Unstable Atmospheric Stability Research Articles

Perbandingan Stabilitas Atmosfer di Permukaan Manifestasi Panas Bumi dengan Tanpa Manifestasi Panas Bumi menggunakan Bilangan Richardson

The stability of the atmosphere can affect the weather conditions in an area. This study aims to compare atmospheric stability carried out in Lake Linow which has two surfaces, namely the surface of geothermal manifestation and the surface without geothermal manifestation. In determining the stability of the atmosphere, researchers use the Richardson number method. To determine atmospheric stability using the Richardson number, data on wind speed and temperature at each altitude are needed. The measured height is 2 meters and 4 meters from the surface. The results of this study show that on the surface geothermal manifestations have unstable atmospheric stability with Richardson numbers -1.4729 to -0.1420, while on the surface without geothermal manifestations have 3 states of atmospheric stability, namely: stable, neutral, and unstable, with Richardson numbers -1.1316 to 0.9808. Therefore, it can be concluded that the state of the atmosphere on the surface of geothermal manifestations is more unstable, compared to surfaces without geothermal manifestations.

On the Retrieval of Surface-Layer Parameters from Lidar Wind-Profile Measurements

We revisit two recent methodologies based on Monin–Obukhov Similarity Theory (MOST), the 2D method and Hybrid-Wind (HW), which are aimed at estimation of the Obukhov length, friction velocity and kinematic heat flux within the surface layer. Both methods use wind-speed profile measurements only and their comparative performance requires assessment. Synthetic and observational data are used for their quantitative assessment. We also present a procedure to generate synthetic noise-corrupted wind profiles based on estimation of the probability density functions for MOST-related variables (e.g., friction velocity) and the statistics of the noise-corrupting perturbational amplitude found during an 82-day IJmuiden observational campaign. In the observational part of the study, 2D and HW parameter retrievals from floating Doppler wind lidar measurements are compared against those from a reference mast. Overall, the 2D algorithm outperformed the HW in the estimation of all the three parameters above. For instance, when assessing the friction-velocity retrieval performance with reference to sonic anemometers, determination coefficients of ρ2D2=0.77 and ρHW2=0.33 were found under unstable atmospheric stability conditions, and ρ2D2=0.81 and ρHW2=0.07 under stable conditions, which suggests the 2D algorithm as a prominent method for estimating the above-mentioned surface-layer parameters.

In situ particle sampling relationships to surface and turbulent fluxes using large eddy simulations with Lagrangian particles

Abstract. Source functions for mechanically driven coarse-mode sea spray and dust aerosol particles span orders of magnitude owing to a combination of physical sensitivity in the system and large measurement uncertainty. Outside special idealized settings (such as wind tunnels), aerosol particle fluxes are largely inferred from a host of methods, including local eddy correlation, gradient methods, and dry deposition methods. In all of these methods, it is difficult to relate point measurements from towers, ships, or aircraft to a general representative flux of aerosol particles. This difficulty is from the particles' inhomogeneous distribution due to multiple spatiotemporal scales of an evolving marine environment. We hypothesize that the current representation of a point in situ measurement of sea spray or dust particles is a likely contributor to the unrealistic range of flux and concentration outcomes in the literature. This paper aims to help the interpretation of field data: we conduct a series of high-resolution, cloud-free large eddy simulations (LESs) with Lagrangian particles to better understand the temporal evolution and volumetric variability of coarse- to giant-mode marine aerosol particles and their relationship to turbulent transport. The study begins by describing the Lagrangian LES model framework and simulates flux measurements that were made using numerical analogs to field practices such as the eddy covariance method. Using these methods, turbulent flux sampling is quantified based on key features such as coherent structures within the marine atmospheric boundary layer (MABL) and aerosol particle size. We show that for an unstable atmospheric stability, the MABL exhibits large coherent eddy structures, and as a consequence, the flux measurement outcome becomes strongly tied to spatial length scales and relative sampling of crosswise and streamwise sampling. For example, through the use of ogive curves, a given sampling duration of a fixed numerical sampling instrument is found to capture 80 % of the aerosol flux given a sampling rate of zf/w∗∼ 0.2, whereas a spanwise moving instrument results in a 95 % capture. These coherent structures and other canonical features contribute to the lack of convergence to the true aerosol vertical flux at any height. As expected, sampling all of the flow features results in a statistically robust flux signal. Analysis of a neutral boundary layer configuration results in a lower predictive range due to weak or no vertical roll structures compared to the unstable boundary layer setting. Finally, we take the results of each approach and compare their surface flux variability: a baseline metric used in regional and global aerosol models.

