Boundary-Layer Meteorology最新文献

This study investigates the parameterization of the geostrophic drag law (GDL) for conventionally neutral atmospheric boundary layers (CNBLs). Utilizing large eddy simulations, we confirm that in CNBLs capped by a potential temperature inversion, the boundary-layer height scales as (u_*/sqrt{N f}), where (u_*) represents the friction velocity, N the free-atmosphere Brunt–Väisälä frequency, and f the Coriolis parameter. Additionally, we confirm that the wind gradients normalized by the Brunt–Väisälä frequency have universal profiles above the surface layer. Leveraging these physical insights, we derived analytical expressions for the GDL coefficients A and B, correcting the earlier form of Zilitinkevich and Esau (Q J R Meteorol Soc 131:1863–1892, 2005). These expressions for A and B have been validated numerically, ensuring their accuracy in representing the geostrophic drag coefficient (u_*/G) (G is the geostrophic wind speed) and the cross-isobaric angle. This work extends the range for which the GDL has been validated up to (u_*/G =[0.019, 0.047]). This further supports the application of GDL to CNBLs over a broader range of (u_*/G), which is useful for meteorological applications such as wind energy.

Zero plane displacement height ((d_0)) and momentum roughness length ((z_{0m})), describe the aerodynamic characteristics of a vegetated surface. Usually, (d_0) and (z_{0m}) are assumed to be constant functions of the physical characteristics of the surface. Prior evidence collected from the literature and our examination of flux tower data show that (d_0) and (z_{0m}) vary in time at sites with tree and shrub canopies, but not grasslands. The conventional explanations of these variations are based on linear functions of wind velocity and friction velocity, with little theoretical basis. This study explains the variation in aerodynamic parameters by matching four analytical canopy velocity models to a logarithmic above-canopy velocity profile at canopy height. (d_0) and (z_{0m}) come out as functions of 2 non-dimensional terms, the canopy momentum absorption capacity (parameter) and a (measurable) Péclet number. To test the theories of variation, we analysed the velocity profiles from Ozflux and Ameriflux sites. None of the theories could recreate (d_0) and (z_{0m}) at half-hourly intervals. However, the canopy velocity models were able better to recreate the distribution of the variations in (d_0) and (z_{0m}). Additionally, the estimates of canopy momentum absorption capacity varied consistently with phenological changes in the canopies, whereas, the fitting parameters of the linear regression of using wind speed and friction velocity did not exhibit physically interpretable variations. The canopy velocity models may offer better predictions with an accurate estimation of the canopy height, a horizontally homogeneous and rigid canopy, and incorporation of the roughness sublayer.

Near-surface similarities and atmospheric turbulence characteristics have a large impact on numerical weather prediction models. However, the validity of these similarities is unclear during precipitation. This study investigates the modulations in atmospheric boundary layer turbulence and the variations of the near-surface scaling similarities caused by rainfall. Here we present our field observations on the effects of rainfall on the near-surface similarities and atmospheric turbulence in the stable boundary layer using a Parsivel² disdrometer and a 3D ultrasonic anemometer at our outdoor rainfall laboratory in San Antonio, Texas, USA. During moderate to heavy rainfall conditions, higher turbulent energy was observed than those in non-rainy conditions when the turbulence intensity and the wind speeds were relatively low. On the contrary, when the turbulence intensity and the wind speeds were relatively high, the turbulence energy in the stable boundary layer were dampened due to the raindrops. Raindrops with high particle Reynolds numbers ((Re_{p} = D_{m} v_{t} /vartheta); (D_{m})—mean volume diameter, ({v}_{t})—terminal raindrop fall speed, and (vartheta)—kinematic viscosity of the surrounding air) can act as either a source or a sink of turbulent kinetic energy depending on the turbulence intensity of the atmosphere. Our field observations showed that near-surface similarities deviated from the scaled similarities under the influence of rainfall. The normalized standard deviations of the streamwise and vertical velocity components and the dissipation rate were higher during rainy than non-rainy times. Rainfall effects on turbulence modulations and near-surface scaling parameters of the stable boundary layer are discussed with considerations of the relevant mechanisms.

