PNNL

Abstract

Entrainment of surrounding cooler and drier air into convective updrafts is one of the key processes that influences deep convection initiation and growth. Numerous studies have investigated entrainment effects for isolated convective clouds in idealized simulations, but their role in realistic conditions with many interacting convective clouds remains uncertain. We examine the effects of entrainment on the depth reached by convective clouds in realistic LES simulations over central Argentina during the Cloud, Aerosol, and Complex Terrain Interactions field campaign. Cloudy updrafts and their associated properties are assigned to convective cells tracked with radar reflectivity signatures. Several thousand convective cells are tracked over two high CAPE and two low CAPE cases that support cells of varying depths and intensities. Entrainment is calculated explicitly as the fluxes of air into the outer surface of each cloudy updraft. Single predictor logistic regression models are used to determine the relative importance of updraft, near-updraft, and ambient atmospheric conditions in predicting whether convective cells become deep. We then build a multiple predictor regression model pairing key updraft and meteorological metrics with fractional entrainment rate. The probability of cells transitioning to deep convection is most sensitive to ambient 600-hPa relative humidity (42% of total metric contribution to cloud depth predictability), followed by low-level CAPE (28%), cloud-base updraft width (19%), and fractional entrainment (11%). Thus, the initial state of the updraft and available potential energy and its buoyancy dilution as it deepens through the mid troposphere collectively determine whether deep convection will result from shallower clouds.