of weather-related events; examples of such decisions include the ratings of catastrophe bonds or weather derivatives; calculations that statisticians use to adjust data for seasonal effects; and public and private decisions made in agriculture, insurance, reinsurance, health (e.g., disease), fire control, and ecosystem management. Many of the decisions are based on statistical calculations that are appropriate for stationary climates. One well-known example is the widespread use of “30-year normals” in deriving climate data for individual locations.

On the whole, these assumptions are reasonable, if imperfect, rules of thumb to use when the variability of weather is small and climate is stationary. If some parameter related to climate, such as runoff, follows normal distributions with known and constant means and standard deviations, businesses and governments can reasonably use current practices. However, in light of recent findings related to nonstationary and often highly skewed climate-related variables, current practices can be misleading and result in costly errors. An event that is estimated to be a “500-year flood” or a “500-year fire” can be found to occur every 100 or 50 or 20 years if the averages and the variabilities are significantly misestimated.

The potential for abrupt climate change and the existence of thresholds for its effects require revisions of our statistical estimates and practices. We have not attempted to compile a list of all the places where society estimates or uses the assumption of a stationary and stable climate; such an effort would be enormous, and lies outside the committee charge. Rather, we believe that the time is ripe to examine this issue, develop improved methods, and develop improved estimates of the likelihood of extreme events.


Recommendation 5. Research should be undertaken to identify “no-regrets” measures to reduce vulnerabilities and increase adaptive capacity at little or no cost. No-regrets measures may include low-cost steps to: slow climate change; improve climate forecasting; slow biodiversity loss; improve water, land, and air quality; and develop institutions that are more robust to major disruptions. Technological changes may increase the adaptability and resiliency of market and ecological systems faced by the prospect of damaging abrupt climate change. Research is particularly needed to assist poor countries, which lack both scientific resources and economic

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