Horizontal Wind Components Research Articles

Flight-Data-Based High-Fidelity System Identification of DJI M600 Pro Hexacopter

Research and industrial application can require custom high-level controllers for industrial drones. Thus, this paper presents the high-fidelity dynamic and control model identification of the DJI M600 Pro hexacopter. This is a widely used multicopter in the research and industrial community due to its high payload capability and reliability. To support these communities, the focus of control model identification was on the exploration and implementation of DJI Onboard Software Development Kit (OSDK) functionalities, also including some unconventional special modes. Thus, the resulting model can be controlled with the same OSDK functionalities as the real drone, making control development and application time effective. First, the hardware and software structure of the additional DJI M600 onboard system are introduced. Then, the postulated dynamic and control system models are shown. Next, real flight test campaigns generating data for system identification are presented. Then, the mass and inertial properties are estimated for TB47S and TB48S battery sets and the custom Forerunner UAV payload. Dynamic system model identification includes the aerodynamic effects and considers hover, vertical, and horizontal forces together with static horizontal wind components and finally the rotational moments and dynamics. The control system components were identified following the structure of OSDK, including vertical, horizontal, and yaw loops. After identification, the model was validated and refined based on an unused flight test and software-in-the-loop simulation data. The simulation is provided by DJI and was also compared to real flight results. This comparison showed that the DJI simulation covers the dynamics of the real drone well, but it requires being connected to the drone and needs the controllers onboard to be implemented in advance, which limits applicability and increases development time. This was another motivation to introduce a standalone simulation in Matlab Simulink, which covers all the important modes of OSDK control and can be run solely in Matlab without any hardware support. The constructed model will be published for the benefit of the research and industrial community.

Computational Domain Size Effects on Large-Eddy Simulations of Precipitating Shallow Cumulus Convection

Idealized large-eddy simulations of shallow convection often utilize horizontally periodic computational domains. The development of precipitation in shallow cumulus convection changes the spatial structure of convection and creates large-scale organization. However, the limited periodic domain constrains the horizontal variability of the atmospheric boundary layer. Small computational domains cannot capture the mesoscale boundary layer organization and artificially constrain the horizontal convection structure. The effects of the horizontal domain size on large-eddy simulations of shallow precipitating cumulus convection are investigated using four computational domains, ranging from 40×40km2 to 320×320km2 and fine grid resolution (40 m). The horizontal variability of the boundary layer is captured in computational domains of 160×160km2. Small LES domains (≤40 km) cannot reproduce the mesoscale flow features, which are about 100km long, but the boundary layer mean profiles are similar to those of the larger domains. Turbulent fluxes, temperature and moisture variances, and horizontal length scales are converged with respect to domain size for domains equal to or larger than 160×160km2. Vertical velocity flow statistics, such as variance and spectra, are essentially identical in all domains and show minor dependence on domain size. Characteristic horizontal length scales (i.e., those relating to the mesoscale organization) of horizontal wind components, temperature and moisture reach an equilibrium after about hour 30.

MMA: A novel algorithm for efficient separation of the precipitation echoes from wind profiler radar's Doppler power spectrum

Wind profiler radars are powerful research tools for analyzing atmospheric dynamics, and their acquired data quality is vital for accurate wind parameter estimation. The presence of precipitation poses a major challenge to traditional estimation techniques. This paper presents a novel algorithm for efficiently separating ambient air and precipitation echoes from the Doppler power spectrum. The proposed Mirror-Minimum Algorithm leverages mirror image formation in opposite off-zenith beams to separate the echoes. It is a straightforward and practical solution that can be implemented with less computing complexity than existing methods. The wind profiler radars operating worldwide can easily employ this method to improve the accuracy of estimating horizontal wind components from measurements affected by precipitation. The proposed algorithm has been validated on the Doppler power spectrum obtained from the wind profiler radar operating at 205 MHz. The experimental evaluation shows promising results in varying precipitation conditions, even in highly adverse ones.

