Specification of wet-day daily rainfall quantiles from the mean value

References

• Balakrishnan N. Basu A. P. The exponential distribution: theory, methods and applications. B.V. Publishers: Amsterdam, 1995
   Google Scholar
• Benestad, R. E. 2007. Novel methods for inferring future changes in extreme rainfall over Northern Europe. Clim. Res. 34, 195–210. 10.3402/tellusa.v64i0.14981.
   Google Scholar
• Benestad R. E. 2010. Downscaling precipitation extremes: correction of analog models through PDF predictions. Theor. Appl. Clim. 100, 1. 10.3402/tellusa.v64i0.14981.
   Google Scholar
• Benestad R. E. Chen D. Hanssen-Bauer I. Empirical-statistical downscaling. World Scientific Publishing: Singapore, 2008
   Google Scholar
• Blyth A. M. Benestad R. E. Krehbiel P. R. Latham J. Observations of supercooled raindrops in New Mexico summertime cumuli. J. Atmos. Sci. 1997; 54(4): 569–575.
   Web of Science ®Google Scholar
• Bremnes, J. B. 2004. Probabilistic forecasts of precipitation in terms of quantiles using NWP model output. Monthly Weather Rev. 132, 338347. 10.3402/tellusa.v64i0.14981.
   Google Scholar
• Bretherton C. S. Smith C. Wallace J. M. An intercomparison of methods for finding coupled patterns in climate data. J. Clim. 1992; 5: 541–560.
   Web of Science ®Google Scholar
• Coles S. G. An introduction to statistical modeling of extreme values. Springer: London, 2001
   Google Scholar
• Epstein P. R. Ferber D. Changing planet, changing health. University of California Press: Berkely and Los Angeles CA, 2011
   Google Scholar
• Frei, C, Schöll, R, Fukutome, S, Schmidli, J and Vidale, P. L. 2006. Future change of precipitation extremes in Europe: intercomparison of scenarios from regional climate models. J. Geophys. Res. 111, D06105. 10.3402/tellusa.v64i0.14981.
   Google Scholar
• Friederichs P. Statistical downscaling of extreme precipitation using extreme value theory. Extremes. 2010; 13: 109–132.
   Web of Science ®Google Scholar
• Friederichs P. Hense A. Statistical downscaling of extreme precipitation events using censored quantile regression. Monthly Weather Rev. 2007; 135: 2365–2378.
   Web of Science ®Google Scholar
• Frigessi A. Haug O. Rue H. A dynamic mixture model for unsupervised tail estimation without treshold selection. Extremes. 2003; 5: 219–235.
   Google Scholar
• Frisch U. Sornett D. Extreme deviations and applications. J. Phys. I. 1997; 7(9): 1155–1171.
   Google Scholar
• Giorgi, F, Diffenbaugh, N. S, Gao, X. J, Coppola, E, Dash, S. K and co-authors. 2008. The regional climate change hyper-matrix framework. Eos. 89(45), 445–456.
   Google Scholar
• Haylock, M. R, Hofstra, N, Klein Tank, A. M. G, Klok, E. J, Jones, P. D and co-authors. 2008. A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res. 113, D20119. 10.3402/tellusa.v64i0.14981.
   Google Scholar
• Klein Tank, A. M. G, Wijngaard, J. B, Können, G. P, Böhm, R, Demarée, G and co-authors. 2002. Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment. Int. J. Clim. 22, 1441–1453. Online at: http://eca.knmi.nl.
   Web of Science ®Google Scholar
• Kundzewicz, Z. W, Mata, L. J, Arnell, N, Döll, P, Kabat, P. and co-authors. 2007. Climate change: impacts, adaptation and vulnerabilit. Contribution of Working Group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press: CambridgeUK and New York, NY, USA.
   Google Scholar
• Lanzante J. R. Resistant, robust, and nonparametric techniques for the analysis of climate data. Theory and examples, including applications to historical radiosonde station data. Int. J. Clim. 1996; 16: 1197–1226.
   Web of Science ®Google Scholar
• Legates, D. R and Willmott, C. J. 1990a. Mean seasonal and spatial variability in gauge-corrected global precipitation. Int. J. Clim. 10, 111–127.
   Google Scholar
• Legates D. R. Willmott C. J. Mean seasonal and spatial variability in global surface air temperature. Theor. Appl. Clim. 1990b; 41: 11–21.
   Web of Science ®Google Scholar
• Maraun, D, Wetterhall, F, Chandler, R. E, Kendon, E. J, Widmann, M and co-authors. 2010. Precipitation downscaling under climate change: recent developments to bridge the gap between dynamical models and the end user. Rev. Geophys. 48, 10.3402/tellusa.v64i0.14981.
