Footprint model development and validation for homogeneous and inhomogeneous terrain using high resolution large eddy simulation

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Footprint models determine the spatial context of a measurement by defining a transfer function between sources or sinks of the signal and the sensor position. The resulting source area is an important quality assessment tool, e.g. to assess the influence of disturbing terrain elements o the data. Although micrometeorological research focuses increasingly on complex terrain, footprint models developed to data are restricted to idealized cases of horizontally homogeneous flow conditions, and thus cannot consider the impact of inhomogenity. The project focuses developing and validating methods to compute footprints above thermally and aerodynamically inhomogeneous surfaces. The first approach to do so is to use massively parallel computers to run a high-resolution large eddy simulation (LES) model that allows the explicit resolution of the turbulent transport processes. In a second method requiring less computational resources, both forward and backward Lagrangian stochastic (LS) algorithms will be modified to account for horizontally heterogeneous flow conditions. The LES datasets will be used both to derive the flow statistics required to run the LS models, and to evaluate their produced source areas. The reliability of the footprint results of both LES model and LS algorithms will finally be validated with data from field experiments.