Mesoscale structure of the atmospheric boundary layer across a natural roughness transition

The structure and intensity of turbulence in the atmospheric boundary layer (ABL) drive fluxes of sediment, contaminants, heat, moisture, and CO[Formula: see text] at the Earth's surface. Where ABL flows encounter changes in roughness-such as cities, wind farms, forest canopies, and landforms-a new mesoscopic flow scale is introduced: the internal boundary layer (IBL), which represents a near-bed region of transient flow adjustment that develops over kilometers. Measurement of this new mesoscopic scale lies outside present observational capabilities of ABL flows, and simplified models fail to capture the sensitive dependence of turbulence on roughness geometry. Here, we use large-eddy simulations, run over high-resolution topographic data and validated against field observations, to examine the structure of the ABL across a natural roughness transition: the emergent sand dunes at White Sands National Park. We observe that development of the IBL is triggered by the abrupt transition from smooth playa surface to dunes; however, continuous changes in the size and spacing of dunes over several kilometers influence the downwind patterns of boundary stress and near-bed turbulence. Coherent flow structures grow and merge over the entire [Formula: see text]10 km distance of the dune field and modulate the influence of large-scale atmospheric turbulence on the bed. Simulated boundary stresses in the developing IBL counter existing expectations and explain the observed downwind decrease in dune migration, demonstrating a mesoscale coupling between flow and form that governs landscape dynamics. More broadly, our findings demonstrate the importance of resolving both turbulence and realistic roughness for understanding fluid-boundary interactions in environmental flows.

Atmospheric Boundary Layer Wind Profile Estimation Using Neural Networks, Mesoscale Models, and LiDAR Measurements

This paper introduces a novel methodology that estimates the wind profile within the ABL by using a neural network along with predictions from a mesoscale model in conjunction with a single near-surface measurement. A major advantage of this solution compared to other solutions available in the literature is that it requires only near-surface measurements for prediction once the neural network has been trained. An additional advantage is the fact that it can be potentially used to explore the time evolution of the wind profile. Data collected by a LiDAR sensor located at the University of León (Spain) is used in the present research. The information obtained from the wind profile is valuable for multiple applications, such as preliminary calculations of the wind asset or CFD modeling.

Atmospheric Boundary Layer Over Ahmedabad, Western Indian Region: Impact of COVID-19 Nationwide Lockdown

The government of India imposed a nationwide lockdown to tackle the outbreak of COVID-19 in 2020. This period witnessed record low anthropogenic activity, which had severe socio-economic impacts but also had orthogonal effects on the ambient air quality of the atmosphere. This study focuses on the variations in the atmospheric boundary layer (ABL) over a western Indian urban region in the light of COVID-19. Continuous backscatter recorded by a ceilometer, stationed at Ahmedabad, was used in this study to monitor the ABL during the national lockdown (NLD) in 2020 and state restrictions in 2021, and compared with the control year of 2019. In parallel, improvement in air quality during the NLD was observed by the SAFAR air quality station at Ahmedabad, with decreased particulate matter concentrations. The ground-based observations were substantiated by the ERA5 reanalysis dataset. A decline in the ABL height was recorded during the NLD, which showed improvement in 2021 but which was shy of the ABL in 2019. This was correlated with rain events during the observational period, recorded by an automatic weather station.

Vertical structure of conventionally neutral atmospheric boundary layers

SignificanceThe presented model describes the vertical structure of conventionally neutral atmospheric boundary layers. Due to the complicated interplay between buoyancy, shear, and Coriolis effects, analytical descriptions have been limited to the mean wind speed. We introduce an analytical approach based on the Ekman equations and the basis function of the universal potential temperature flux profile that allows one to describe the wind and turbulent shear stress profiles and hence capture features like the wind veer profile. The analytical profiles are validated against high-fidelity large-eddy simulations and atmospheric measurements. Our findings contribute to the scientific community's fundamental understanding of atmospheric turbulence with direct relevance for weather forecasting, climate modeling, and wind energy applications.

