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Revising Return Periods for Record Events in a Climate Event Attribution Context
Author(s) -
Philippe Naveau,
Aurélien Ribes,
Francis W. Zwiers,
Alexis Hannart,
Alexandre Tuel,
Pascal Yiou
Publication year - 2018
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/jcli-d-16-0752.1
Subject(s) - attribution , counterfactual thinking , context (archaeology) , event (particle physics) , econometrics , computer science , extreme value theory , inference , climate model , rare events , variable (mathematics) , climate change , statistical hypothesis testing , statistical inference , sample (material) , climatology , statistics , geography , psychology , mathematics , artificial intelligence , social psychology , ecology , physics , chemistry , archaeology , chromatography , quantum mechanics , geology , biology , mathematical analysis
Both climate and statistical models play an essential role in the process of demonstrating that the distribution of some atmospheric variable has changed over time and in establishing the most likely causes for the detected change. One statistical difficulty in the research field of Detection and Attribution resides in defining events that can be easily compared and accurately inferred from reasonable sample sizes. As many impacts studies focus on extreme events, the inference of small probabilities and the computation of their associated uncertainties quickly become challenging. In the particular context of event attribution, we address the question of how to compare records between the so-called world as “it might have been been without anthropogenic forcings” and the “world that is”. Records are often the most important events in terms of impact and get much media attention. We will show how to efficiently estimate the ratio of two small probability of records. The inferential gain is particula...

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