Extreme events: dynamics, statistics and prediction

TLDR

The paper reviews extreme events, their causes and consequences, as part of a three‑year European‑American research project. It surveys theoretical time‑series and extreme‑value methods, deterministic continuous and discrete dynamic models, and applies them to climatic, seismic and socio‑economic events and their prediction. Key findings show that spectral analysis gains from jointly considering continuous and discrete power spectrum components, and that coupled natural‑socio‑economic modeling is essential, both enhancing hazard study and prediction. Abstract.

Abstract

Abstract. We 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.