Many of the questions raised here could be addressed by better collection of reports. At the very least, that would provide a baseline of the occurrence of events. At a deeper level, large datasets of events would be useful for better determining relationships between environments and events. Those could then be used to refine the reanalysis estimates of favorable environments. To that end, the development of the European Severe Weather Database for the entire continent is an important step. Significant tornadoes do occur in Europe (e.g., Wegener, 1917; Fulks, 1967, 1969; Laun, 1969; Dotzek, 2001, 2003), but the reanalysis appears to underestimate them. This underestimate could
Figure 3.8. Same as Figure 3.6, except for a region of equal size encompassing local maxima in severe thunderstorm counts in South America shown in Figure 3.4.
occur for a variety of reasons, including a failure to identify the environments in which they occur, poor representation of important processes such as orographic forcing in the reanalysis, or differences in the efficiency of the atmosphere in taking an environmental condition and producing a storm.
In order to look at climate change effects, climate model simulations must be analyzed. The challenge in such analysis is that there are important differences compared with the reanalysis problem. The reanalysis has observed events to tie itself to reality. A priori, the ability of the models to represent the future distribution is unknown, and relies strongly on successful verification of present-day simulations. In the model world, the verification can be done by simulating the climate of recent decades, and relating derived quantities (analogous to the reanalysis approach) to observed severe convective storm events. This approach further substantiates the need for reliable, homogeneous, long-term severe weather report databases. Only after such verification, analysis of the distribution of environments in (regional) climate model runs for future scenarios can become feasible, even without having particular severe weather events with which to associate them. It is likely that the analysis will require the development of relationships that are unique to the models. If they can be developed, changes in the distributions in climate change scenarios can be evaluated. The models also have the advantage of producing very large samples of environments, in both space and time, from which the distributions can be studied.
Severe thunderstorms and tornadoes will continue to be a threat. Increases in population and wealth mean that larger losses are possible (Brooks and Doswell, 2001a), even without changes in the meteorological events. Thus, awareness of the threats is important. If, however, changes in the distribution of those threats could be identified, additional preparation for them could be carried out.
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