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A detailed analysis of the predictability of observed Monin–Obukhov (MO) similarity within the near-ground region of near-neutral to moderately convective atmospheric boundary layers (ABL) from large-eddy simulation (LES) fields is reported in this work. High-resolution LES predictions of means, variances, budgets of turbulent kinetic energy and temperature variance, and the velocity and temperature spectra from three ABL states (−zi/L=0.44, 3 and 8) are analysed under MO scaling. The resolution in the near-ground region is increased by using ‘nested meshes.’ For the close-to-neutral case (−zi/L=0.44) the relative roles of grid resolution and subgrid-scale scale (SGS) parameterization on the predictability of MO-similarity are also studied. The simulated temperature field is found to satisfy the MO hypothesis and agree well with observations. The simulated velocity field, on the other hand, shows significant departures. Except for the horizontal variance, MO scales are the appropriate normalizing scales for the near-ground-layer statistics. However, the LES suggest that the boundary layer depth zi has an ‘indirect’ influence on all near-ground-layer variables except temperature, and the LES-predicted MO-scaled variables exhibit a functional dependence on both z/L and z/zi. The simulated two-dimensional spectra of velocity and temperature fluctuations, however, suggest that while large scales deviate from MO-similarity, inertial subrange scales are MO-similar. Discrepancies with field observations raise important questions of the non-dimensional depth z/zi over which MO-similarity holds for a particular variable. Surface-layer field studies generally do not document zi. It is also not clear to what extent these discrepancies are due to approximations made in LES. Measurements are needed designed specifically for comparing with LES predictions.

A recent study of convective boundary layer characteristics performed with large eddy simulation technique (LES) has demonstrated unexpected influence of the depth of the boundary layer on surface layer characteristics. The present study tests some of the predictions from these simulations with field measurements from a summertime experiment in Sweden, which includes in addition to regular surface layer data also airborne measurements and numerous radio soundings, which enable accurate determination of boundary layer depth. It is found that the measurements strongly support most of the conclusions draws from the LES study and give additional information over a wider stability range. Thus, the normalized wind gradient m is found to depend on both z/L, where z is height above the ground and L is the Monin-Obukhov length, and z i /L, where z i is the height of the convective boundary layer. This additional dependence on z i /L explains much of the scatter between experiments encountered for this parameter. In the case of the normalized temperature gradient h , the experimental data follow the generally accepted functional relation with z/L, but with an additional, slight ordering according to z i /L. Analyses of nondimensional variances show (i) the horizontal velocity variance scales on mixed layer variables and is a function only of z i /L, in agreement with the LES results and with previous measurements; (ii) the normalized vertical velocity variance depends on the large-scale pressure gradient length scale for slight instability and is primarily a function of z /L for moderate and strong instability; (iii) the normalized temperature variance is a function of z/L, with a possible slight dependence on z i /L; and (iv) whereas mean temperature gradient is characterized by local shear scales, temperature variances are normalized by local buoyancy-driven scales.

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Abstract. Large-eddy simulation (LES) provides three-dimensional, time-dependent fields of turbulent refractivity in the atmospheric boundary layer on spatial scales down to a few tens of meters. These fields are directly applicable to the computation of electromagnetic (EM) wave propagation in the megahertz range but not in the gigahertz range. We present an approximate technique for extending LES refractivity fields to the smaller scales needed for calculating EM propagation at gigahertz frequencies. We demonstrate the technique by computing refractivity fields through 128 3 LES, extending them to smaller scales in two dimensions, and using them in a parabolic equation EM propagation model. At 0.263 GHz the very small scale structure in the extended fields has a negligible effect on the predicted EM levels. At 2 GHz, however, it increases the predicted levels by 15-25 dB. We relate these results to the refractivity structure sampled by EM waves at 0.263 and 2 GHz. We also show that at long range an EM field calculated through an LES-based refractivity field is generally less coherent and significantly weaker than one computed from a "plywood" (i.e., stratified, range-independent) model of the small-scale refractivity field. We give a physical explanation for the differences in the EM fields computed in these two ways. Finally, although the plywood model gives results that fit the EM levels observed in the recent Variability of Coastal Atmospheric Refractivity (VOCAR) experiment, it is not physically realistic. The instantaneous top of the atmospheric boundary layer is known to be sharp and horizontally varying, and we show that using such a top also yields a fit to the VOCAR data. IntroductionThe research discussed here is an interdisciplinary effort between boundary-layer meteorologists and physicists working in electromagnetic (EM) propagation. The purpose of the collaboration was to use large-eddy simulation (LES) methods and a parabolic equation ( Large-Eddy SimulationTurbulence is characterized by three-dimensional, stochastic motions (eddies) of a wide range of spatial scales. These motions generate corresponding stochastic structure in advected scalars such as refractive index. The largest eddies in the turbulent atmospheric boundary layer scale with the integral scale, which is of the order of the boundary-layer depth zi (-1 km). The smallest eddies scale with the Kolmogorov microscale, which is typically of the order of 1 mm. A direct numerical solution of the governing equations for such a turbulent flow is far beyond the present or expected capabilities of computers. 1413

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