Some disasters and crises are related to each other by more than just the common negative social value we assign to them. For example, earthquakes, homicide surges, magnetic storms, and the U.S. economic recession are all kindred of a sort, according to a theoretical framework presented in the journal Chaos, which is published by the American Institute of Physics.
The researchers who developed this framework contend that these four types of events share a precursory development pattern -- a specific change of scale in indicators that can be tracked. They suggest that detecting this pattern could improve crisis prediction.
"Knowing the patterns of extreme events development is pivotal both for predictive understanding of these events and for enhancing disaster preparedness," says investigator Vladimir Keilis-Borok of the University of California, Los Angeles.
Adds his colleague Alexander Soloviev of the Russian Academy of Sciences: "A premonitory pattern common to four complex systems of different nature is probably a manifestation of a certain general feature of complex systems."
To mathematicians who probe complexity, extreme events grow out of the dynamic interplay of indicators representing a complex process. A system may give off signals that deep shift is afoot. A change of scaling is a "premonitory pattern" indicating a coming extreme event. This manifests as a shift in pattern -- large events that were once infrequent begin to occur closer and closer together (similar to the way that the tempo of "Jaws" soundtrack increases in anticipation of a shark attack).
That systems as diverse as an earthquake, surge in homicides, economic recession and magnetic storm can share a developmental pattern is not as surprising as it may at first seem. Systems are deep as well as dynamic: shift happens -- and can, to a large extent, be predicted to save and improve lives.
- Keilis-Borok et al. Variations of trends of indicators describing complex systems: Change of scaling precursory to extreme events. Chaos An Interdisciplinary Journal of Nonlinear Science, 2010; 20 (3): 033104 DOI: 10.1063/1.3463438
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