Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/hess-2017-437
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
07 Sep 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).
Censored rainfall modelling for estimation of fine–scale extremes
David Cross1, Christian Onof1, Hugo Winter2, and Pietro Bernardara2 1Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK
2EDF Energy R&D UK Centre, London SW1E 5JL, UK
Abstract. Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In a warming climate, the moisture holding capacity of the atmosphere is greater which increases the potential for short duration high intensity storm events. In this study, we improve the physical basis for short duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it is emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15 and 60 minute resolutions, and considerations for censor selection discussed.

Citation: Cross, D., Onof, C., Winter, H., and Bernardara, P.: Censored rainfall modelling for estimation of fine–scale extremes, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-437, in review, 2017.
David Cross et al.
David Cross et al.
David Cross et al.

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Short summary
Extreme rainfall is one of the most significant natural hazards. But, estimating very large events is highly uncertain. We present a new approach to construct intense rainfall using the structure of rainfall generation in clouds. The method is particularly effective at estimating short-duration extremes which can be the most damaging. This is expected to have immediate impact for the estimation of very rare downpours with the potential to improve climate resilience and hazard preparedness.
Extreme rainfall is one of the most significant natural hazards. But, estimating very large...
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