Improving Community Risk Management

Abstract

Extreme and catastrophic events are notoriously challenging to learn from, prepare for, and protect against. They are rare and unfamiliar – the bigger the loss, the less frequent and familiar catastrophes of that magnitude tend to be. This makes them hard to envision and plan for adequately in our daily lives. They are often inherently unpredictable, in that past data does not enable credible early warnings of the approximate time, place, or magnitude of the next occurrence. This unpredictability arises even under ideal conditions, with unrestricted access to all past data and computational power and modeling expertise to analyze it, largely because causes cannot always be discerned in advance. Seemingly trivial events sometimes precipitate large consequences, such as massive avalanches, forest fires, power blackouts, stock market slides, epidemics, or wars, even though they usually do not (Mandelbrot 1964). Several examples are discussed shortly.