Effect Of Atmospheric Stability Research Articles

An update to WRF surface layer parameterization over an Indian region

Surface layer parameterization schemes in numerical weather prediction models are based on the Monin-Obukhov similarity theory (MOST), which utilizes empirical functions to incorporate the effects of near-surface atmospheric stability. In the present study, an effort has been made to implement and evaluate the performance of recently developed similarity functions under stable stratification in the surface layer parameterization of Weather Research and Forecasting Model version 4.2.2 (WRFv4.2.2). For this purpose, the commonly used revised version of MM5 surface layer module in WRF model is updated using the similarity functions suggested by Srivastava et al. (2020). The model is configured with three nested domains around the flux tower installed at Ranchi (23.412° N, 85.440°E), India. The simulations are carried out for a complete year, and the model simulated near-surface atmospheric variables are compared with the observations. The study reveals that updated similarity functions lead to a noticeable improvement in WRF model performance. In particular, the modified scheme reduced the mean absolute error and root mean square error for 10-m wind speed (2-m temperature) by about 22 % (10 %) and 23 % (8 %), respectively, with improved correlation coefficients during January. The analysis suggests that the new similarity functions could potentially be used in weather forecast model over the Indian region.

Effect of the vertical wake deflection on the response of a 12MW semisubmersible FWT

The need to understand the interaction of floating wind turbines operating in the marine boundary layer with other surrounding turbines is of increasing importance as wind farms and rotor sizes get larger. For low wind speed conditions, the wake deflects upwards due to the floating wind turbine built-in rotor tilt and the platform pitch angle. Furthermore, based on field data from the North Sea, a convective atmosphere is likely to occur, especially for lower wind speeds. It is therefore key to understand the combined effect of meandering, wake deflection and atmospheric stability for low wind speed conditions on the floating wind turbines in a wind farm.In this work, to account for atmospheric stability, data from large-eddy simulation (LES) for a 7.5m/s wind speed scenario and three atmospheric stability conditions, are used as input to FAST. Farm to study the effect of the wake deflection upwards on a 12 MW semisubmersible placed 8 rotor diameters (D) downwind of a stationary wind turbine. Three built-in shaft tilt angles cases are considered for the fixed upwind turbine: 12°, 6° and no tilt angle. The main effects of the wake deflection are on the power output of the floating wind turbine in the wake, and on the tower top yaw moment. For stable conditions, the mean tower top yaw moment increases by more than three times. The findings of this work contribute to the investigation of the wake deflection as a control strategy to minimize wake losses in floating wind farms.

Effect of atmospheric stability on the dynamic wake meandering model applied to two 12 MW floating wind turbines

AbstractCurrent global analysis tools for floating wind turbines (FWTs) do not account for the combined effects of atmospheric stability and wakes from neighboring turbines. This work uses the mid‐fidelity dynamic wake meandering model, together with turbulent wind fields generated based on stable, neutral, and unstable atmospheric conditions, to study the low‐frequency content of the global responses of two semisubmersible FWTs separated by eight rotor diameters. Incoming wind fields based on the Kaimal spectrum and exponential coherence model, the Mann spectral tensor model, and a time‐series input‐based turbulence model are used. The respective input parameters for these models are fitted to high‐fidelity large eddy simulation data.In unstable, below‐rated conditions, meandering leads to an increase in the yaw standard deviation of the downwind turbine of almost three times larger than the upwind turbine. Deficit and the upwards wake deflection affect the mean pitch and yaw, especially for the below‐rated wind speed scenario. The mean pitch of the downwind turbine is reduced up to half the mean pitch value of the upwind turbine, whereas the mean yaw changes direction due to the enhanced effect of shear. The effect of meandering on the structural loading is highest on the standard deviation of the tower‐top yaw moment of the downstream turbine, which increases more than 2.2 times compared to the upwind turbine value. Based on these findings, atmospheric stability affects wake deficit and meandering which in turn have a profound effect on the low‐frequency global motions and structural response of floating wind turbines.

