Advanced societies have become quite proficient at defending against moderate-size earthquakes, hurricanes, floods, or other natural assaults. What still pose a significant threat, however, are the unknowns, the extremes, the natural phenomena encompassed by the upper tail of the probability distribution. Alongside the large or powerful events, truly extreme natural disasters are those that tie different systems together: an earthquake that causes a tsunami, which leads to flooding, which takes down a nuclear reactor. In the geophysical monograph Extreme Events and Natural Hazards: The Complexity Perspective, editors A. Surjalal Sharma, Armin Bunde, Vijay P. Dimro, and Daniel N. Baker present a lens through which such multidisciplinary phenomena can be understood. In this interview, Eos talks to Sharma about complexity science, predicting extreme events and natural hazards, and the push for “big data.”
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