Atmospheric Boundary Layer Wind Profile Estimation Using Neural Networks Applied to Lidar Measurements

This paper introduces a new methodology for estimating the wind profile within the ABL (Atmospheric Boundary Layer) using a neural network and a single-point near-ground measurement. An important advantage of this solution when compared with others available in the literature is that it only requires near surface measurements for the prognosis once the neural network is trained. Another advantage is that it can be used to study the wind profile temporal evolution. This work uses data collected by a lidar sensor located at the Universidad de León (Spain). The neural network best configuration was determined using sensibility analyses. The result is a multilayer perceptron with three layers for each altitude: the input layer has six nodes for the last three measurements, the second has 128 nodes and the third consists of two nodes that provide u and v. The proposed method has better performance than traditional methods. The obtained wind profile information obtained is useful for multiple applications, such as preliminary calculations of the wind resource or CFD models.

Key Points in Air Pollution Meteorology

Although emissions have a direct impact on air pollution, meteorological processes may influence inmission concentration, with the only way to control air pollution being through the rates emitted. This paper presents the close relationship between air pollution and meteorology following the scales of atmospheric motion. In macroscale, this review focuses on the synoptic pattern, since certain weather types are related to pollution episodes, with the determination of these weather types being the key point of these studies. The contrasting contribution of cold fronts is also presented, whilst mathematical models are seen to increase the analysis possibilities of pollution transport. In mesoscale, land-sea and mountain-valley breezes may reinforce certain pollution episodes, and recirculation processes are sometimes favoured by orographic features. The urban heat island is also considered, since the formation of mesovortices determines the entry of pollutants into the city. At the microscale, the influence of the boundary layer height and its evolution are evaluated; in particular, the contribution of the low-level jet to pollutant transport and dispersion. Local meteorological variables have a major influence on calculations with the Gaussian plume model, whilst some eddies are features exclusive to urban environments. Finally, the impact of air pollution on meteorology is briefly commented on.

Moving towards a Network of Autonomous UAS Atmospheric Profiling Stations for Observations in the Earth's Lower Atmosphere: The 3D Mesonet Concept

The deployment of small unmanned aircraft systems (UAS) to collect routine in situ vertical profiles of the thermodynamic and kinematic state of the atmosphere in conjunction with other weather observations could significantly improve weather forecasting skill and resolution. High-resolution vertical measurements of pressure, temperature, humidity, wind speed and wind direction are critical to the understanding of atmospheric boundary layer processes integral to air–surface (land, ocean and sea ice) exchanges of energy, momentum, and moisture; how these are affected by climate variability; and how they impact weather forecasts and air quality simulations. We explore the potential value of collecting coordinated atmospheric profiles at fixed surface observing sites at designated times using instrumented UAS. We refer to such a network of autonomous weather UAS designed for atmospheric profiling and capable of operating in most weather conditions as a 3D Mesonet. We outline some of the fundamental and high-impact science questions and sampling needs driving the development of the 3D Mesonet and offer an overview of the general concept of operations. Preliminary measurements from profiling UAS are presented and we discuss how measurements from an operational network could be realized to better characterize the atmospheric boundary layer, improve weather forecasts, and help to identify threats of severe weather.

On the Use of Rotary-Wing Aircraft to Sample Near-Surface Thermodynamic Fields: Results from Recent Field Campaigns

Rotary-wing small unmanned aircraft systems (sUAS) are increasingly being used for sampling thermodynamic and chemical properties of the Earth’s atmospheric boundary layer (ABL) because of their ability to measure at high spatial and temporal resolutions. Therefore, they have the potential to be used for long-term quasi-continuous monitoring of the ABL, which is critical for improving ABL parameterizations and improving numerical weather prediction (NWP) models through data assimilation. Before rotary-wing aircraft can be used for these purposes, however, their performance and the sensors used therein must be adequately characterized. In the present study, we describe recent calibration and validation procedures for thermodynamic sensors used on two rotary-wing aircraft: A DJI S-1000 and MD4-1000. These evaluations indicated a high level of confidence in the on-board measurements. We then used these measurements to characterize the spatiotemporal variability of near-surface (up to 300-m AGL) temperature and moisture fields as a component of two recent field campaigns: The Verification of the Origins of Rotation in Tornadoes Experiment in the Southeast U.S. (VORTEX-SE) in Alabama, and the Land Atmosphere Feedback Experiment (LAFE) in northern Oklahoma.

