Extreme events: dynamics, statistics and prediction
Author(s) -
Michael Ghil,
Pascal Yiou,
Stéphane Hallegatte,
Bruce D. Malamud,
Philippe Naveau,
Alexander Soloviev,
Petra Friederichs,
V. I. KeilisBorok,
Dmitri Kondrashov,
V. G. Kossobokov,
Olivier Mestre,
C. Nicolis,
Henning W. Rust,
П. Н. Шебалин,
Mathieu Vrac,
A. Witt,
Ilya Zaliapin
Publication year - 2011
Publication title -
nonlinear processes in geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.604
H-Index - 61
eISSN - 1607-7946
pISSN - 1023-5809
DOI - 10.5194/npg-18-295-2011
Subject(s) - extreme value theory , complementarity (molecular biology) , econometrics , series (stratigraphy) , computer science , time series , statistical physics , statistics , mathematics , geology , machine learning , physics , genetics , biology , paleontology
International audienceWe review work on extreme events, their causes and consequences, by a group of European and American researchers involved in a three-year project on these topics. The review covers theoretical aspects of time series analysis and of extreme value theory, as well as of the deterministic modeling of extreme events, via continuous and discrete dynamic models. The applications include climatic, seismic and socio-economic events, along with their prediction. Two important results refer to (i) the complementarity of spectral analysis of a time series in terms of the continuous and the discrete part of its power spectrum; and (ii) the need for coupled modeling of natural and socio-economic systems. Both these results have implications for the study and prediction of natural hazards and their human impacts
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