Latent Process Modelling of Threshold Exceedances in Hourly Rainfall Series
Paola Bortot and
Carlo Gaetan ()
Additional contact information
Paola Bortot: Università di Bologna
Carlo Gaetan: Università Ca’ Foscari - Venezia
Journal of Agricultural, Biological and Environmental Statistics, 2016, vol. 21, issue 3, No 8, 547 pages
Abstract:
Abstract Two features are often observed in analyses of both daily and hourly rainfall series. One is the tendency for the strength of temporal dependence to decrease when looking at the series above increasing thresholds. The other is the empirical evidence for rainfall extremes to approach independence at high enough levels. To account for these features, Bortot and Gaetan (Scand J Stat 41:606–621, 2014) focus on rainfall exceedances above a fixed high threshold and model their dynamics through a hierarchical approach that allows for changes in the temporal dependence properties when moving further into the right tail. It is found that this modelling procedure performs generally well in analyses of daily rainfalls, but has some inherent theoretical limitations that affect its goodness of fit in the context of hourly data. In order to overcome this drawback, we develop here a modification of the Bortot and Gaetan model derived from a copula-type technique. Application of both model versions to rainfall series recorded in Camborne, England, shows that they provide similar results when studying daily data, but in the analysis of hourly data the modified version is superior.
Keywords: Asymptotic independence; Exceedance; Extreme values; Generalized Pareto distribution; Hourly rainfall; Hierarchical model; Latent process (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://link.springer.com/10.1007/s13253-016-0254-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:jagbes:v:21:y:2016:i:3:d:10.1007_s13253-016-0254-5
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/13253
DOI: 10.1007/s13253-016-0254-5
Access Statistics for this article
Journal of Agricultural, Biological and Environmental Statistics is currently edited by Stephen Buckland
More articles in Journal of Agricultural, Biological and Environmental Statistics from Springer, The International Biometric Society, American Statistical Association
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().