continental-level phenomena that are only beginning to be appreciated and understood. Climate change has moved the physical Earth system into conditions that are unprecedented in recorded history, and we do not understand the complexities of the relationships among the elements of the system well enough to make skillful forecasts of specific events. It is therefore prudent to expect that the likelihoods of such events occurring will increase in the coming decade in most places and that the rate of change will continue subsequently to increase. Models are an increasingly powerful tool for examining the likelihood of changes in means, extremes, and variability of climate.

It makes sense for the intelligence community to apply a scenario approach in thinking about potentially disruptive events that are expectable but not truly predictable. For example, available climate models sometimes disagree about the direction of a climate trend even when the fundamental science strongly suggests that change is likely. In such situations it may make sense to consider the security implications of two or more plausible trends as a way to anticipate risks. It will also be valuable for the intelligence community to have improved forecasting ability for subcontinental climate events and for event clusters and sequences. An improved monitoring of factors that might provide early warning of potentially disruptive events would also be valuable. We discuss monitoring issues in Chapter 6.

Recommendation 3.1: The intelligence community should participate in a whole-of-government effort to inform choices about adapting to and reducing vulnerability to climate change. It should, along with appropriate federal science agencies, support research to improve the ability to quantify the likelihoods of potentially disruptive climate events, that is, single extreme climate events, event clusters, and event sequences. A special focus should be on quantifying risks of events and event clusters that could disrupt vital supply chains, such as for food grains or fuels, and thus contribute to global system shocks.

This research should include efforts by climate scientists to improve fundamental understanding of the effects of climate change on the likelihoods of extreme climate events and also efforts to apply the methods of extreme value statistics to these problems, particularly the problem of estimating the likelihoods of clusters of extreme climate events that are dependent on the same underlying climatic processes. Having improved likelihood estimates for single and clustered extreme climate events would help in defining climate event scenarios for countries, regions, and systems that could be used as the basis for the climate stress tests that we discuss in Chapter 6.

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