In this study, we present an extension to the Monin–Obukov similarity theory (MOST) for the roughness sublayer (RSL) over short vegetation. We test our theory using temperature measurements from fiber optic cables in an array-shaped set-up. This provides a high vertical measurement resolution that enables us to measure the sharp temperature gradients near the surface. It is well-known that MOST is invalid in the RSL as the flow is distorted by roughness elements. However, to derive the surface temperature, it is common practice to extrapolate the logarithmic profiles down to the surface through the RSL. Instead of logarithmic behaviour defined by MOST near the surface, our observations show near-linear temperature profiles. This log-to-linear transition is described over an aerodynamically smooth surface by the Van Driest equation in classical turbulence literature. Here we propose that the Van Driest equation can also be used to describe this transition over a rough surface, by replacing the viscous length scale with a surface length scale (L_s) that represents the size of the smallest eddies near the grass structures. We show that (L_s) scales with the geometry of the vegetation and that the model shows the potential to be scaled up to tall canopies. The adapted Van Driest model outperforms the roughness length concept in describing the temperature profiles near the surface and predicting the surface temperature.

In this study, a systematic mathematical analysis has been presented for the extent of applicability of various non-linear similarity functions for momentum (({{upvarphi }}_{{text{m}}})) and heat (({{upvarphi }}_{{text{h}}})) under stable conditions to compute surface turbulent fluxes in numerical models. The investigation is carried out for equal and unequal momentum (({{text{z}}}_{0})) and heat (({{text{z}}}_{{text{h}}})) roughness lengths. The study reveals that ({{upvarphi }}_{{text{m}}}) and ({{upvarphi }}_{{text{h}}}) utilized in the National Centre for Atmospheric Research Community Atmosphere Model version 5 (NCAR-CAM5) (Holtslag et al. in Mon Weather Rev 118:1561–1575, 1990) have several restrictions on their applicability in moderately to strongly stable cases. If the ratios of ({{text{z}}}_{0}) and ({{text{z}}}_{{text{h}}}) to the height (({text{z}})) from the surface (i.e., (frac{{{text{z}}}_{0}}{{text{z}}}) and (frac{{{text{z}}}_{{text{h}}}}{{text{z}}})) lie in the range ((0.2, 1)), the functions are valid for a limited range of (upzeta ) (stability parameter) in strong stable conditions (left(upzeta >1right)); however, when (frac{{{text{z}}}_{0}}{{text{z}}}le 0.2) and (frac{{{text{z}}}_{{text{h}}}}{{text{z}}}le 0.2), the validity of functions is unrestricted. In terms of bulk Richardson number (left({{text{Ri}}}_{{text{B}}}right)), the functions are valid for a limited range of moderately to strongly stable conditions. These theoretically derived upper limits have also been validated using observations from the UK Meteorological Office’s Cardington and Cooperative Atmosphere-Surface Exchange Study-99 datasets. On the other hand, similarity functions based on Cheng and Brutsaert (Boundary-Layer Meteorol 114:519–538, 2005), Grachev et al. (Boundary-Layer Meteorol 124:315–333, 2007), Srivastava et al. (Meteorol Appl 27, 2020), and Gryanik et al. (J Atmos Sci 77:2687–2716, 2020) are found to be theoretically valid for all values of (upzeta ) and ({{text{Ri}}}_{{text{B}}}). The efforts have also been made to implement these functions in the Weather Research and Forecasting as well as global scale models.

Large-eddy simulations are used to evaluate mean profile similarity in the convective boundary layer (CBL). Particular care is taken regarding the grid sensitivity of the profiles and the mitigation of inertial oscillations in the simulation spin-up. The nondimensional gradients (phi ) for wind speed and air temperature generally align with Monin–Obukhov similarity across cases but have a steeper slope than predicted within each profile. The same trend has been noted in several other recent studies. The Businger-Dyer relations are modified here with an exponential cutoff term to account for the decay in (phi ) to first-order approximation, yielding improved similarity from approximately 0.05(z_i) to above 0.3(z_i), where (z_i) is the CBL depth. The necessity for the exponential correction is attributed to an extended transition from surface scaling to zero gradient in the mixed layer, where the departure from Monin–Obukhov similarity may be negligible at the surface but becomes substantial well below the conventional surface layer height of 0.1(z_i).

