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A doubly stochastic rainfall model with exponentially decaying pulses

A doubly stochastic rainfall model with exponentially decaying pulses

Ramesh, N. I., Garthwaite, A and Onof, C. (2017) A doubly stochastic rainfall model with exponentially decaying pulses. Stochastic Environmental Research and Risk Assessment, 32 (6). pp. 1645-1664. ISSN 1436-3240 (Print), 1436-3259 (Online) (doi:https://doi.org/10.1007/s00477-017-1483-z)

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Abstract

We develop a doubly stochastic point process model with exponentially decaying pulses to describe the statistical properties of the rainfall intensity process. Mathematical formulation of the point process model is described along with second-order moment characteristics of the rainfall depth and aggregated processes. The derived second-order properties of the accumulated rainfall at different aggregation levels are used in model assessment. A data analysis using 15 years of sub-hourly rainfall data from England is presented. Models with fixed and variable pulse lifetime are explored. The performance of the model is compared with that of a doubly stochastic rectangular pulse model. The proposed model fits most of the empirical rainfall properties well at sub-hourly, hourly and daily aggregation levels.

Item Type: Article
Additional Information: © The Author(s) 2017. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Uncontrolled Keywords: Doubly stochastic, Point process, Rainfall intensity, Exponential pulse, Accumulated rainfall
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Department of Mathematical Sciences
Last Modified: 15 Apr 2019 15:55
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: GREAT a
Selected for GREAT 2019: GREAT 1
URI: http://gala.gre.ac.uk/id/eprint/18018

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