Spatial dependence of extreme rainfall

This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. Th...

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Main Authors:	Noor Fadhilah, Ahmad Radi, Roslinazairimah, Zakaria, Siti Zanariah, Satari, Muhammad Az-Zuhri, Azman
Format:	Conference or Workshop Item
Language:	English
Published:	AIP Publishing 2017
Subjects:	QA Mathematics
Online Access:	http://umpir.ump.edu.my/id/eprint/22310/ http://umpir.ump.edu.my/id/eprint/22310/ http://umpir.ump.edu.my/id/eprint/22310/1/Spatial%20Dependence%20of%20Extreme%20Rainfall.pdf

id	ump-22310
recordtype	eprints
spelling	ump-223102018-10-03T04:53:28Z http://umpir.ump.edu.my/id/eprint/22310/ Spatial dependence of extreme rainfall Noor Fadhilah, Ahmad Radi Roslinazairimah, Zakaria Siti Zanariah, Satari Muhammad Az-Zuhri, Azman QA Mathematics This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC’s value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process AIP Publishing 2017 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/22310/1/Spatial%20Dependence%20of%20Extreme%20Rainfall.pdf Noor Fadhilah, Ahmad Radi and Roslinazairimah, Zakaria and Siti Zanariah, Satari and Muhammad Az-Zuhri, Azman (2017) Spatial dependence of extreme rainfall. In: AIP Conference Proceedings: The 3rd ISM International Statistical Conference 2016 (ISM-III), 9-11 August 2016 , Kuala Lumpur, Malaysia. pp. 1-11., 1842 (020003). ISBN 978-0-7354-1512-6 https://doi.org/10.1063/1.4982833
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA Mathematics
spellingShingle	QA Mathematics Noor Fadhilah, Ahmad Radi Roslinazairimah, Zakaria Siti Zanariah, Satari Muhammad Az-Zuhri, Azman Spatial dependence of extreme rainfall
description	This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC’s value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process
format	Conference or Workshop Item
author	Noor Fadhilah, Ahmad Radi Roslinazairimah, Zakaria Siti Zanariah, Satari Muhammad Az-Zuhri, Azman
author_facet	Noor Fadhilah, Ahmad Radi Roslinazairimah, Zakaria Siti Zanariah, Satari Muhammad Az-Zuhri, Azman
author_sort	Noor Fadhilah, Ahmad Radi
title	Spatial dependence of extreme rainfall
title_short	Spatial dependence of extreme rainfall
title_full	Spatial dependence of extreme rainfall
title_fullStr	Spatial dependence of extreme rainfall
title_full_unstemmed	Spatial dependence of extreme rainfall
title_sort	spatial dependence of extreme rainfall
publisher	AIP Publishing
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/22310/ http://umpir.ump.edu.my/id/eprint/22310/ http://umpir.ump.edu.my/id/eprint/22310/1/Spatial%20Dependence%20of%20Extreme%20Rainfall.pdf
first_indexed	2023-09-18T22:33:08Z
last_indexed	2023-09-18T22:33:08Z
_version_	1777416419410968576

Spatial dependence of extreme rainfall

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