The backdrop for this study is a knowledge gap about how turbulence anisotropy relates to the dissimilar transport of momentum and scalars. We use single-level measurements of turbulence over an alpine glacier for exploring the dissimilar transport of momentum, heat, and moisture in stably stratified katabatic flows. Our study is motivated by the need of addressing their flux dissimilarity from a fresh perspective of anisotropic motions of turbulence. Its objective is to promote new understanding of boundary-layer turbulence anisotropy as one possible factor in dissimilar behaviours between momentum and scalar transport over a sloping terrain. Specifically, the momentum–heat flux correlation (({R}_{{F}_{uT}})) and the heat–moisture flux correlation (({R}_{{F}_{Tq}})) coefficients vary across three different bulk states of kinetic anisotropy. Those states, identified using the barycentric Lumley map, suggest the predominance of two-component turbulence (being axisymmetric or not) and miscellaneous turbulence (whose topological shape is less salient). Miscellaneous turbulence typically bears a higher degree of the flux similarity between momentum and heat (i.e., ({R}_{{F}_{uT}}) > 0.6) but a lower degree of that between heat and moisture (i.e., (left|{R}_{{F}_{Tq}}right|) < 0.7). The multi-resolution decomposition technique is then applied to identify larger-scale eddies of two-component topology, intermediate-scale eddies of oblate topology, and smaller-scale eddies of isotropic topology. Further analysis shows that an explicit change in eddy scale-wise topology is correlated not only with variations in ({R}_{{F}_{uT}}) and (left|{R}_{{F}_{Tq}}right|) but with the dissimilar transport of momentum and scalars, so explaining a deviation from the Reynolds and the Lewis analogies in fluid mechanics.

Studies on the shortwave spectrum, namely short-gravity, gravity-capillary, and parasitic-capillary waves, reveal that spectrum representation may modify the estimate of momentum transport at the air-sea interface. However, in numerical simulations, the shortwave spectra are usually approximated by simplified formulations. The effect of three shortwave spectrum formulations on the momentum balance at the air-sea interface was quantitatively evaluated for light to high wind speeds and fully developed seas. In the simulations, the spectra considered were: (i) obtained by an extrapolated function, (ii) dependent on the wave age derived from the observations, and (iii) from the solution of the energy balance equation. Considering computational time, the second was the fastest. while the first and third the computational time increased, respectively, by approximately 2–7% and 15–30%, depending on the wind speed. Concerning the observations, the mean square slope, the coupling parameter, and the drag coefficient, the second and third formulations showed better agreement, while the first one showed a large discrepancy. The results highlighted the importance of shortwave formulations in the analysis of the interaction between wind and wave.

In the last decades the energy-balance-closure problem has been thoroughly investigated from different angles, resulting in approaches to reduce but not completely close the surface energy balance gap. Energy transport through secondary circulations has been identified as a major cause of the remaining energy imbalance, as it is not captured by eddy covariance measurements and can only be measured additionally with great effort. Several models have already been developed to close the energy balance gap that account for factors affecting the magnitude of the energy transport by secondary circulations. However, to our knowledge, there is currently no model that accounts for thermal surface heterogeneity and that can predict the transport of both sensible and latent energy. Using a machine-learning approach, we developed a new model of energy transport by secondary circulations based on a large data set of idealized large-eddy simulations covering a wide range of unstable atmospheric conditions and surface-heterogeneity scales. In this paper, we present the development of the model and show first results of the application on more realistic LES data and field measurements from the CHEESEHEAD19 project to get an impression of the performance of the model and how the application can be implemented on field measurements. A strength of the model is that it can be applied without additional measurements and, thus, can retroactively be applied to other eddy covariance measurements to model energy transport through secondary circulations. Our work provides a promising mechanistic energy balance closure approach to 30-min flux measurements.

The present paper shows that local similarity theories, proposed for the strongly-stratified boundary layers, can be derived as invariant solutions defined under the Lie-group theory. A system truncated to the mean momentum and buoyancy equations is considered for this purpose. The study further suggests how similarity functions for the mean profiles are determined from the vertical fluxes, with a potential dependence on a measure of the anisotropy of the system. A time scale that is likely to characterize the transiency of a system is also identified as a non-dimensionalization factor.