Battle of extreme value distributions: A global survey on extreme daily rainfall

By Simon Michael Papalexiou, Demetris Koutsoyiannis. 2013

424 citations recorded by the source corpus.

Subfields: Finance, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/61211a0059c7dea6ff7bc151c889187d8860f1e8

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Citations in the corpus

Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes? (2015, neutral): “…( k , 0) (Adamowski et al. 1996; Alila 1999), which is consistent with analyses of global precipitation records that recommend excluding the reversed Weibull form of the GEV distribution and constraining k 2 f 2 0 : 5, 0 g during parameter estimation (Papalexiou and Koutsoyiannis 2013).”
Bayesian estimation of rainfall intensity-duration-frequency relationships (2015, background): “For example, Papalexiou and Koutsoyiannis (2013) have analysed the annual maximum daily rainfall of more than 15,000 records from all over the world, and came to the conclusion that c is expected to belong in a narrow range, approximately from 0 to 0.23.”
Generalized extreme value shape parameter and its nature for extreme precipitation using long time series and the Bayesian approach (2016, methodology): “Only those stations with a minimum of 99 complete years of measurements were chosen in order to meet the requirement (a) by Papalexiou and Koutsoyiannis (2013).”
Intensity–duration–frequency (IDF) rainfall curves in Senegal (2017, background): “, 2015) but also all around the world (e.g., Koutsoyiannis, 2004b; Papalexiou and Koutsoyiannis, 2013).”
Automated threshold selection for extreme value analysis via ordered goodness-of-fit tests with adjustment for false discovery rate (2018, background): “, Papalexiou and Koutsoyiannis (2013), Serinaldi and Kilsby (2014)] finds that the right tail for daily rainfall is better described by heavy tail distributions than exponential types. Following the study of Roth, Jongbloed and Buishand (2016), data is generated from a distribution characterized by ”
Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database (2016, background): “As discussed in section 3.3 below, values of the shape parameter n on the order of 0.1–0.2 are representative for rainfall applications [see also Koutsoyiannis, 2004b; Deidda and Puliga, 2006; Deidda, 2007, 2010; Papalexiou and Koutsoyiannis, 2013; Serinaldi and Kilsby, 2014].”
Non-stationary extreme value analysis in a changing climate (2014, background): “The extreme value theory for stationary random sequences has been extensively studied (Papalexiou and Koutsoyiannis 2013).”
Upper tail dependence in rainfall extremes: would we know it if we saw it? (2015, background): “As for an example, Papalexiou and Koutsoyiannis (2013) and Serinaldi and Kilsby (2014b) highlighted the concealing effect of the (short) record length on the recognition of the nature of the univariate tails of rainfall extremes.”
Bayesian hierarchical modeling of extreme hourly precipitation in Norway (2013, background): “Papalexiou & Koutsoyiannis (2013) studied annual maximum daily rainfall of 15 137 records from all over the world, and declared the Fréchet distribution (ξ > 0) to be “the winner”.”
Stochastic generation of multi-site daily precipitation focusing on extreme events (2018, background): “Indeed, local assessments of precipitation extremes are often inconclusive due to insufficient information on the distribution tails (Papalexiou and Koutsoyiannis, 2013).”