One of the more critical issues in a changing climate is the
behavior of extreme weather events, such as severe tornadic storms as seen
recently in Moore and El Reno, Oklahoma. It is generally thought that such
events would increase under a changing climate. How to evaluate this extreme
behavior is a topic currently under much debate and investigation. One approach
is to look at the behavior of large scale indicators of severe weather. The use
of the generalized extreme value distribution for annual maxima is explored for
a combination product of convective available potential energy and wind shear.
Results from this initial study show successful modeling and high quantile
prediction using extreme value methods. Predicted large scale values are
consistent across different extreme value modeling frameworks, and a general
increase over time in predicted values is indicated. A case study utilizing
this methodology considers the large scale atmospheric indicators for the
region of Moore, Oklahoma for Class EF5 tornadoes on May 3, 1999 and more
recently on May 20, 2013, and for the class EF5 storm in El Reno, Oklahoma on May
31, 2013.
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