being written, could affect world corn or wheat prices in ways that make essential foods unaffordable for populations in Africa or Asia. Another example of a global system shock would be constraints on the availability of humanitarian aid for a country because aid providers are responding to situations elsewhere in the world. Yet another would be a climate event that altered the distribution of a major pathogen affecting people or staple crops. These examples, which are discussed in greater detail in Chapter 4, indicate that there are numerous ways in which climate events could create shocks to integrated global social, economic, health, or technological systems and thus have effects far removed geographically from where the events occur.

SURPRISES ARISING FROM POORLY RESOLVED CLIMATE DYNAMICS

Many extreme events, such as hurricanes, tornadoes, other severe storms, floods, heat waves, and wild fires, occur on the time-scale of days to about two weeks. A key question for climate research is how such extreme events will change within a warming climate. With such warming the statistics of weather are no longer stationary, and the linkage between weather and climate emerges as a research priority. Today’s climate change models are generally considered to provide an adequate representation of the large-scale secular trend in climate. However, gaining a better insight into how climate change will affect extreme weather requires that high-resolution numerical weather prediction models (and their inherent fast physics, such as cloud–radiation–precipitation interactions) be run in climate mode. This presents a major computational and resource challenge and has been the reason for the call for a seamless approach to weather and climate forecasting (World Climate Research Programme, 2009). Such a unified approach was first implemented by the U.K. Met Office in 1993. In the United States the National Centers for Environmental Prediction of the National Oceanic and Atmospheric Administration developed the Coupled Forecast System (CFS) in 2004 as a lower-resolution climate version of its Global Forecast System, a weather forecast system for short-term seasonal climate prediction. However, this system has yet to be run on decadal to centennial time-scales in response to GHG forcing. Hence the behavior of extreme events in a non-stationary climate cannot be fully described and projected until climate change models are run with the spatial resolution and physical processes of numerical weather prediction models. Until that time, extreme climate surprises should be expected to be more the rule than the exception.



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