Many severe, forward-propagating MCSs were identified with radar reflectivities during the warm season over the continental U.S. The times and locations at which each storm attains maturity and at which dissipation begins were identified, enabling the computation of several relevant indices (e.g. precipitable water, temperature lapse-rates, CAPE, shear-vector magnitudes) in the MCS’s near environment using 20 km RAP analysis data. Non-parametric statistical inferences were performed to identify which indices have the greatest skill for discriminating between mature MCSs and dissipating storms.
Results show that the layer-lifting CAPE (CAPEll), which is an inflow-weighted mean CAPE, is the best discriminator between mature and dissipating MCSs. The second best discriminator is a layer-lifting measure of the dilution of deep convective buoyancy, followed and the vertically integrated CAPE (ICAPE), which measures the potential for latent heating within the atmospheric column. These results lend weight to the importance of layer-lifting convective instability for the maintenance of severe MCSs. Furthermore, CAPEll maintains its discriminatory skill if Corfidi-vectors are used to estimate the movement of MCSs, providing an index that can be useful for forecasting the dissipation of MCSs.