Simulation of radiatively driven mixing in a smoke cloud using "one-dimensional turbulence"

Large-eddy simulations (LESs) are known to significantly overestimate entrainment in cloud-topped boundary layers, negatively impacting predictions on cloud mass and cover. This overestimation stems from coarse model resolutions that lead to numerical broadening of the entrainment layer. While it has been shown in direct numerical simulations (DNSs) that down-to-centimetre-scale resolutions can mitigate this issue, such high resolutions are not viable for most applications in the atmospheric sciences. The one-dimensional turbulence model (ODT), introduced by Kerstein [1], offers a computationally efficient alternative that provides full-scale resolution along a 1-D vertical domain. Molecular diffusion is explicitly resolved, while turbulent advection is modelled through a stochastically sampled sequence of spatial mappings, known as eddy events. Physically plausible eddy events are selected based on their current kinetic and potential energy. This allows an accurate representation of local turbulence properties and their dynamical complexity by evolving instantaneous property profiles. This study applies ODT to investigate cloud-top turbulent mixing processes driven by radiative cooling in a smoke cloud, benchmarking the results against DNS. Building on the preliminary findings by Meiselbach [2], we demonstrate improvements in mean profiles and turbulent fluxes of buoyancy and smoke concentration, showing ODT's ability to reproduce salient features observed in DNSs. In addition, we explore convective boundary layer scalings at extended Reynolds and Richardson numbers beyond those accessible in DNS studies.
 

References:
[1] A. R. Kerstein, Journal of Fluid Mechanics 392, 277334 (1999).
[2] F. T. Meiselbach, Application of ODT to Turbulent Flow Problems, doctoral thesis, BTU Cottbus-Senftenberg (2015).