Abstract
The statistical theory of extreme values is applied to daily minimum and maximum temperature time series in the U.S. Midwest and Southeast. If the spatial pattern in the frequency of extreme temperature events can be explained simply by shifts in location and scale parameters (e.g., the mean and standard deviation) of the underlying temperature distribution, then the area under consideration could be termed a “region.” A regional analysis of temperature extremes suggests that the Type I extreme value distribution is a satisfactory model for extreme high temperatures. On the other hand, the Type III extreme value distribution (possibly with common shape parameter) is often a better model for extreme low temperatures. Hence, our concept of a region is appropriate when considering maximum temperature extremes, and perhaps also for minimum temperature extremes.
Based on this regional analysis, if a temporal climate change were analogous to a spatial relocation, then it would be possible to anticipate how the frequency of extreme temperature events might change. Moreover, if the Type III extreme value distribution were assumed instead of the more common Type I, then the sensitivity of the frequency of extremes to changes in the location and scale parameters would be greater.