Effects of atmospheric stability on the structural response of a 12 MW semisubmersible floating wind turbine

AbstractGlobal dynamic response models used for the design of wind turbines are largely based on neutral stability, which is not representative of real atmospheric conditions. Offshore wind farms, for example, have been seen to experience predominantly unstable conditions, especially at lower wind speeds. In the current work, we use four wind generation models under stable, neutral and unstable atmospheric stability conditions to study the low‐frequency content of the global responses of a semisubmersible floating wind turbine (FWT). To represent the wind fields, we use the Kaimal Spectrum and Exponential Coherence Model (Kaimal), the Mann Spectral Tensor Model (Mann), a point measurement based model (TIMESR) and large‐eddy simulation (LES). At the low‐frequency range, both atmospheric stability and the turbulence wind model significantly affect the response of the FWT. In all the cases studied throughout this paper, the structural response under unstable conditions is higher than under stable or neutral conditions. The TIMESR and the Kaimal models fitted to the FINO‐1 offshore meteorological mast measurements show more similar responses than the Mann model; surge and pitch are higher for the TIMESR and Kaimal models, and yaw is lower. When fitted to LES, TIMESR and Kaimal predict surge and pitch responses closer to LES, but they underestimate the responses related to yaw, opposite to what the Mann model does. The responses are directly related to turbulence intensity and coherence, which are affected by atmospheric stability. Therefore, based on the analyses carried out through this study, the structural analysis of FWT should account for the effect of atmospheric stability.

Vertical profiles of O3, NO2 and PM in a major fine chemical industry park in the Yangtze River Delta of China detected by a sensor package on an unmanned aerial vehicle

The vertical profiles and diurnal variations of air pollutants at different heights in the fine chemical industry park (FCIP) were systematically studied in this study. Air pollutants in a major FCIP in the Yangtze River Delta of China within 500 m above ground level (AGL) detected by a sensor package on an unmanned aerial vehicle (UAV). The air pollutants including ozone (O3), nitrogen dioxide (NO2), particulate matter (PM), total volatile organic compounds (TVOCs) and carbon monoxide (CO), respectively, had been measured through more than one hundred times of vertical flights from Aug. 2020 to Jul. 2021. The concentrations of NO2 and CO generally decreased with the height while the concentrations of O3 increased with the height within 500 m AGL. The photochemical reaction resulted in a strong inverse relationship between the vertical profiles of O3 and that of NO2. The concentrations of PM2.5 and TVOCs generally decreased with the height below 100 m AGL and were fully mixed above 100 m AGL. The vertical profiles of different particle sizes were well consistent with the R2 value of 0.97 between PM1 and PM2.5 and 0.93 between PM2.5 and PM10. The NO2 and PM2.5 concentrations sometimes increased with height maybe due to the influence of temperature inversion layer or long-distance transportation from northern China. The diurnal variations of NO2, O3, TVOCs and CO concentrations at different heights within 500 m AGL were basically consistent. The diurnal variations range of PM2.5 concentrations below 100 m AGL was large and different from other heights, which should be greatly influenced by the local emissions. The unstable atmospheric stability was accompanied by strong photochemical reactions and convective activities, resulting in low concentrations of NO2 and PM2.5, while high concentrations of O3.

Non‐Closure of Surface Energy Balance Linked to Asymmetric Turbulent Transport of Scalars by Large Eddies

AbstractHow large turbulent eddies influence non‐closure of the surface energy balance is an active research topic that cannot be uncovered by the mean continuity equation in isolation. It is demonstrated here that asymmetric turbulent flux transport of heat and water vapor by sweeps and ejections of large eddies under unstable atmospheric stability conditions reduce fluxes. Such asymmetry causes positive gradients in the third‐order moments in the turbulent flux budget equations, primarily attributed to substantially reduced flux contributions by sweeps and sustained large flux contributions by ejections. Small‐scale surface heterogeneity in heating generates ejecting eddies with larger air temperature variance than sweeping eddies, causing asymmetric flux transport in the atmospheric surface layer. Changes in asymmetry with increasing instability are congruent with observed increases in the surface energy balance non‐closure. To assess the contributions of asymmetric flux transport by large eddies to the non‐closure requires two eddy covariance systems on the tower to measure the gradients of the turbulent heat flux and other third‐order moments.