Identification of equatorial waves using Hough function vectors

AbstractEquatorial waves are essential features of the tropical atmosphere dynamics, and their diagnosis is relevant for both operational and climate analysis. Here, we present a method for the identification of equatorial waves using the multivariate spatial structures of the eigensolutions of the linearized shallow‐water equations over the sphere, named Hough function vectors. The method does not require any a priori space–time filtering to separate westward‐ and eastward‐moving waves, and it can be applied to instantaneous or daily circulation fields. The wave types (Kelvin, Rossby, mixed Rossby–gravity, inertio‐gravity) are unambiguously identified by the intrinsic dynamical relationship between the horizontal wind components and geopotential fields represented in the multivariate meridional structures of the Hough function vectors. Both free and convectively coupled equatorial waves can be diagnosed. Moreover, different time filterings can be applied a posteriori, depending on the purposes of the analysis. This article is written as a proof of concept, and direct comparisons are made with results of other methods recently reviewed in a work published in this journal.

Modeling Tool for Estimating Carbon Dioxide Fluxes over a Non-Uniform Boreal Peatland

We present a modeling tool capable of computing carbon dioxide (CO2) fluxes over a non-uniform boreal peatland. The three-dimensional (3D) hydrodynamic model is based on the “one-and-a-half” closure scheme of the system of the Reynolds-Averaged Navier–Stokes and continuity equations. Despite simplifications used in the turbulence description, the model allowed obtaining the spatial steady-state distribution of the averaged wind velocities and coefficients of turbulent exchange within the atmospheric surface layer, taking into account the surface heterogeneity. The spatial pattern of CO2 fluxes within and above a plant canopy is derived using the “diffusion–reaction–advection” equation. The model was applied to estimate the spatial heterogeneity of CO2 fluxes over a non-uniform boreal ombrotrophic peatland, Staroselsky Moch, in the Tver region of European Russia. The modeling results showed a significant effect of vegetation heterogeneity on the spatial pattern of vertical and horizontal wind components and on vertical and horizontal CO2 flux distributions. Maximal airflow disturbances were detected in the near-surface layer at the windward and leeward forest edges. The forest edges were also characterized by maximum rates of horizontal CO2 fluxes. Modeled turbulent CO2 fluxes were compared with the mid-day eddy covariance flux measurements in the southern part of the peatland. A very good agreement of modeled and measured fluxes (R2 = 0.86, p < 0.05) was found. Comparisons of the vertical profiles of CO2 fluxes over the entire peatland area and at the flux tower location showed significant differences between these fluxes, depending on the prevailing wind direction and the height above the ground.

The Potential Benefits of Handling Mixture Statistics via a Bi-Gaussian EnKF: Tests With All-Sky Satellite Infrared Radiances.

The meteorological characteristics of cloudy atmospheric columns can be very different from their clear counterparts. Thus, when a forecast ensemble is uncertain about the presence/absence of clouds at a specific atmospheric column (i.e., some members are clear while others are cloudy), that column's ensemble statistics will contain a mixture of clear and cloudy statistics. Such mixtures are inconsistent with the ensemble data assimilation algorithms currently used in numerical weather prediction. Hence, ensemble data assimilation algorithms that can handle such mixtures can potentially outperform currently used algorithms. In this study, we demonstrate the potential benefits of addressing such mixtures through a bi-Gaussian extension of the ensemble Kalman filter (BGEnKF). The BGEnKF is compared against the commonly used ensemble Kalman filter (EnKF) using perfect model observing system simulated experiments (OSSEs) with a realistic weather model (the Weather Research and Forecast model). Synthetic all-sky infrared radiance observations are assimilated in this study. In these OSSEs, the BGEnKF outperforms the EnKF in terms of the horizontal wind components, temperature, specific humidity, and simulated upper tropospheric water vapor channel infrared brightness temperatures. This study is one of the first to demonstrate the potential of a Gaussian mixture model EnKF with a realistic weather model. Our results thus motivate future research toward improving numerical Earth system predictions though explicitly handling mixture statistics.

Numerical modeling of infrasound propagation in a stratified atmosphere with small-scale inhomogeneities

A major focus in infrasound research is the inclusion of realistic atmospheric flows in numerical propagation models. This usually encompasses temperature gradients and horizontal wind components, which create atmospheric waveguides. Additionally, gravity waves lead to small-scale variations of the ambient wind in the middle atmosphere, between 10 and 100 km in altitude. Using an internal gravity wave model from the literature [Gardner, J. Atmos. Terr. Phys. (1996)], we parametrize random fluctuations of the wind profiles, where the initial background state is based on a published case study [Sabatini et al., J. Acoust. Soc. Am. (2016)]. Acoustic propagation from an impulsive point source located at the ground is then modelled with solvers of the PLetma package [Khodr et al., J. Acoust. Soc. Am. (2021)], namely, ray tracing, normal modes, one-way equation and FDTD, for frequencies higher than 0.01 Hz. Cases with and without wind are considered, and propagation effects are investigated by a sensitivity analysis on source parameters and characteristics of the gravity wave. [This work was conducted within the framework of LETMA, a Contractual Research Laboratory shared between CEA, CNRS, Ecole Centrale de Lyon, C-Innov, and Sorbonne Université.]

