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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.