Extraction of nite-time coherent sets in 3D Rayleigh-BenardConvection using the dynamic LaplacianGARY FROYLAND, University ofNew South Wales, ANNA KLUENKER, KATHRIN PADBERG-GEHLE, CHRISTIANE SCHNEIDE, Leuphana University, JOERG SCHUMACHER, TechnicalUniversity Ilmenau | Turbulent convection ows in nature are often organized inregular large-scale patterns, which evolve slowly relative to to the typical convectivetimescale, and are arranged on spatial scales that are much larger than the layerheight. Prominent examples are cloud streets in the atmosphere and granulationpatterns in solar convection. This order in a fully developed turbulent ow is some-times called turbulent superstructure in convection. Large-scale structure formationin turbulent Rayleigh-Benard convection recently became accessible in direct numerical simulations, which resolve all relevant scales of turbulence in horizontally extended domains with a large aspect ratio. Using DNS output we apply the dynamicLaplacian approach [Froyland, 2015] to identify these turbulent superstructures as nite-time coherent sets in both quasi-2D and fully three-dimensional settings. Amodest number of trajectories are meshed and a nite-element based method isemployed to numerically estimate the dynamic Laplacian [Froyland Junge, 2018].The coherent sets are encoded in the leading eigenvectors of the dynamic Laplacian,and the individual coherent sets are \decoded" using the recently developed SparseEigenbasis Approximation (SEBA) algorithm [Froyland, Rock, Sakellariou, 2019]