Frequency spectra of horizontal winds in the mesosphere and lower thermosphere region from multistatic specular meteor radar observations during the SIMONe 2018 campaign

In recent years, multistatic specular meteor radars (SMRs) have been introduced to study the Mesosphere and Lower Thermosphere (MLT) dynamics with increasing spatial and temporal resolution. SMRs, compared to other ground-based observations, have the advantage of continuously measuring the region between 80 and 100 km independent of weather, season, or time of day. In this paper, frequency spectra of MLT horizontal winds are explored through observations from a campaign using the SIMONe (Spread-spectrum Interferometric Multistatic meteor radar Observing Network) approach conducted in northern Germany in 2018 (hereafter SIMONe 2018). The 7-day SIMONe 2018 comprised of fourteen multistatic SMR links and allows us to build a substantial database of specular meteor trail events, collecting more than one hundred thousand detections per day within a geographic area of sim 500 km times 500 km. We have implemented two methods to obtain the frequency spectra of the horizontal wind components: (1) Mean Wind Estimation (MWE) and (2) Wind field Correlation Function Inversion (WCFI), which utilizes the mean and the covariances of the line of sight velocities, respectively. Monte Carlo simulations of a gravity wave spectral model were implemented to validate and compare both methods. The simulation analyses suggest that the WCFI helps us to capture the energy of smaller scale wind fluctuations than those capture with MWE. Characterization of the spectral slope of the horizontal wind at different MLT altitudes has been conducted on the SIMONe 2018, and it provides evidence that gravity waves with periods smaller than 7 h and greater than 2 h dominate with horizontal structures significantly larger than 500 km. In the future, these analyses can be extended to understand the significance of small-scale fluctuations in the MLT, which were not possible with conventional MWE methods.Graphical

Resolving Vertical Variations of Horizontal Neutral Winds in Earth's High Latitude Space-Atmosphere Interaction Region (SAIR).

Few remote sensing or in‐situ techniques can measure winds in Earth's thermosphere between altitudes of 120 and 200 km. One possible approach within this region uses Doppler spectroscopy of the optical emission from atomic oxygen at 558 nm, although historical approaches have been hindered in the auroral zone because the emission altitude varies dramatically, both across the sky and over time, as a result of changing characteristic energy of auroral precipitation. Thus, a new approach is presented that instead uses this variation as an advantage, to resolve height profiles of the horizontal wind. Emission heights are estimated using the Doppler temperature derived from the 558 nm emission. During periods when the resulting estimates span a wide enough height interval, it is possible to use low order polynomial functions of altitude to model the Doppler shifts observed across the sky and over time, and thus reconstruct height profiles of the horizontal wind components. The technique introduced here is shown to work well provided there are no strong horizontal gradients in the wind field. Conditions satisfying these caveats do occur frequently and the resulting wind profiles validate well when compared to absolute in‐situ wind measurements from a rocket‐borne chemical release. While both the optical and chemical tracer techniques agreed with each other, they did not agree with the HWM‐14 horizontal wind model. Applying this technique to wind measurements near the geomagnetic cusp footprint indicated that cusp‐region forcing did not penetrate to atmospheric heights of 240 km or lower.

Validation of Multistatic Meteor Radar Analysis Using Modeled Mesospheric Dynamics: An Assessment of the Reliability of Gradients and Vertical Velocities

AbstractA virtual meteor radar system based on the upper‐atmosphere extension of the high‐resolution ICOsahedral Non‐hydrostatic general circulation model is constructed to validate multistatic specular meteor radar (SMR) analyses. The virtual radar system examines the validity of mean winds and gradients estimation techniques used in multistatic SMRs. The study is motivated by unexpected mean values and tide‐like features recently observed in the vertical velocities estimated from multistatic SMRs at different latitudes in the mesosphere and lower thermosphere. The proposed analysis confirms multistatic SMR systems' excellent capability to measure the horizontal mean wind components and gradient terms. It is also found that multistatic SMRs can estimate mean vertical winds if they have an amplitude greater than ±2 m/s. Due to the smoothing inherent to the model results, these results should be treated as lower bounds to the error incurred using real data. Hourly variability in vertical velocity estimates up to ±1–2 m/s in the observed vertical winds are due to contamination by small‐scale horizontal structures in the horizontal winds.