Offshore Wind Turbine Loads and Motions in Unstable Atmospheric Conditions

Even though it is widely known that unstable atmospheric stability conditions can lead to higher turbulence, the use of proper turbulent wind models considering unstable conditions are not often used in the simulation of loads and motions of offshore wind turbines. For this reason, the Højstrup model, which was specifically developed for unstable conditions, is used to simulate a spar-buoy offshore wind turbine (OWT) and investigate the importance of unstable conditions in the design of floating offshore wind turbines. It is found that fatigue damage of a spar-buoy OWT is strongly influenced by unstable conditions, where very unstable condition gives 65% higher fatigue damage than neutral conditions for the tower top torsion, followed by 37% higher for tower base side-side bending and 24% higher for blade root flap-wise mode.

Parameterized Vertical Concentration Profiles for Aerosols in the Marine Atmospheric Boundary Layer

AbstractInformation about sea spray aerosol particle transport and their vertical distribution in the marine atmospheric boundary layer (MABL) is important in marine meteorological forecasting and geobiochemical models. However, due to difficulties in field observations, values of aerosol concentration are often limited to point measurements, and obtaining the size‐resolved concentration profiles is quite challenging. Hence, numerical and analytical studies are vital in modeling the transport of aerosols in the atmospheric boundary layer and beyond. Due to their coarse resolution, most mesoscale and global aerosol models do not accurately resolve the sea spray and aerosol concentrations in the MABL, especially in the surface layer. The objective of the present study is to develop a relatively simple, one‐dimensional analytical model to calculate concentration profiles of aerosols in the MABL. In this study, a new analytical model relating surface flux to vertical concentration profile in the MABL is proposed. The model accounts for the different atmospheric stability and particle settling velocity, thus providing size‐resolved vertical profiles of aerosol concentration. The equations developed here extend the surface layer similarity models to the mixed layer. Model results are compared to aerosol concentration profiles emitted from a surface source obtained from large eddy simulations, for both neutral and unstable atmospheric stability and for particle sizes ranging from 1 to 30 μm. Though the model is developed for sea spray aerosols, it can be used to calculate vertical concentration profiles for other types of settling particles, including dust and sand particles in the atmospheric boundary layer.

Optimizing Window Length for Turbulent Heat Flux Calculations from Airborne Eddy Covariance Measurements under Near Neutral to Unstable Atmospheric Stability Conditions

Airborne eddy covariance (EC) is one of the most effective ways to directly measure turbulent flux at a regional scale. This study aims to find the optimum spatial window length for turbulent heat fluxes calculation from airborne eddy covariance measurements under near neutral to unstable atmospheric stability conditions, to reduce the negative influences from mesoscale turbulence, and to estimate local meaningful turbulent heat fluxes accurately. The airborne flux measurements collected in 2008 in the Netherlands were used in this study. Firstly, the raw data was preprocessed, including de-spike, segmentation, and stationarity test. The atmospheric stability conditions were classified as near neutral, moderately unstable, or very unstable; the stable condition was excluded. Secondly, Ogive analysis for turbulent heat fluxes from all available segmentations of the airborne measurements was used to determine the possible window length range. After that, the optimum window length for turbulent heat flux calculations was defined based on the analysis of all possible window lengths and their uncertainties. The results show that the choice of the optimum window length strongly depends on the atmospheric stability conditions. Under near neutral conditions, local turbulence is mixed insufficiently and vulnerable to heterogeneous turbulence. A relatively short window length is needed to exclude the influence of mesoscale turbulence, and we found the optimum window length ranges from 2000 m to 2500 m. Under moderately unstable conditions, the typical scale of local turbulence is relative large, and the influence of mesoscale turbulence is relatively small. We found the optimum window length ranges from 3900 m to 5000 m. Under very unstable conditions, large convective eddies dominate the transmission of energy so that the window length needs to cover the large eddies with large energy transmission. We found the optimum window length ranges from 4500 m to 5000 m. This study gives a comprehensive methodology to determine the optimizing window length in order to compromise a balance between the accuracy and the surface representativeness of turbulent heat fluxes from airborne EC measurements.

