Thermodynamic sensitivities in observed and simulated extreme-rain-producing mesoscale convective systems

Mesoscale convective systems (MCSs) are responsible for a large fraction of warm-season extreme rainfall events over the continental United States, as well as other midlatitude regions globally. The rainfall production in these MCSs is determined by numerous factors, including the large-scale forcing for ascent, the organization of the convection, cloud microphysical processes, and the surrounding thermodynamic and kinematic environment. Furthermore, heavy-rain-producing MCSs are most common at night, which means that well-studied mechanisms for MCS maintenance and organization such as cold pools (gravity currents) are not always at work. In this study, we use numerical model simulations and recent field observations to investigate the sensitivity of low-level MCS structures, and their influences on rainfall, to the details of the thermodynamic environment. In particular, small alterations to the initial conditions in idealized and semi-idealized simulations result in comparatively large precipitation changes, both in terms of the intensity and the spatial distribution. The uncertainties in the thermodynamic enviroments in the model simulations will be compared with high-resolution observations from the Plains Elevated Convection At Night (PECAN) field experiment in 2015. The results have implications for the paradigms of "surface-based" versus "elevated" convection, as well as for the predictability of warm-season convective rainfall.