Using soil moisture and variability with respect to ENSO as a predictor for spring convective events within the State of Missouri, USA

Previous studies demonstrated that increased soil moisture can affect the water vapor in the overlaying atmospheric boundary layer (ABL). This can increase the surface buoyancy which can be more conducive for the occurrence of severe weather. This research will demonstrate that soil moisture can be an indicator for increased tornado, large hail, and severe wind activity within the state of Missouri for the period from 1980-2018. Then, using data obtained from the Storm Prediction Center in Norman, OK, the April-June soil moisture anomalies were used to determine if there is a correlation to severe weather occurrence during those months. The correlation of soil moisture anomalies for the months of January-March and September through February before the April-June severe weather season was examined next. These experiments will use the Pearson correlation coefficient and a Poisson regression to test for significance. Only significant results from the Pearson correlation method will be shown for brevity. Then, synoptic maps, in conjunction with the ENSO phenomena, were examined to understand what other mechanisms were contributing to the increase/decrease in storm reports within the state. A spectral analysis using Fourier transforms was conducted to examine the interannual variability of severe weather occurrence with respect to soil moisture. Results showed a significant positive relationship between April-June soil moisture with April-June tornado and severe wind activity. Fewer significant positive and negative relationships were found relating the January-March soil moisture with April-June severe weather reports. However, no statistical significance was found between September-February soil moisture and the ensuing April-June severe weather reports. Most of the statistically significant correlations were noted in south central Missouri. Some variability was observed with ENSO years and tornado activity, indicating that the synoptic setup may play more of a role than soil moisture. La Nina was also found to produce a greater number of tornadic systems, while El Nino produces more potent systems.

Automated summary

Previous studies have shown that increased soil moisture can affect atmospheric boundary layer (ABL) water vapor, resulting in a higher surface buoyancy and more severe weather. This research aims to demonstrate the correlation between soil moisture and tornado, hail, and severe wind activity in Missouri from 1980-2018. Data from the Storm Prediction Center in Norman, OK was used to analyze the relationship between April-June soil moisture anomalies and severe weather occurrence. Pearson correlation coefficient and Poisson regression were used for significance testing. Results showed a significant positive relationship between April-June soil moisture and tornado and severe wind activity.