Comparison of the wake characteristics and aerodynamic response of a wind turbine under varying atmospheric conditions using WRF-LES-GAD and WRF-LES-GAL wind turbine models

A generalized actuator line model (GAL) is implemented in the Weather Research and Forecasting (WRF) (Skamarock and Klemp, 2008) model to carry out high-fidelity large-eddy simulations (LESs) of turbulent wind fields in stratified atmospheric boundary layer (ABL) flows and study the effects of atmospheric stability on the wake characteristics and aerodynamic response of a wind turbine (WT). The performance of Vestas V27 WT has been evaluated paying attention to the wind turbine wake behavior and the aerodynamic performance using the already available generalized actuator disk (GAD) and the recently implemented GAL model. Spatial distributions of mean velocity components, their variances and instantaneous vorticity in the wake of the wind turbine are analyzed by comparing the results from GAD and GAL approaches. Results of the wake velocity deficit profiles and wind turbine aerodynamic response have been compared with the experimental ones obtained in the Scaled Wind Farm Technology campaign and available LES data reported in the works of Doubrawa et al. (2020) and Jézéquel et al. (2021). The results from the GAD and GAL models, including the aerodynamic effects of nacelle and tower, agree reasonably well with the results from other LES codes and experimental data, with minor differences between these two models regarding velocity deficits in the near-wake region and wind turbine response under varying atmospheric stability conditions. Overall, the GAL model is able to reproduce the observed wake behavior and the aerodynamic response of the Vestas V27 for the atmospheric conditions tested.

From shear to veer: theory, statistics, and practical application

Abstract. In the past several years, wind veer – sometimes called “directional shear” – has begun to attract attention due to its effects on wind turbines and their production, particularly as the length of manufactured turbine blades has increased. Meanwhile, applicable meteorological theory has not progressed significantly beyond idealized cases for decades, though veer's effect on the wind speed profile has been recently revisited. On the other hand the shear exponent (α) is commonly used in wind energy for vertical extrapolation of mean wind speeds, as well as being a key parameter for wind turbine load calculations and design standards. In this work we connect the oft-used shear exponent with veer, both theoretically and for practical use. We derive relations for wind veer from the equations of motion, finding the veer to be composed of separate contributions from shear and vertical gradients of crosswind stress. Following from the theoretical derivations, which are neither limited to the surface layer nor constrained by assumptions about mixing length or turbulent diffusivities, we establish simplified relations between the wind veer and shear exponent for practical use in wind energy. We also elucidate the source of commonly observed stress–shear misalignment and its contribution to veer, noting that our new forms allow for such misalignment. The connection between shear and veer is further explored through analysis of one-dimensional (single-column) Reynolds-averaged Navier–Stokes solutions, where we confirm our theoretical derivations as well as the dependence of mean shear and veer on surface roughness and atmospheric boundary layer depth in terms of respective Rossby numbers. Finally we investigate the observed behavior of shear and veer across different sites and flow regimes (including forested, offshore, and hilly terrain cases) over heights corresponding to multi-megawatt wind turbine rotors, also considering the effects of atmospheric stability. From this we find empirical forms for the probability distribution of veer during high-veer (stable) conditions and for the variability in veer conditioned on wind speed. Analyzing observed joint probability distributions of α and veer, we compare the two simplified forms we derived earlier and adapt them to ultimately arrive at more universally applicable equations to predict the mean veer in terms of observed (i.e., conditioned on) shear exponent; lastly, the limitations, applicability, and behavior of these forms are discussed along with their use and further developments for both meteorology and wind energy.

Evaluation of Climatic Comfort and its Role in Tourist Attractions in Sulaymaniyah Governorate

Human health and discomfort are influenced by many different environmental conditions that have a direct impact on human feeling, although different research has been attempted to find a suitable solution for it, but still considered as a major obstacle due to the differences in atmospheric elements from one region to another, as well as the differences in the human body›s ability to feel comfortable or uncomfortable in person to person according to different regions. Using temperature and humidity index (THI) Temperature Humidity Indexand air-cooling index (K) Wind chill index and their effect on human peace and tourists visiting Sulaimani province. this research consists of two main axes, the first one is e the atmospheric elements effective on human comfort in the research area, and the second axis is about the effect of atmospheric stability on attracting tourists to the researched area, as this area is known for its low temperatures, especially in winter, as it reaches in some parts to zero Celsius, for instance in Penguin region, which leads to snowfall. This area can be used as a tourist area in winter. In addition to the low temperatures in summer, especially in mountainous areas, this will attract a large number of tourists to the research area, so efforts should be made to provide more services to the tourist areas in a way that tourists do not feel uncomfortable in the surrounding environment and in a way that is compatible with the nature of the area.

