Do severe storms across Australia, Europe and the United States share similarities? A comparison of atmospheric profiles and environmental predictors

It is well known that atmospheric environments across Australia, Europe and the United States are conducive to the occurrence of convective storms resulting in significant tornadoes, giant hail and damaging winds. However, while many studies have focused on evaluating convective environments over specific regions, only a limited number of elaborations compared different parts of the world. Therefore, in this work we use severe weather reports, ground lightning detection data and ERA5 reanalysis over the last 20 years to address the following research question: do severe storms across Australia, Europe and the United States share environmental similarities? A comparison of composite vertical profiles of temperature, moisture and wind highlighted several consistent features that are common for specific hazards among all three continents. For example, near-ground relative humidity and storm-relative helicity are important for tornadoes while buoyancy in below freezing temperatures and weak near-ground winds are important for large hail. Low-level moisture flux turned out to be the best discriminator between tornadoes and large hail events. However, despite these similarities, statistical analysis indicated that a predictive value for some ingredients can be markedly different among continents. A prime reason for that are different underlying climatological conditions. For example, a strong low-level wind shear combined with sufficient buoyancy is rare over Europe and Australia but when it occurs, it is often associated with tornado reports. On the other hand, a strong low-level wind shear is common over the United States, but is not always associated with proper convective organization to produce a tornado. For this reason, we believe that developing environmental models intended to work universally across the entire world can be extremely difficult as it is challenging to disentangle signals that are associated with physical processes from those that result from a local climatology.