Thursday, 14 January 2016: 1:30 PM
Room 245 ( New Orleans Ernest N. Morial Convention Center)
Recently, there has been increased interest in the ability to forecast severe weather events on a seasonal scale. Being able to forecast events such as the April 2011 tornado outbreak could have beneficial impacts such as increased preparedness at the Federal and local level as well as greater public awareness. To better forecast tornadoes on a seasonal scale, we must first look at the underlying factors that influence the inter-annual variability of both tornado locations and intensity. Soil moisture has been shown, on regional scales, to have an effect on moisture within the boundary layer, and therefore, it has the potential to impact deep convection. Previous studies have examined relationships between factors related to soil moisture such as precipitation and evapotranspiration and their effects on tornado climatology at the local and regional scale. This study examined the relationship between antecedent soil moisture and tornado activity in five regions within the United States east of the Rocky Mountains, using two approaches. The first approach used fall and winter soil moisture anomalies as a predictor for spring tornado activity. The second looked at the six months preceding each month in the year. Statistically significant correlations between tornado days and soil moisture anomalies were found in the Northern Plains, the Southeast and Oklahoma, indicating that regionally, soil moisture may have an effect on seasonal tornado activity. In addition, we also assessed the reliability of our modeled soil moisture dataset by comparing it to the high-resolution Oklahoma Mesonet observational network. It was found that the Climate Prediction Center's soil moisture dataset was significantly correlated at a 95% confidence level or greater, in each grid box, where there was Mesonet data available for comparison. This suggests that the soil moisture dataset used for our analysis models reality well.
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