An intercomparison of mesoscale models at simple sites for wind energy applications

Abstract. Understanding uncertainties in wind resource assessment associated with the use of the output from numerical weather prediction (NWP) models is important for wind energy applications. A better understanding of the sources of error reduces risk and lowers costs. Here, an intercomparison of the output from 25 NWP models is presented for three sites in northern Europe characterized by simple terrain. The models are evaluated using a number of statistical properties relevant to wind energy and verified with observations. On average the models have small wind speed biases offshore and aloft (< 4 %) and larger biases closer to the surface over land (> 7 %). A similar pattern is detected for the inter-model spread. Strongly stable and strongly unstable atmospheric stability conditions are associated with larger wind speed errors. Strong indications are found that using a grid spacing larger than 3 km decreases the accuracy of the models, but we found no evidence that using a grid spacing smaller than 3 km is necessary for these simple sites. Applying the models to a simple wind energy offshore wind farm highlights the importance of capturing the correct distributions of wind speed and direction.

Dispersion modeling of thermal power plant emissions on stochastic space

This study aims to couple a deterministic atmospheric dispersion solver based on Gaussian model with a nonintrusive stochastic model to quantify the propagation of multiple uncertainties. The nonintrusive model is based on probabilistic collocation framework. The advantage of nonintrusive nature is to retain the existing deterministic plume dispersion model without missing the accuracy in extracting the statistics of stochastic solution. The developed model is applied to analyze the SO2 emission released from coal firing unit in the second stage of the National Thermal Power Corporation (NTPC) in Dadri, India using “urban” conditions. The entire application is split into two cases, depending on the source of uncertainty. In case 1, the uncertainties in stack gas exit conditions are used to construct the stochastic space while in case 2, meteorological conditions are considered as the sources of uncertainty. Both cases develop 2D uncertain random space in which the uncertainty propagation is quantified in terms of plume rise and pollutant concentration distribution under slightly unstable atmospheric stability conditions. Starting with deterministic Gaussian plume model demonstration and its application, development of stochastic collocation model, convergence study, error analysis, and uncertainty quantification are presented in this paper.

Effect of weather conditions on windbreak odour dispersion

Natural windbreaks are planted to enhance the dispersion of livestock odours and improve the rural environment, although the best implementation strategies still need to be better defined. Using computational fluid dynamic modelling, the objective of this paper was to verify the effect of climatic conditions on odour dispersion downwind from natural windbreaks. The Fluent shear stress transport (SST) k– ω model was used to simulate odour dispersion as released by an odour source, and as dispersed downwind from a single-row coniferous windbreak measuring 9.2 m in height and 7 m in thickness, with an aerodynamic porosity of 0.4. The simulation was limited to a single-point emission source. A total of 21 simulations demonstrated the effects of wind velocity and direction, and air temperature under unstable, neutral, and stable atmospheric conditions. Generally, higher wind velocities produced shorter odour plumes for all atmospheric conditions, but a shorter odour plume was observed also at lower wind velocities under unstable atmospheric stability because of stronger vertical convection. As opposed to air temperature at the ground surface, temperature gradient had a much stronger effect on the odour dispersion domain. Wind direction had an impact on the direction and length of the odour plume, which decreased for wind directions of 0–45° (0° being perpendicular to the windbreak) due to air flowing along and near the leeward side of the windbreak. Neutral atmospheric stability conditions produced a shorter odour plume length compared with unstable and stable conditions because of stronger convective effects.

The Effect of Filter Dimension on the Subgrid-Scale Stress, Heat Flux, and Tensor Alignments in the Atmospheric Surface Layer

Abstract In field experiments designed to study subgrid-scale parameterizations for large eddy simulation, the flow field is often measured and then filtered in two-dimensional planes. This two-dimensional filtering serves as a surrogate for three-dimensional filtering. The question of whether this will yield accurate results in subgrid-scale (SGS) models is addressed by analyzing data from a field experiment in which 16 sonic anemometers were deployed in a four by four grid. The experiment was held in July 2002 at the Surface Layer Turbulence and Environmental Science Test (SLTEST) facility in the Utah West Desert. The full SGS stress tensor and its parameterizations using both two- and three-dimensional filterings are obtained. Comparisons are given between two- and three-dimensional filterings of the field measurements based on probability density functions (PDFs) and energy spectra of the SGS stress elements. The PDFs reveal that quantities calculated with two-dimensional filtering exhibit greater intermittency than those computed with three-dimensional filtering at the same scale. From the spectra it is observed that the different filtering methods result in similar behavior, but that spectra of SGS stress components computed with a three-dimensional filter roll off at a slightly lower wavenumber than those computed with a two-dimensional filter. The PDFs and spectra of the stresses calculated with two- and three-dimensional filters can be made to collapse by reducing the three-dimensional filter scale according to Δ3−D = 0.84Δ2−D. Geometric alignment analyses are performed for the SGS heat flux, SGS stress, and filtered strain rate for the cases of stable, near-neutral, and unstable atmospheric stabilities. Under unstable and near-neutral atmospheric stability, two-dimensional filtering yields acceptable results; however, under stable atmospheric stability, a new approach is recommended and delineated.

