Vertical wind shear and convective storms

Convective storms develop in both strong and weak vertical wind shear but long-lived, well organised convection requires strong vertical wind shear. Studies have shown that the relative frequency of occurrence of convective hazards such as large hail, severe wind gusts and tornadoes increases with increasing vertical wind shear. A particularly strong connection exists between shear and large hail, most pronounced for very large hailstones (≥ 5 cm), which form exclusively in supercells. Likewise, severe wind gusts become more likely with increasing vertical wind shear and with stronger mean flow in the lower troposphere. Tornadoes become more probable with increasing streamwise vorticity and storm-relative helicity near the ground. Excessive rainfall shows the weakest connection to the vertical wind shear. Deep-layer shear, typically measured over a 0–6 km layer, is often used to forecast the most likely convective archetypes (single cells, multicells, linear convection or supercells) in a given situation. Wind shear  measured from the surface up to 3 and 1 km AGL are useful for forecasting convective wind and tornado threats, respectively. For tornadoes, 0–1 km storm-relative helicity, which depends not only on speed shear but also on directional shear, is a better predictor for tornadoes than the 0–1 km bulk shear. Numerous composite parameters that incorporate measures of vertical wind shear have been developed. The most robust of those is the product of CAPE (or its square root) and shear, that discriminates well between severe and non-severe convective storms and is one of the ECMWF’s Extreme Forecast Index parameters. Hodographs are an important tool for assessing vertical wind shear in different layers. Long, curved hodographs in the lower troposphere represent environments with high values of storm relative helicity conducive to supercells. Recent and ongoing research use environmental parameters, including measures of wind shear, as predictors in statistical models and neural networks to provide probabilistic forecasts of convective hazards. Interestingly, severe weather often happens along the edges of areas with favorable conditions. Another topic of research is the effect of wind shear on the dynamics and physics of storms, including hail growth and the development of damaging gusts, which is being studied intensively using convection-allowing models. Furthermore, recent studies into the predictability of convective storms as a function of wind shear conclude that the evolution and intensity of storms are least predictable when wind shear is weak.