A workflow for including atmospheric stability effects in wind resource and yield assessment and its evaluation against wind measurements and SCADA

Atmospheric stability conditions are known to impact the wind resource and yield assessments. However, they are too barely or not correctly taken into account in the industry due to several reasons such as limitations of commercial software or the relative inertia in updating industrial processes. This paper proposes a simplistic approach to improve wind resource and yield assessment certainty while keeping very similar software and industry processes. Two test cases are considered. First, the wind speed estimates made using a CFD software (Meteodyn 5.3) for different stability classes are compared to measurements obtained on a site with four met masts. Second, the wake losses obtained with a commercial yield assessment solver (WindPRO 3.5) considering different wake decay constant definitions are compared to SCADA data. In both cases, it appears that dividing the timeseries in “stability classes” and using corresponding stability parameters in the CFD and in the wake model parameters enable a reduction of the uncertainty. In the case of the energy estimation compared to SCADA, an improvement of 1.25% is obtained compared to the conventional approach.

Using Observed and Modelled Heat Fluxes for Improved Extrapolation of Wind Distributions

Modelling the horizontal and vertical variation of wind speed is crucial for wind energy applications. A model frequently used for this purpose is part of the Wind Atlas Analysis and Application program (WAsP). Here, we modify the model in WAsP to account for local atmospheric stability parameters. Atmospheric stability effects are treated by using the impact of a temperature scale on the geostrophic drag law and the diabatic logarithmic wind profile. Using this approach, wind-direction dependent mean and standard deviation of a surface-layer temperature scale and a mean boundary-layer height scale can be obtained from either numerical weather prediction model output or observations to improve vertical extrapolations of Weibull wind speed distribution parameters. The modified atmospheric stability model is validated at six flat sites in northwestern Europe. The surface-layer temperature scale is available from sonic anemometer measurements at three of the sites. At all sites the temperature scale is also estimated from reanalysis data and from mesoscale model output. The modified model improves the aggregated estimations of power density distributions when extrapolating to nearby locations from 5.2 to 3%, when using the temperature scale derived from either observations or mesoscale/reanalysis output compared to the current model.

STAEBLE: A Surface‐Temperature‐ and Available‐Energy‐Based Lake Evaporation Model

AbstractA mass transfer evaporation model is proposed that uses MODIS water surface temperature data and land‐based meteorological data, and employs a new approach to calibrate the transfer coefficient via closure of the long‐term energy budget of the lake. Some of the longstanding issues of developing and applying lake evaporation models are reviewed, including the adequacy of using land‐based meteorological data, the difficulty of applying transfer coefficients with fixed values calibrated elsewhere, and the need to estimate rates of change of stored enthalpy when the model involves energy budget concepts. Publicly available data from a 5‐year measurement campaign at Lake Mead allow quantification of the effect of using land‐based data, and subsequent testing of the proposed model. We show that atmospheric stability effects are very important, and that their incorporation by means of existing stability functions in the literature produces good results with a one‐parameter model that can be locally calibrated with the same input data used by the model, without the need for local measurements. The model is simple in its structure and data requirements, and can be widely applied.

Effect Dynamic Stability of Atmospheric Boundary Layer on Plume Downward Flux Emitted from Daura Refinery Stacks

The vertical motion of air that enhances or restricts the atmospheric turbulence through atmospheric boundary layer is known as "atmospheric stability", in which any movement of atmospheric components such as water vapor, aerosols, etc. are affected by the atmospheric stability. The aim of this research is to test the effect of atmospheric boundary layer stability on the amount of downward aersols flux at 10um (PM10) emission from stacks of Daura refinery, and estimated of deposition dust aerosols PM10 amount in area around the Daura refinery. In this study, hourly atmospheric stability based on similar theory of Monin-Obukhov length is calculated from archived data of the European Center for Medium Range Weather Forecast, and deposition velocity (Vd) for PM10 that is emitted from stacks Daura Refinery is calculated using the stability parameter (L). PM10 concentration is estimated according to the Gaussian model, which is used along with deposition velocity at this partical size in order to produce downward sedimentation flux (Fp) at distances 1000, 5000 and 10000 m from stack point sources emission. Results show that areas located to the south and southeast of the refinery receive large amounts of deposited flux values through stable weather conditions, where the accumulated PM10 amounts during one month have recorded 1.5 million μg /m2.s in January at a distance of 1000 m from refinery center stacks, while this amount reaches 532 million μg/m2.s during July due to the high emission rates resulting from burning fuel oil during July. The percentages of PM10 sedimentation decreased with the distance from the refinery to 1712 and 322839 μg /m2.s at a distance 10 km from the refinery in January and July, respectively. According to this method, the accumulated amount of PM10 in square meters can be estimated at any time, if atmospheric stability conditions and the domain of wind direction are known.

