Investigations of ABL dynamics and structure over heterogeneous surfaces with turbulence-resolving simulations (LES)

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Traditionally, transport in the atmospheric boundary layer is quantified based on a turbulence theory that relies on the assumption of horizontally homogeneous flow. This allows for a local description through one-dimensional fluxes in the vertical direction. While this assumption may hold for small-scale turbulence near the surface, it is well-known that sub-mesoscale transport processes often constitute a majority of the vertical exchange of energy and matter in the middle of the boundary layer under typical daytime convective conditions. However, experimental data indicate that this distinction is not that clear in reality. Hence, we aim to investigate to what extent sub-mesoscale transport can be neglected in the daytime surface layer (SL), and how the sub-mesoscale transport along the transition towards the mixed layer (ML) can be characterized quantitatively. Large-eddy simulations (LES) will be conducted to investigate how the dispersive fluxes associated with these sub-mesoscale secondary circulations depend on the height above the surface and other atmospheric scaling variables characterizing static stability, and how this height-dependence is influenced by surface heterogeneity. In WP1, a parameterization of the dispersive fluxes is developed based on idealized simulations and scaling analysis and the Buckingham-Pi theorem, which is a common method in boundary-layer meteorology. This parameterization will then be used to correct the measured eddy-covariance fluxes for the otherwise unclosed surface energy balance. Then, in WP2, realistic LES will be carried out for the central LAFO observation period in order to allow for an evaluation with data of the three-dimensional atmospheric motion from Doppler-, Raman- and DIAL lidars. The PALM LES model will be employed with a grid-spacing of less than 4 m covering a domain of at least 10 x 10 km. The mesoscale forcing is provided by WRF simulations. Afterwards, in WP3, the potential of deep learning methods will be explored to model the influence of surface heterogeneity on the generation of dispersive fluxes. During the entire project period, skill development of the doctoral researcher working on this sub-project, and team building within the LAFI research unit community will be promoted as part of WP4.