Abstract
Abstract. Large-eddy simulation (LES) and Lagrangian stochastic modeling of passive particle dispersion were applied to the scalar flux footprint determination in the stable atmospheric boundary layer. The sensitivity of the LES results to the spatial resolution and to the parameterizations of small-scale turbulence was investigated. It was shown that the resolved and partially resolved (“subfilter-scale”) eddies are mainly responsible for particle dispersion in LES, implying that substantial improvement may be achieved by using recovering of small-scale velocity fluctuations. In LES with the explicit filtering, this recovering consists of the application of the known inverse filter operator. The footprint functions obtained in LES were compared with the functions calculated with the use of first-order single-particle Lagrangian stochastic models (LSMs) and zeroth-order Lagrangian stochastic models – the random displacement models (RDMs). According to the presented LES, the source area and footprints in the stable boundary layer can be substantially more extended than those predicted by the modern LSMs.
Highlights
Micrometeorological measurements of vertical turbulent scalar fluxes in the atmospheric boundary layer (ABL) are usually carried out at altitudes zM ≥ 1.5 m due to technological limitations of the eddy covariance method
A similar approach was recently applied by Michalek et al (2013) in Large-eddy simulation (LES) with an approximate deconvolution subgrid model (ADM; see Stolz et al, 2001), which can be considered as the model with explicit filtering
Scalar dispersion and flux footprint functions within the stable atmospheric boundary layer were studied by means of LES and stochastic particle dispersion modeling
Summary
Micrometeorological measurements of vertical turbulent scalar fluxes in the atmospheric boundary layer (ABL) are usually carried out at altitudes zM ≥ 1.5 m due to technological limitations of the eddy covariance method. The measurement results are often attributed to the exchange of heat, moisture and gases at the surface. This procedure is not justified for inhomogeneous surfaces because of a large area contributing to the flux, and because of variability of the second moments with height. The relationship between the surface flux Fs(x, y, 0) and the flux Fs(xM , yM , zM ), measured in point xM = (xM , yM , zM ), can be formalized via the footprint function fs: Fs(xM , yM , zM ) = ∞∞. In the ABL the surface area contributing to the flux is elongated in the wind direction; the crosswind-integrated footprint function fsy defined as
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