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On the emergence of rainfall extremes from ordinary events
Author(s) -
Zorzetto E.,
Botter G.,
Marani M.
Publication year - 2016
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2016gl069445
Subject(s) - extreme value theory , quantile , event (particle physics) , rare events , limiting , econometrics , statistical physics , mathematics , statistics , physics , astrophysics , mechanical engineering , engineering
The analysis and estimation of extreme event occurrences is a central problem in many fields of geoscience. Advancements in the study of extreme events have recently been limited, arguably in connection with asymptotic assumptions in the traditional extreme value theory (EVT) and with its focusing on a small fraction of the available observations representing the tail properties of the underlying event generation process. Here we develop a Metastatistical Extreme Value framework (MEV) which relaxes limiting assumptions at the basis of the traditional EVT and accounts for the full distribution of the underlying “ordinary” events. We apply this general approach to the relevant case of daily rainfall and find that the MEV approach reduces the uncertainty in the estimation of high‐quantile extremes by up to 50% with respect to the classical EVT. The improved predictive power of the MEV framework is connected with its recognizing that extremes emerge from repeated sampling of ordinary events, thereby being able to use all available observations.