Experimental and numerical simulations of air quality in an urban canopy: Effects of roof shapes and atmospheric stability

The roof shapes of buildings and atmospheric stability play vital roles in dispersing and transporting pollutants in urban canopies. This study investigated the influence of roof shapes and atmospheric stability through experimental and numerical simulations. Wind flow and gas diffusion simulations were conducted around buildings in urban canopies using wind tunnel experiments and computational fluid dynamic models based on Reynolds-averaged Navier–Stokes models. Four building roof shapes and three atmospheric stability conditions were used in this study. The results of the experiment and numerical simulations were validated using quantitative computational models based on the validation metrics. The numerical simulation results corresponded with the experimental results for the flow and dispersion. The simulation results showed that the flow velocity of the slanted roof was higher than that of the other roof shapes. The pollutants accumulated near the slanted and pitched roofs' leeward side were higher than those in the flat and hip-shaped roofs. Pollutants in the building increased under stable atmospheric conditions and decreased under unstable atmospheric conditions.

Characterising wind shear exponents in the offshore area using Lidar measurements

From a practical standpoint, the 1/7th power law has been extensively used for wind speed extrapolation in wind energy community. However, numerous studies have suggested that unrestricted use of the 1/7th power law can be sometimes misleading due to the highly variable nature of wind shear. Hence, the main goal of this study is to unveil the wind shear characteristics at an offshore site using 3-yr wind Lidar measurement data. The calculation indicates that more than 80% of wind shear exponents (WSEs) are less than 0.14, and the occurrence of negative WSE is more frequent than those over-land. The mean value of WSE increases with wind speed, while the variance exhibits a decreasing pattern. The seasonal variability of WSE is apparent, with a maximum in April and a minimum in September and October. Likewise, the WSE varies within a diurnal cycle, in which higher values are often observed in night-times, while lower and almost constant values are found during daytime. In addition, the effect of atmospheric stability on WSE is also evident, with larger mean values obtained in near-neutral and stable conditions.

Machine Learning for Improving Surface-Layer-Flux Estimates

Flows in the atmospheric boundary layer are turbulent, characterized by a large Reynolds number, the existence of a roughness sublayer and the absence of a well-defined viscous layer. Exchanges with the surface are therefore dominated by turbulent fluxes. In numerical models for atmospheric flows, turbulent fluxes must be specified at the surface; however, surface fluxes are not known a priori and therefore must be parametrized. Atmospheric flow models, including global circulation, limited area models, and large-eddy simulation, employ Monin–Obukhov similarity theory (MOST) to parametrize surface fluxes. The MOST approach is a semi-empirical formulation that accounts for atmospheric stability effects through universal stability functions. The stability functions are determined based on limited observations using simple regression as a function of the non-dimensional stability parameter representing a ratio of distance from the surface and the Obukhov length scale (Obukhov in Trudy Inst Theor Geofiz AN SSSR 1:95–115, 1946), z/L. However, simple regression cannot capture the relationship between governing parameters and surface-layer structure under the wide range of conditions to which MOST is commonly applied. We therefore develop, train, and test two machine-learning models, an artificial neural network (ANN) and random forest (RF), to estimate surface fluxes of momentum, sensible heat, and moisture based on surface and near-surface observations. To train and test these machine-learning algorithms, we use several years of observations from the Cabauw mast in the Netherlands and from the National Oceanic and Atmospheric Administration’s Field Research Division tower in Idaho. The RF and ANN models outperform MOST. Even when we train the RF and ANN on one set of data and apply them to the second set, they provide more accurate estimates of all of the fluxes compared to MOST. Estimates of sensible heat and moisture fluxes are significantly improved, and model interpretability techniques highlight the logical physical relationships we expect in surface-layer processes.