Introduction Wind farms in complex terrains: an introduction

Wind energy is one of the fastest growing sources of sustainable energy production. As more wind turbines are coming into operation, the best locations are already becoming occupied by turbines, and wind-farm developers have to look for new and still available areas-locations that may not be ideal such as complex terrain landscapes. In these locations, turbulence and wind shear are higher, and in general wind conditions are harder to predict. Also, the modelling of the wakes behind the turbines is more complicated, which makes energy-yield estimates more uncertain than under ideal conditions. This theme issue includes 10 research papers devoted to various fluid-mechanics aspects of using wind energy in complex terrains and illustrates recent progress and future developments in this important field.This article is part of the themed issue 'Wind energy in complex terrains'.

Surface-atmosphere decoupling limits accumulation at Summit, Greenland

Despite rapid melting in the coastal regions of the Greenland Ice Sheet, a significant area (~40%) of the ice sheet rarely experiences surface melting. In these regions, the controls on annual accumulation are poorly constrained owing to surface conditions (for example, surface clouds, blowing snow, and surface inversions), which render moisture flux estimates from myriad approaches (that is, eddy covariance, remote sensing, and direct observations) highly uncertain. Accumulation is partially determined by the temperature dependence of saturation vapor pressure, which influences the maximum humidity of air parcels reaching the ice sheet interior. However, independent proxies for surface temperature and accumulation from ice cores show that the response of accumulation to temperature is variable and not generally consistent with a purely thermodynamic control. Using three years of stable water vapor isotope profiles from a high altitude site on the Greenland Ice Sheet, we show that as the boundary layer becomes increasingly stable, a decoupling between the ice sheet and atmosphere occurs. The limited interaction between the ice sheet surface and free tropospheric air reduces the capacity for surface condensation to achieve the rate set by the humidity of the air parcels reaching interior Greenland. The isolation of the surface also acts to recycle sublimated moisture by recondensing it onto fog particles, which returns the moisture back to the surface through gravitational settling. The observations highlight a unique mechanism by which ice sheet mass is conserved, which has implications for understanding both past and future changes in accumulation rate and the isotopic signal in ice cores from Greenland.

Observed Thermal Impacts of Wind Farms Over Northern Illinois

This paper assesses impacts of three wind farms in northern Illinois using land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard the Terra and Aqua satellites for the period 2003–2013. Changes in LST between two periods (before and after construction of the wind turbines) and between wind farm pixels and nearby non-wind-farm pixels are quantified. An areal mean increase in LST by 0.18–0.39 °C is observed at nighttime over the wind farms, with the geographic distribution of this warming effect generally spatially coupled with the layout of the wind turbines (referred to as the spatial coupling), while there is no apparent impact on daytime LST. The nighttime LST warming effect varies with seasons, with the strongest warming in winter months of December-February, and the tightest spatial coupling in summer months of June-August. Analysis of seasonal variations in wind speed and direction from weather balloon sounding data and Automated Surface Observing System hourly observations from nearby stations suggest stronger winds correspond to seasons with greater warming and larger downwind impacts. The early morning soundings in Illinois are representative of the nighttime boundary layer and exhibit strong temperature inversions across all seasons. The strong and relatively shallow inversion in summer leaves warm air readily available to be mixed down and spatially well coupled with the turbine. Although the warming effect is strongest in winter, the spatial coupling is more erratic and spread out than in summer. These results suggest that the observed warming signal at nighttime is likely due to the net downward transport of heat from warmer air aloft to the surface, caused by the turbulent mixing in the wakes of the spinning turbine rotor blades.