The Madden-Julian Oscillation (MJO) is the leading mode of tropical intraseasonal variability and has known links to modification of extratropical patterns. Spatial and temporal scale differences between the MJO and US tornadoes makes connecting the two difficult, but using tornado outbreaks (TO) that are typically synoptically evident helps close this gap. An assessment of TO probability was conducted for each of the eight Realtime Multivariate MJO index phases for each month. In addition, clusters of TOs were used to identify how the MJO’s extratropical response influences patterns that lead to outbreaks in the US. It was found, and in part, consistent with previous research, that the shifts in the jet stream and wave breaking over the Pacific that occur in response to the current location of the MJO convection and circulation anomalies contribute to changes in the mid-latitude flow that can produce TOs in the central and eastern US.

A better understanding of the performance in precision of physical parameterizations in NWP models is necessary for improving forecasts of tornadic outbreaks. For this study, WRF simulations of tornadic outbreaks were run using configurations of three microphysics, three convective physics, and two PBL physics schemes. Each configuration was subjected to ten iterations of SKEBS. The means of the ten perturbation members of each parameterization configuration were bootstrapped for SB CAPE, SB CIN, and 0-3km SRH to find 95% confidence interval widths at each grid point. Maps of these spreads provided a spatial analysis of the uncertainty. Analyses on correlations and clusters were performed to determine how the configurations related spatially and in magnitude. These uncertainties were further bootstrapped to compare the mean of each configuration in boxplots. The effect on the uncertainty produced by each configuration varied according to the diagnostic variable being analyzed.

Tornado outbreaks (TO) occur every year across the continental United States and are a result of various synoptic scale, mesoscale, and climatological patterns. This study looks to find what patterns exist among the various scales and how that relates to the climatology of the TOs. In order to find these patterns, principal component analysis (PCA) and a cluster analysis were conducted to differentiate the patterns of data. Four distinct clusters of TOs were found with varying synoptic and mesoscale patterns as well as distinct climatological patterns. An interesting result from this study includes the shifting of TO characteristics over time to a more synoptically forced pattern that has becoming stronger and shifted eastward from the Great Plains.