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.

Pseudo-2D RANS: A LiDAR-driven mid-fidelity model for simulations of wind farm flows

Next-generation models of wind farm flows are increasingly needed to assist the design, operation, and performance diagnostic of modern wind power plants. Accuracy in the descriptions of the wind farm aerodynamics, including the effects of atmospheric stability, coalescing wakes, and the pressure field induced by the turbine rotors are necessary attributes for such tools as well as low computational costs. The Pseudo-2D RANS model is formulated to provide an efficient solution of the Navier–Stokes equations governing wind-farm flows installed in flat terrain and offshore. The turbulence closure and actuator disk model are calibrated based on wind light detection and ranging measurements of wind turbine wakes collected under different operative and atmospheric conditions. A shallow-water formulation is implemented to achieve a converged solution for the velocity and pressure fields across a farm with computational costs comparable to those of mid-fidelity engineering wake models. The theoretical foundations and numerical scheme of the Pseudo-2D RANS model are provided, together with a detailed description of the verification and validation processes. The model is assessed against a large dataset of power production for an onshore wind farm located in North Texas showing a normalized mean absolute error of 5.6% on the 10-min-averaged active power and 3% on the clustered wind farm efficiency, which represent 8% and 24%, respectively, improvements with respect to the best-performing engineering wake model tested in this work.

Meso- to microscale modeling of atmospheric stability effects on wind turbine wake behavior in complex terrain

Abstract. Terrain-induced flow phenomena modulate wind turbine performance and wake behavior in ways that are not adequately accounted for in typical wind turbine wake and wind plant design models. In this work, we simulate flow over two parallel ridges with a wind turbine on one of the ridges, focusing on conditions observed during the Perdigão field campaign in 2017. Two case studies are selected to be representative of typical flow conditions at the site, including the effects of atmospheric stability: a stable case where a mountain wave occurs (as in ∼ 50 % of the nights observed) and a convective case where a recirculation zone forms in the lee of the ridge with the turbine (as occurred over 50 % of the time with upstream winds normal to the ridgeline). We use the Weather Research and Forecasting Model (WRF), dynamically downscaled from the mesoscale (6.75 km resolution) to microscale large-eddy simulation (LES) at 10 m resolution, where a generalized actuator disk (GAD) wind turbine parameterization is used to simulate turbine wakes. We compare the WRF–LES–GAD model results to data from meteorological towers, lidars, and a tethered lifting system, showing good qualitative and quantitative agreement for both case studies. Significantly, the wind turbine wake shows different amounts of vertical deflection from the terrain and persistence downstream in the two stability regimes. In the stable case, the wake follows the terrain along with the mountain wave and deflects downwards by nearly 100 m below hub height at four rotor diameters downstream. In the convective case, the wake deflects above the recirculation zone over 40 m above hub height at the same downstream distance. Overall, the WRF–LES–GAD model is able to capture the observed behavior of the wind turbine wakes, demonstrating the model's ability to represent wakes over complex terrain for two distinct and representative atmospheric stability classes, and, potentially, to improve wind turbine siting and operation in hilly landscapes.

Atmospheric Stability Effects on Offshore and Coastal Wind Resource Characteristics in South Korea for Developing Offshore Wind Farms

South Korea is surrounded by the sea on three sides. The characteristics of offshore wind resources vary from region to region due to the influence of the distribution of the coastline and differences in roughness length and atmospheric stability between the coast and the sea. In particular, turbulent gusts and low-level wind shear occurring near the hub height of the wind turbine within the atmospheric boundary layer have a significant effect on the load of wind turbines. These severe weather phenomena are closely related to atmospheric stability. Therefore, the objective of this study is to determine differences in wind resource characteristics in the South Korean offshore and coast in relation to variations in atmospheric stability using observation data from the HeMOSU-1 meteorological tower in the West Sea and the Boseong meteorological observation tower on the southern coast. On the southern coast, changes in sea and land breezes are observed throughout diurnal and nocturnal periods, with an atmospheric stability distribution similar to that of land, which is unstable during the day and becomes more stable at night. On the other hand, the stable ratio continues to dominate in the west offshore. In the case of coastal areas, low-level wind shear occasionally occurs near the general wind turbine hub height approximately over 100 m due to the influence of winds from the sea. This study shows that when constructing an offshore wind farm, it is necessary to first analyze the characteristics of local coastal and offshore wind resources for more efficient and safe wind farm construction and operation.