The heat flux and the temperature gradient in the lower atmosphere

Most parameterizations used in Large Eddy Simulations of the atmospheric boundary layer are based on the assumption that subgrid‐scale fluxes are aligned against spatial gradients of transported quantities (down‐gradient closures). Based on field experiments, we determine the distribution and most probable relative orientations of the subgrid‐scale (SGS) heat flux relative to parameterizations based on the temperature gradient. We show that, under neutral and unstable atmospheric stability, the SGS heat flux most likely lies within the geometric span of the so called mixed tensor eddy diffusivity model.

Some Basic Properties of the Surrogate Subgrid-Scale Heat Flux in the Atmospheric Boundary Layer

The development of improved subgrid-scale (SGS) models for large-eddy simulation of scalar transport in the atmospheric boundary layer requires an improved understanding of basic properties of the SGS fluxes. High frequency atmospheric wind speed and temperature data sampled at a height of 1.7 m are used to measure SGS heat fluxes and dissipation of temperature variance, by means of one-dimensional filtering and invoking Taylor's hypothesis. Conditional averaging is used to isolate interesting features of the SGS signals, and to relate them to the large-scale characteristics of the flow, such as the presence of coherent structures. Both mean and conditionally averaged SGS quantities are compared with those obtained using a standard eddy-diffusivity model. Within the limitations imposed by the one-dimensional data analysis, we observe that the model appears unable to reproduce important features of the real signals, such as the negative dissipation of temperature variance associated with strong negative resolved temperature gradients due to the ejection of warm air under unstable atmospheric stability conditions.

Watershed Scale Shear Stress From Tethersonde Wind Profile Measurements Under Near Neutral and Unstable Atmospheric Stability

Mean wind speed profiles were measured in the atmospheric surface layer, using a tethersonde system, above the Ojai Valley Watershed in southern California. The valley is mainly planted with mature avocado and orange trees. The surface shear stress and latent and sensible heat fluxes were measured above the trees which are up to 9 m in height. Near‐neutral wind speed profile measurements allowed the determination of the watershed surface roughness (z0 = 1.4 m) and the momentum displacement height (d0 = 7.0 m). The wind speed measurements obtained under unstable atmospheric stability were analyzed using Monin‐Obukhov similarity theory. New stability correction functions proposed based on theory and experiments of Kader‐Yaglom as well as the now classic Businger‐Dyer type functions were tested. The watershed shear stress values calculated using the surface layer wind speed profiles with the new Monin‐Obukhov stability functions were found to be improved in comparison with the values obtained with the Businger‐Dyer functions under strongly unstable stability conditions. The Monin‐Obukhov model with the Businger‐Dyer stability correction function underpredicted the momentum flux by 25% under strongly unstable stability conditions, while the new Kader‐Yaglom formulation compared well on average (R2 = 0.77) with the surface eddy correlation measurements for all atmospheric stability conditions. The unstable 100‐m drag coefficient was found to be u*2/V1002 = 0.0182.

Sensible Heat Flux From Arid Regions: A Simple Flux‐Variance Method

Similarity models in the inner region of the unstable atmospheric boundary layer (ABL) are generally based on four dimensional parameters: buoyancy, friction velocity, surface heat flux, and the height above the land surface. In the free convection limit the friction velocity can be neglected, thus reducing the measurement needs in practical applications. Some field measurements of the second moment of temperature have indicated that free convection scaling of this statistic may be extended into more dynamic regimes, namely, the “dynamic‐convective” and, perhaps, the “dynamic” regions of the ABL. An advantage of this approach is that the sensible heat flux can be estimated without shear stress measurements. This temperature variance similarity model is applied for a wide range of unstably stratified flows over the dry Owens Lake, in southeastern California. The simple free convection model of the temperature variance is accurate for sensible heat flux estimation across the full range of unstable atmospheric stability conditions.