Using an Artificial Neural Network to improve operational wind prediction in a small unresolved valley

AbstractThis study improves surface wind predictions in an unresolved valley using an artificial neural network (ANN). Forecasting winds in complex terrain with a mesoscale model is challenging. This study assesses the quality of 3-km wind forecasts by the Weather Research and Forecasting (WRF) model and the potential of post-processing by an ANN within the 1-2 km wide Cadarache Valley in southeast France. Operational wind forecasts for 110m above ground level and the near-surface vertical potential temperature gradient with a lead time of 24-48h were used as ANN input. Observed horizontal wind components at 10m within the valley were used as targets during ANN training. We use the Directional ACCuracy (DACC45, wind direction error ≤ 45°) and mean absolute error to evaluate the WRF direct model output and the ANN results. By post-processing, the score for DACC45 improves from 56% in the WRF direct model output to 79% after applying the ANN. Furthermore, the ANN performed well during the day and night, but poorly during the morning and afternoon transitions. The ANN improves the DACC45 at 10m even for poor WRF forecasts (direction bias ≥ 45°) from 42% to 72%. A shorter lead time and finer grid spacing (1 km) showed negligible impact which suggests that a 3 km grid spacing and a 24-48h lead time is effective and relatively cheap to apply. We find that WRF performs well in near-neutral conditions and poorly in other atmospheric stability conditions. The ANN post-treatment consistently improves the wind forecast for all stability classes to a DACC45 of about 80%. The study demonstrates the ability to improve Cadarache valley wind forecasts using an ANN as post-processing for WRF daily forecasts.

Easterly waves and precipitation over northern South America and the Caribbean

ABSTRACTThe Easterly Waves (EWs) have been highlighted as one of the different spatiotemporal processes that influence hydro‐climatology over northern South America and the Caribbean Sea, particularly during boreal summer. Previous studies recognize the EWs among the most important features of the rainy season in northern South America, suggesting the occurrence of precipitation as the main meteorological response to the passage of these disturbances. However, it is shown in this work that not all the EWs that propagate over northern South America and the Caribbean Sea have such an effect. Almost 50% of the EWs moving over the region during the 1983–2018 period were accompanied by the inhibition of precipitation and clear skies, as depicted by anomalies from the Climate Data Record of Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks precipitation dataset and the National Oceanic and Atmospheric Administration interpolated Outgoing Longwave Radiation dataset. This work intends to address the relationship between these atmospheric perturbations and the occurrence or inhibition of precipitation, as well as a plausible connection with the Madden–Julian Oscillation (MJO). In particular, horizontal components of wind and relative vorticity, together with low and upper troposphere divergence, were used to identify and characterize the EW activity over northern South America and the Caribbean Sea. Results suggest an influence of the MJO on the effects that the EWs have on convection and precipitation over the region, as well as the direction in which such perturbances continue their westward propagation.

Validation of Aeolus winds using ground-based radars in Antarctica and in northern Sweden

Abstract. Winds measured by lidar from the Aeolus satellite are compared with winds measured by two ground-based radars – MARA in Antarctica (70.77∘ S, 11.73∘ E) and ESRAD (67.88∘ N, 21.10∘ E) in Arctic Sweden – for the period 1 July–31 December 2019. Aeolus is a demonstrator mission to test whether winds measured by Doppler lidar from space can have sufficient accuracy to contribute to improved weather forecasting. A comprehensive programme of calibration and validation has been undertaken following the satellite launch in 2018, but, so far, direct comparison with independent measurements from the Arctic or Antarctic regions have not been made. The comparison covers heights from the low troposphere to just above the tropopause. Results for each radar site are presented separately for Rayleigh (clear) winds, Mie (cloudy) winds, sunlit (“summer”) and non-sunlit (“winter”) seasons, and ascending and descending satellite tracks. Horizontally projected line-of-sight (HLOS) winds from Aeolus, reprocessed using baseline 2B10, for passes within 100 km of the radar sites, are compared with HLOS winds calculated from 1 h averaged radar horizontal wind components. The agreement in most data subsets is very good, with no evidence of significant biases (<1 m s−1). Possible biases are identified for two subsets (about −2 m s−1 for the Rayleigh winds for the descending passes at MARA and about 2 m s−1 for the Mie winds for the ascending passes at ESRAD, both in winter), but these are only marginally significant. A robust significant bias of about 7 m s−1 is found for the Mie winds for the ascending tracks at MARA in summer. There is also some evidence for increased random error (by about 1 m s−1) for the Aeolus Mie winds at MARA in summer compared to winter. This might be related to the presence of sunlight scatter over the whole of Antarctica as Aeolus transits across it during summer.

