Articles | Volume 18, issue 11
Nat. Hazards Earth Syst. Sci., 18, 2825–2840, 2018
Nat. Hazards Earth Syst. Sci., 18, 2825–2840, 2018

Research article 02 Nov 2018

Research article | 02 Nov 2018

Stochastic downscaling of precipitation in complex orography: a simple method to reproduce a realistic fine-scale climatology

Silvia Terzago et al.

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Cited articles

Badas, M. G., Deidda, R., and Piga, E.: Orographic influences in rainfall downscaling, Adv. Geosci., 2, 285–292,, 2005. a, b
Badas, M. G., Deidda, R., and Piga, E.: Modulation of homogeneous space-time rainfall cascades to account for orographic influences, Nat. Hazards Earth Syst. Sci., 6, 427–437,, 2006. a, b
Bedia, J., Herrera, S., and Gutiérrez, J. M.: Dangers of using global bioclimatic datasets for ecological niche modeling. Limitations for future climate projections, Global Planet. Change, 107, 1–12, 2013. a
Begert, M., Frei, C., and Abbt, M.: Einführung der Normperiode 1981–2010, Tech. Rep., Fachbericht MeteoSchweiz, 245, MeteoSchweiz, Zurich, 50 pp., 2013. a, b
Bordoy, R. and Burlando, P.: Stochastic downscaling of precipitation to high-resolution scenarios in orographically complex regions: 1. Model evaluation, Water Resour. Res., 50, 540–561, 2014. a, b
Short summary
This study proposes a modification to a stochastic downscaling method for precipitation, RainFARM, to improve the representation of the statistics of the daily precipitation at fine scales (1 km) in mountain areas. This method has been demonstrated in the Alps and it has been found to reconstruct small-scale precipitation distribution. It can be employed in a number of applications, including the analysis of extreme events and their statistics and hydrometeorological hazards.
Final-revised paper