Abstract
The development of improved subgrid-scale (SGS) models for large-eddy simulation of scalar transport in the atmospheric boundary layer requires an improved understanding of basic properties of the SGS fluxes. High frequency atmospheric wind speed and temperature data sampled at a height of 1.7 m are used to measure SGS heat fluxes and dissipation of temperature variance, by means of one-dimensional filtering and invoking Taylor's hypothesis. Conditional averaging is used to isolate interesting features of the SGS signals, and to relate them to the large-scale characteristics of the flow, such as the presence of coherent structures. Both mean and conditionally averaged SGS quantities are compared with those obtained using a standard eddy-diffusivity model. Within the limitations imposed by the one-dimensional data analysis, we observe that the model appears unable to reproduce important features of the real signals, such as the negative dissipation of temperature variance associated with strong negative resolved temperature gradients due to the ejection of warm air under unstable atmospheric stability conditions.
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