Modelling Extreme Rain Accumulation with an Application to the 2011 Lake Champlain Flood

Autor: Johanna Nešlehová, Christian Genest, Jonathan Jalbert, Orla A. Murphy
Rok vydání: 2019
Předmět:
Zdroj: Journal of the Royal Statistical Society Series C: Applied Statistics. 68:831-858
ISSN: 1467-9876
0035-9254
DOI: 10.1111/rssc.12342
Popis: Summary A simple strategy is proposed to model total accumulation in non-overlapping clusters of extreme values from a stationary series of daily precipitation. Assuming that each cluster contains at least one value above a high threshold, the cluster sum S is expressed as the ratio S = M/P of the cluster maximum M and a random scaling factor P ∈ (0, 1]. The joint distribution for the pair (M, P) is then specified by coupling marginal distributions for M and P with a copula. Although the excess distribution of M is well approximated by a generalized Pareto distribution, it is argued that, conditionally on P < 1, a scaled beta distribution may already be sufficiently rich to capture the behaviour of P. An appropriate copula for the pair (M, P) can also be selected by standard rank-based techniques. This approach is used to analyse rainfall data from Burlington, Vermont, and to estimate the return period of the spring 2011 precipitation accumulation which was a key factor in that year's devastating flood in the Richelieu Valley Basin in Québec, Canada.
Databáze: OpenAIRE
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