Boundary-Layer Meteorology最新文献

The closure of the surface energy balance (SEB) in complex terrain remains a persistent challenge. We present a multi-site analysis based on the i-Box network in the Inn Valley, Austria, to characterize the SEB residual (Res) normalized by net radiation (Rn) across different conditions. Diurnal cycles of Res/Rn and turbulent fluxes show a significant residual, positive (i.e., an energy gain) during the day and negative (i.e., an energy loss) during the night. Large Res/Rn is observed during nighttime stable conditions, and minimum values are found under convective mixing. Annual cycles show a distinct pattern for most of the sites, with warmer months displaying the smallest Res/Rn during daytime and largest values during nighttime, while colder months are associated with the opposite behaviour. The study examines the influence of atmospheric stability, turbulent mixing and flow conditions on Res/Rn. Results reveal that unstable conditions, associated with higher vertical mixing, tend to reduce the magnitude of Res/Rn. In contrast, stable conditions are linked to larger residuals. Especially for certain stations, foehn events and valley wind days introduce additional variability. Our findings thus point out not only the need to account for atmospheric stability, turbulence structure, and flow regimes, but also the site-specific response of Res/Rn to the above conditions which highlights the importance of collecting spatially distributed complex terrain observations.

Most single-column, Gaussian dispersion-model algorithms exclusively consider the time-averaged Reynolds shear stress contribution to the friction velocity, neglecting any dispersive stress component inherently present from the lateral spatial averaging of the model. This work examines the impact of incorporating dispersive stresses when calculating the friction velocity used for dispersion parameterizations in idealized uniform and nonuniform urban areas. This is accomplished through wind tunnel-validated, neutrally-stratified Large Eddy Simulations (LES) at incoming wind flow angles of 0°, 10°, 30°, and 50°. Comparisons are made to the existing formulations in AERMOD, the EPA's preferred Gaussian dispersion model. Given the issues with Gaussian models in complex environments, results are focused above the urban canopy, where the vertical shear stress from Reynolds and dispersive components are used to estimate a friction velocity to fit the log law velocity profile with surface roughness and displacement height. An urban model with rows of uniform buildings was found to feature negligible dispersive components to the friction velocity outside of any city blocks within a transition region where the dispersive shear stress was opposite in sign to the Reynolds stress. A second urban model containing nonuniform buildings featured meaningful dispersive stresses for nearly all city blocks and flow angles. The friction velocity and fitted surface roughness for all blocks of both models were compared to existing reduced order models used to predict urban friction velocity. The method used in AERMOD relies on a convective-like boundary layer assumption and has poor agreement with our results, whereas a simple power law expression reproduces all our data within 9.6% if the height at which the velocity matches from both the upwind to the urban wind profiles is known. Finally, the inclusion of dispersive shear stress in the friction velocity is reflected in the prediction of pollutant concentrations in the AERMOD formulations, leading to a +20.6% and +21.2% increase in predicted concentrations within the first row for the uniform and nonuniform cases, respectively, but otherwise a +0.4% and -15.6% change for all other rows. Future work could incorporate these effects in conjunction with the physical presence of buildings to improve the predictive power of Gaussian models in urban areas.

Background: The SAGIT^® instrument has been developed for acromegaly to assist clinicians in staging the disease accurately, assessing the response to therapy, and adjusting the treatment. We aimed to evaluate the preoperative utility of the SAGIT^® instrument and to discover a cut-off value for predicting the surgery outcome and long-term prognosis of patients with acromegaly.

Methods: A total of 832 patients with acromegaly were identified from the medical record system. Acromegaly diagnosis was confirmed by elevated IGF-1 levels according to the age-adjusted upper limit of normal, lack of suppression of GH concentration to <0.4 µg/L following a 75 g oral glucose tolerance test, and the existence of a pituitary adenoma demonstrated by MRI. The SAGIT^® instrument comprises five key components of acromegaly: signs and symptoms (S), associated comorbidities (A), GH levels (G), IGF-1 levels (I), and the features of the tumor (T). The initial postoperative remission was evaluated 3 months after surgery.

Results: A final cohort of 132 patients has been included in our study. Median preoperative SAGIT scores were significantly different (10.00 [9.00-11.00] to 11.00 [10.00-13.00], [P=0.002]) between patients who achieved initial remission at 3 months and those who were not in remission. The threshold SAGIT score distinguishing between initial remission and nonremission groups was 10 with an AUC of 0.660 (P<0.001).

Conclusions: In our retrospective cohort study, the findings suggested that the SAGIT^® instrument may be a beneficial preoperative tool to predict the initial remission postoperatively and long-term prognosis of the patients with acromegaly.

Urban forms characterised by multi-scale roughness can drastically modify the wind structure within cities affecting both pedestrian comfort and air quality at street level. For simplicity, most urban flow studies focus on cuboid buildings with a single length scale. We consider six forms to assess how additional length scales impact urban flow: two reference cuboids that differ in aspect ratio (mean building height to width) cases (Standard, 1; Tall, 3) plus two additional fractal iterations of each. The six models have the same mean building width, height, and frontal area but their length scale characteristics differ. These are used in wind tunnel experiments within a deep turbulent boundary layer. The length scale differences are found to affect the drag force exerted by the buildings in a non-negligible way (up to 5 and 13% for Standard and Tall buildings, respectively). The added length scales also modify the wake lateral spread and intensity of the turbulence fluctuations, with smaller the length scales having the lower (higher) intensity of fluctuations in the near (far) wake. Additionally, the strength of the vortex shedding emanating from the buildings is reduced by introducing systematically smaller length scales. This work suggests that omission of additional length scales can lead to inaccuracies in drag and wake recovery estimations. The reduction in intensity of vortex shedding found with each fractal iteration could have engineering applications (e.g. reducing vibration).

Dispersion within idealized urban environments was studied in a simulated neutrally buoyant, 1:200 scale boundary layer with the Meteorological Wind Tunnel at the EPA's Fluid Modeling Facility. The measurements are used to offer a baseline of performance for the mechanical turbulence formulation and concentration predictions of AERMOD, the EPA's preferred Gaussian dispersion model. Scaled meteorological conditions and dispersion characteristics were studied for both uniform and nonuniform building arrays oriented at 0° and 30° with respect to the flow and were compared to baseline, "rural", measurements without the presence of buildings. Particle image velocimetry (PIV) measured velocity and shear stress profiles within each model configuration, whereas hydrocarbon analyzers (HCAs) measured ethane concentrations at defined points throughout the model. Four source locations were examined for each building array, with two in the urban core and two in a street canyon, each with a source within and above the building canopy. Experimental profiles, regardless of their shape, were fitted to Gaussian profiles to determine lateral and vertical plume spread and shift from the wind tunnel centerline. These parameters were compared against a no-building reference case. Concentration predictions using the formulations in AERMOD are computed for 3 variations of modeled velocity profiles for each source, using factor of 2 ( $FAC2$ ) and fractional bias ( $FB$ ) as the governing model evaluation parameters. The two urban configurations were found to decrease the $FAC2$ performance by 34.1% and 30.1% from the no-building reference for the uniform and nonuniform cases, respectively, while producing modeled concentrations of only 48.1% and 62.4% of the 10 highest observed concentrations. These results encouraged simple first-order corrections to improve model performance with an emphasis on predicting maximum concentrations for regulatory purposes. These corrections proved successful for the uniform cases, mitigating $FB$ , and improving the $FAC2$ percentage by 11.4% with more mixed results in nonuniform configurations, highlighting the difficulty in applying uniformly derived parameterizations in realistic, nonuniform environments.

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.