期刊
EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS
卷 225, 期 3, 页码 471-487出版社
SPRINGER HEIDELBERG
DOI: 10.1140/epjst/e2015-50233-y
关键词
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资金
- Humboldt University / IRI THESys fellowship
- Stordalen Foundation (via the Planetary Boundary Research Network PB.net)
- Earth League's EarthDoc program
- German Federal Ministry for Education and Research (BMBF) [01LN1306A]
- Evangelisches Studienwerk Villigst
- German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety [11-II-093-Global-A SIDS and LDCs]
Studying event time series is a powerful approach for analyzing the dynamics of complex dynamical systems in many fields of science. In this paper, we describe the method of event coincidence analysis to provide a framework for quantifying the strength, directionality and time lag of statistical interrelationships between event series. Event coincidence analysis allows to formulate and test null hypotheses on the origin of the observed interrelationships including tests based on Poisson processes or, more generally, stochastic point processes with a prescribed inter-event time distribution and other higher-order properties. Applying the framework to country-level observational data yields evidence that flood events have acted as triggers of epidemic outbreaks globally since the 1950s. Facing projected future changes in the statistics of climatic extreme events, statistical techniques such as event coincidence analysis will be relevant for investigating the impacts of anthropogenic climate change on human societies and ecosystems worldwide.
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