv, E. Z.: Water resources implications of global warming: A U.S. regional perspective, Climatic Change, 43, 537–579, 1999. Maniak, U.: Hydrologie und Wasserwirtschaft – Eine Einführung für Ingenieure, Springer, Berlin, Germany, 2005. Meehl, G. A., Stocker, T. F., Collins, W. D., Friedlingstein, P., Gaye, A. T., Gregory, J. M., Kitoh, A., Knutti, R., Murphy, J. M., Noda, A., Raper, S. C. B., Watterson, I. G., Weaver, A. J., and Zhao, Z.-C.: Global Climate Projections, in: 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, 2007. Mitchell, T. D. and Jones, P. D.: An improved method of constructing a database of monthly climate observations and associated high-resolution grids, Int. J. Climatology, 25, 693–712, 2005. Piani, C., Härter, J. O., Hagemann, S., Allen, M., and Rosier, S.: Practical methodologies to correct for biases in climate model output, and to quantify and handle resulting uncertainties in estimates of future components of the global water cycle, WATCH Tech. Rep. No. 22, http://www.eu-watch.org, 2008. Piani, C., Weedon, G. P., Best, M., Gomes, S. M., Viterbo, P., Hagemann, S., and Haerter, J. O.: Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models, J. Hydrol., 395, 199–215, 2010. Rudolf, B. and Schneider, U.: Calculation of Gridded Precipitation Data for the Global Land-Surface using in-situ Gauge Observations, in: Proceedings of the 2nd Workshop of the International Precipitation Working Group IPWG, Monterey, October 2004, 231–247, 2005. Schulze, K. and Döll, P.: Neue Ansätze zur Modellierung von Schneeakkumulation und -schmelze im globalen Wassermodell WaterGAP, in: Neue methodische Ansätze zur Modellierung der Wasser- und Stoffumsätze in groß en Einzugsgebieten, Tagungsband zum 7 Workshop zur großskaligen Modellierung in der Hydrologie, Kassel University Press, Kassel, Germany, 145–154, 2004. Schulze, K., Hunger, M., and Döll, P.: Simulating river flow velocity on global scale, Adv. Geosci., 5, 133–136, https://doi.org/10.5194/adgeo-5-133-2005, 2005. US Water Resources Council (Ed.): Guidelines for determining flood flow frequency, US Government Printing Office, Washington, USA, 1981. Verzano, K.: Climate change impacts on flood related hydrological processes: Further development and application of a global scale hydrological model, Ph.D. thesis, International Max Planck Research School on Earth System Modelling, University of Kassel, Germany, 2009. Weedon, G. P., Gomes, S., Viterbo, P., Osterle, H., Adam, J. C., Bellouin, N., Boucher, O., and Best, M.: The WATCH forcing data 1958–2001: a meteorological forcing dataset for land-surface and hydrological-models, WATCH Tech. Rep. No. 22, http://www.eu-watch.org, 2010. Weiß, M.: Modelling of global change impacts on hydrology with focus on Europe and Africa, Ph.D. thesis, University of Kassel, Germany, 2009.