Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Hydrol. Earth Syst. Sci., 21, 5823-5846, 2017
https://doi.org/10.5194/hess-21-5823-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
24 Nov 2017
Simple scaling of extreme precipitation in North America
Silvia Innocenti1, Alain Mailhot1, and Anne Frigon2 1Centre Eau-Terre-Environnement, INRS, 490 de la Couronne, Québec, G1K 9A9, Canada
2Consortium Ouranos, 550 Sherbrooke Ouest, Montrèal, H3A 1B9, Canada
Abstract. Extreme precipitation is highly variable in space and time. It is therefore important to characterize precipitation intensity distributions on several temporal and spatial scales. This is a key issue in infrastructure design and risk analysis, for which intensity–duration–frequency (IDF) curves are the standard tools used for describing the relationships among extreme rainfall intensities, their frequencies, and their durations. Simple scaling (SS) models, characterizing the relationships among extreme probability distributions at several durations, represent a powerful means for improving IDF estimates. This study tested SS models for approximately 2700 stations in North America. Annual maximum series (AMS) over various duration intervals from 15 min to 7 days were considered. The range of validity, magnitude, and spatial variability of the estimated scaling exponents were investigated. Results provide additional guidance for the influence of both local geographical characteristics, such as topography, and regional climatic features on precipitation scaling. Generalized extreme-value (GEV) distributions based on SS models were also examined. Results demonstrate an improvement of GEV parameter estimates, especially for the shape parameter, when data from different durations were pooled under the SS hypothesis.

Citation: Innocenti, S., Mailhot, A., and Frigon, A.: Simple scaling of extreme precipitation in North America, Hydrol. Earth Syst. Sci., 21, 5823-5846, https://doi.org/10.5194/hess-21-5823-2017, 2017.
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Short summary
The relationship among the extreme rainfall probability distributions and the temporal scales of observation is characterized by the use of scaling models. The validity, the magnitude, and the spatial variability of the estimated scaling laws are evaluated for ~2700 stations in North America. Results demonstrate an improvement of extreme rainfall inference and provide evidence for the influence of both local geographical characteristics and regional climatic features on rainfall scaling.
The relationship among the extreme rainfall probability distributions and the temporal scales of...
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