Abstract
In atmospheric dispersion models driven by meteorological data from numerical weather prediction (NWP) models, it is necessary to include a parameterization for plume spread that is due to unresolved mesoscale motions. These are motions that are not resolved by the input NWP data but are larger in size than the three-dimensional turbulent motions represented by turbulence parameterizations. Neglecting the effect of these quasi-two-dimensional unresolved mesoscale motions has been shown to lead to underprediction of plume spread and overprediction of concentrations within the plume. NWP modeling is conducted at a range of resolutions that resolve different scales of motion. This suggests that any parameterization of unresolved mesoscale motions should depend on the resolution of the input NWP data. Spectral analysis of NWP data and wind observations is used to assess the mesoscale motions unresolved by the NWP model. Appropriate velocity variances and Lagrangian time scales for these motions are found by calculating the missing variance in the energy spectra and analyzing correlation functions. A strong dependence on the resolution of the NWP data is seen, resulting in larger velocity variances and Lagrangian time scales from the lower-resolution models. A parameterization of unresolved mesoscale motions on the basis of the NWP resolution is proposed.
Current affiliation: Theory of Condensed Matter Group, Department of Physics, Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom.
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