Can large scale climate controls help predict seasonal tornado activity?
Brittany L. Perrin, Univ. of Missouri, Columbia, MO; and K. Hughes and A. R. Lupo
The purpose of my research was to examine the influence large-scale climate patterns have on tornado activity in the Midwest United States. Tornado data from 1950 to 2007, taken from NSSL's website, was used to index the number of tornados that occurred yearly between March and June in twelve Midwest states. The trend of increasing tornados, probably artificial, was calculated and removed to find an accurate measure of years with high or low tornado activity. Once this index was created we compared it to moisture transports, moisture convergence, low-to-mid tropospheric vertical wind shear and sea surface temperatures (SSTs), all from the NCEP-NCAR global reanalysis. I was able to use Matlab to analyze the relationships between tornado activity and the large-scale climate datasets. I computed the correlations and the composite mean distributions and mathematically determined their significance.
I have found through my analysis that an increased amount of large-scale vertical wind shear was positively correlated to high tornado activity. I have also found that the transport of moisture on-shore from the Gulf Coast creates moisture convergence over our area of interest in the Midwest, in association with high tornadic activity. This moisture convergence indicates atmospheric instability over the region, one of the main ingredients for severe weather and tornado development. In the future I can relate appropriate indices of the moisture transport and vertical shear to global SST distributions to try to discover potential predictive relationships.
Extended Abstract (592K)
Session 9A, Prediction of climate on seasonal to decadal timescales - II
Wednesday, 14 January 2009, 10:30 AM-12:00 PM, Room 129A
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