The effects of thermal stratification on airborne transport within the urban roughness sublayer

The release of airborne hazardous substances in the urban roughness sublayer (RSL) is a risk to human health. The atmospheric dispersion of these materials should be contained to mitigate their adverse consequences. This study investigates the effects of atmospheric stability on the air, heat, and pollutant transport within RSL by a validated 3-D RANS code. A building morphology with height variance is proposed for better representing the real urban environment and characterizing the complex interactions between the roughness elements and the flow regimes. The thermal stratification stability test subject to the ground-inflow temperature difference is extended to span from strongly unstable to moderately stable. The quantitative indicators, including air exchange rate, heat removal rate, pollutant removal rate, heat transfer coefficient, and pollutant transfer coefficient, are introduced and analyzed. The correlations between indicators and thermal stabilities are established, which provides explicit expressions to describe the influence of the changing bulk Richardson number (Rb). Results show that the design of height-variance elements enables a stronger lateral momentum towards the target street canyon, which suppresses the spanwise dispersion of pollutants. The discussions upon heat and pollutant transport based on stability categories show a high Rb-dependence of heat/mass transfer efficiency. The stability threshold is demonstrated to be Rb ≈ 0.7, where the flow speed near the ground approaches zero. As a result, the high temperature gradient is formed and acts as positive feedback to facilitate a more stratified condition. The accurate and rational correlations obtained in this study will save the computational cost considerably for further research. Also, the available results will be a reference for environmentally friendly designs.

Computational fluid dynamics study of CO2 dispersion with phase change of water following the release of supercritical CO2 pipeline

Accidental release of pressurized CO2 pipeline in carbon capture and storage involves the interaction of phase change and heavy-gas dispersion. However, the effect of the phase change of water vapor in air on the performance of cold CO2 dispersion is usually neglected. In this study, a three-dimensional two-phase computational fluid dynamics (CFD) model is developed to evaluate the cold CO2 dispersion by considering the phase change of water. A phase-change model based on the homogeneous relaxation model is used to describe the evaporation and condensation of water. The effects of terrain roughness, atmospheric stability, and turbulence models on the dispersion are also considered. The numerical results show that the model that uses the k–ω turbulent equations is superior to the other models. The results in which the phase change of water is considered exhibit a better agreement with the data from the experiments than those that do not consider it. The model is subsequently used in urban areas, which results in over-predicted CO2 concentration in the near field and under-predicted CO2 concentration in the far field when the phase change of water vapor is considered than that when it is neglected. Therefore, we proposed that the phase change of water vapor in the atmosphere should not be overlooked in the more accurate modeling of cold CO2 dispersion.

Reduced Sea-Surface Roughness Length at a Coastal Site

Sea-surface roughness length is a key parameter for characterizing marine atmospheric boundary layer. Although aerodynamic roughness lengths for homogeneous land and open water surfaces have been examined extensively, the extension of relevant knowledge to the highly inhomogeneous coastal area is problematic due to the complex mechanisms controlling coastal meteorology. This study presented a lidar-based observational analysis of sea-surface roughness length at a coastal site in Hong Kong, in which the wind data recorded from March 2012 to November 2015 were considered and analyzed. The results indicated the turning of wind near the land-sea boundary, leading to a dominative wind direction parallel to the coastline and an acceleration in wind. Moreover, the roughness lengths corresponding to two representative azimuthal sectors were compared, in which the roughness lengths for the onshore wind sector (i.e., 120°–240°) appear to be larger than the constant value (z0 = 0.2 mm) recommended in much existing literature, whereas the values for the alongshore wind sector (i.e., 60°–90°) are significantly smaller, i.e., about two orders of magnitude less than that of a typical sea surface. However, it is to be noted that the effect of atmospheric stability, which is of crucial importance in governing the marine atmospheric boundary layer, is not taken into account in this study.