A New Large Eddy Simulation-based Method for Estimating the Properties of Surface-Driven Convection

Massless Lagrangian particles tracked by a large eddy simulation model have been utilized to characterize coherent structures rooted in an idealized shallow cumulus-topped convective boundary layer.  The unique ability of such tracer particles to record the history of air parcels enables our method to identify convective updrafts without resorting to the use of liquid water as a tracer.  Accordingly, the statistical properties of convective updraft ensembles can be characterized seamlessly from the surface to cloud top, in contrast to Eulerian methods that characterize only the cloudy portion of updrafts.  The statistics estimated by our method include the means, variances, and co-variances of entropy, moisture, and momentum in the ensemble, as well that of air entrained and detrained by the updrafts.  Our method has excellent potential to advance the understanding of surface-driven convection as well as to serve as a test bed for the evaluation of unified parameterizations of turbulence and shallow convection in large-scale weather and climate models.