   Google Scholar
• Oreskes, N, Stainforth, D. A and Smith, L. A. 2010. Adaptation to global warming: Do climate models tell us what we need to know?. Philos. Sci. 77, 1012–1028. 10.3402/tellusa.v64i0.14981.
   Google Scholar
• Orskaug, E, Scheel, I, Frigressi, A, Guttorp, P, Haugen, J. E and co-authors. 2011. Evaluation of a dynamic downscaling of precipitation over the Norwegian mainland. Tellus. 63A, 746–756.
   Google Scholar
• Peterson T. Daan H. Jones P. Initial selection of a GCOS surface network. Bull. Amer. Meteor. Soc. 1997; 78(10): 2145–2152.
   Web of Science ®Google Scholar
• Press W. H. Flannery B. P. Teukolsky S. A. Vetterling W. T. Numerical recipes in pascal. Cambridge University Press: Cambridge, 1989
   Google Scholar
• Pryor, S. C, School, J. T and Barthelmie, R. J. 2005. Empirical downscaling of wind speed probability distributions. J. Geophys. Res. 110, D19109.
   Google Scholar
• R Development Core Team. 2004. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0.
   Google Scholar
• Rogers R. R. Yau M. K. A short course in cloud physics3rd edn. Pergamon Press: Oxford, 1989
   Google Scholar
• Schmidli, J, Goodess, C. M, Frei, C, Haylock, M. R, Hundecha, Y and co-authors. 2007. Statistical and dynamical downscaling of precipitation: an evaluation and comparison of scenarios for the Alps. J. Geophys. Res. 112, D04105. 10.3402/tellusa.v64i0.14981.
   Google Scholar
• Semenov, V. A and Bengtsson, L. 2002. Secular trends in daily precipitation characteristics: greenhouse gas simulation with a coupled AOGCM. Clim. Dyn. 19, 123–140. 10.3402/tellusa.v64i0.14981.
   Web of Science ®Google Scholar
• Smither J. C. Schulze R. E. A methodology for the estimation of short duration design storms in South Africa using a regional approach based on L-moments. J. Hydrol. 2001; 241(1–2): 42–52.
   Web of Science ®Google Scholar
• Solomon, S, Quin, D, Manning, M, Chen, Z, Marquis,M. and co-authors. 2007. Climate change: the physical science basis. contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press: CambridgeUK and New York, NY, USA.
   Google Scholar
• Themeßl, M. J, Gobiet, A and Leuprecht, A. 2010. Empirical-statistical downscaling and error correction of daily precipitation from regional climate models. International J. Clim. 31, 1530–1544.
   Google Scholar
• Timbal B. Jones D. A. Future projections of winter rainfall in southeast Australia using a statistical downscaling technique. Climatic Change. 2008; 86: 165–187.
   Web of Science ®Google Scholar
• van den Besselaar, E. J. M, Haylock, M. R, van der Schrier, G and Klein Tank, A. M. G. 2011. A European daily high-resolution observational gridded data set of sea level pressure. J. Geophys. Res. 116, D11110. 10.3402/tellusa.v64i0.14981.
   Google Scholar
• van der Linden, P. and Mitchell, J. F. B. 2009. Ensembles: climate change and its impacts: summary of research and results from the ENSEMBLES project. European Comission: Met Office Hadley CentreExeter, UK.
   Google Scholar
• Vrac, M and Naveau, P. 2007. Stochastic downscaling of precipitation: from dry events to heavy rainfalls. Water Resour. Res. 43, W07402. 10.3402/tellusa.v64i0.14981.
   Google Scholar
• Wilks D. S. Multisite generalization of a daily stochastic precipitation generation model. J. Hydrol. 1998; 210(1–4): 178–191.
   Web of Science ®Google Scholar
• Wilks D. S. Interannual variability and extreme-value characteristics of several stochastic daily precipitation models. Agr. Forest Meteorol. 1999; 93(3): 153–169.
   Web of Science ®Google Scholar
• Wilson, P. S and Toumi, R. 2005. A fundamental probability distribution for heavy rainfall. Geophys. Res. Lett. 32, L14812. 10.3402/tellusa.v64i0.14981.
   Google Scholar
• Woolhiser D. A. Roldán J. Stochastic daily precipitation models: 2. A comparison of distributions of amounts. Water Resour. Res. 1982; 18(5): 1461–1468.
   Web of Science ®Google Scholar