Garthwaite, Andrew P. and Ramesh, N. I. ORCID: 0000-0001-6373-2557 (2018) Parsimonious modelling of winter season rainfall incorporating reanalysis climatological data. Hydrology Research, 49 (6). pp. 2030-2045. ISSN 0029-1277 (doi:https://doi.org/10.2166/nh.2018.012)

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Abstract

Several Markov Modulated Poisson Process (MMPP) models are developed to describe winter season rainfall with parsimonious parameter use. We propose a methodology for determining the best form of seasonal model for fine-scale rainfall within a MMPP framework. Of those proposed here, a model with a fixed transition rate is shown to be superior over the other MMPP models considered. The model is expanded to include covariate data for sea-level air pressure, relative humidity, and temperature using reanalysis data over 14 years from the coordinates covering the Bracknell rainfall collection site in England. Results are compared using the likelihood ratio test and the second-order properties of aggregated rainfall.

Item Type:	Article
Additional Information:	© 2018 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY-NC-ND 4.0), which permits copying and redistribution for non-commercial purposes with no derivatives, provided the original work is properly cited (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Uncontrolled Keywords:	bucket-tip, covariates, Cox model, fine-scale modelling, seasonal rainfall
Subjects:	Q Science > QA Mathematics
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science
Last Modified:	04 Mar 2022 13:06
URI:	http://gala.gre.ac.uk/id/eprint/20883

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