A Feasibility Study for Determining the Sensible Heat Flux to and from Small Green Roofs

Eddy covariance is an established technique for registering sensible heat fluxes. However, this method is less adequate for smaller surfaces that cannot match the associated footprint. As an alternative technique, a recently constructed acoustic anemometer (Ly-ATOM) is tested, which operates horizontally at an extension of circa 1 m and a data-acquisition frequency of 1 Hz. The Ly-ATOM device reproduces both the acoustic virtual temperature and the horizontal wind components registered by a three-dimensional sonic anemometer. As this Ly-ATOM device can be applied much closer to the ground compared with a sonic anemometer, the size of the related source area is significantly reduced (by a factor of 25). Two methods are used to retrieve the sensible heat flux from variance characteristics of temperature and the horizontal wind components recorded by the Ly-ATOM device: combining the flux-variance-similarity and alternative-flux-variance methods for use in unstable and stable stratification, respectively, yields good results for the sonic measurements. Therefore, these methods can be applied to the Ly-ATOM device as well. In investigating the sensitivity to detect modified surface characteristics, specifically increased evapotranspiration and decreased surface albedo, the Ly-ATOM device proves to be superior to the sonic anemometer which is more vertically removed from the surface of interest.

Characterization of vertical wind velocity variability based on fractal dimension analysis

Abstract Modelling and forecasting the temporal behaviour of wind is of substantial importance in a variety of applications, which depend largely on the understanding and quantification of its variability. Existing literature focusing on wind speed variability is predominantly associated with horizontal wind component, whereas the knowledge of vertical wind component is much less documented. This paper investigates the variability of vertical wind velocity in the context of fractal dimension analysis. It is shown that the time series of vertical wind velocity are monofractals and weak anti-persistent. The median value of fractal dimension decreases from 1.582 ​at 10 ​m height to 1.547 ​at 320 ​m height. The vertical profile of fractal dimension is strongly tied with atmospheric stability condition, in terms of both magnitude and profile shape, and the deviation is most pronounced at higher levels. Moreover, the fractal dimension is found to increase with the increase in the mean horizontal wind speed, which can be partly attributed to the effect of atmospheric stability. Such relationship is also height-dependent. Similar to the horizontal wind component, the fractal dimension of vertical wind component also exhibits a positive correlation with window width.

Wave-slope soaring of the brown pelican

BackgroundFrom the laboratory at Scripps Institution of Oceanography, it is common to see the brown pelican (Pelecanus occidentalis) traveling along the crests of ocean waves just offshore of the surf-zone. When flying in this manner, the birds can travel long distances without flapping, centimeters above the ocean’s surface. Here we derive a theoretical framework for assessing the energetic savings related to this behavior, ‘wave-slope soaring,’ in which an organism in flight takes advantage of localized updrafts caused by traveling ocean surface gravity waves.MethodsThe energy cost of steady, constant altitude flight in and out of ground effect are analyzed as controls. Potential flow theory is used to quantify the ocean wave-induced wind associated with near-shoaling, weakly nonlinear, shallow water ocean surface gravity waves moving through an atmosphere initially at rest. Using perturbation theory and the Green’s function for Laplace’s equation in 2D with Dirichlet boundary conditions, we obtain integrals for the horizontal and vertical components of the wave-induced wind in a frame of reference moving with the wave. Wave-slope soaring flight is then analyzed using an energetics-based approach for waves under a range of ocean conditions and the body plan of P. occidentalis.ResultsFor ground effect flight, we calculate a ∼15 - 25% reduction in cost of transport as compared with steady, level flight out of ground effect. When wave-slope soaring is employed at flight heights ∼2m in typical ocean conditions (2m wave height, 15s period), we calculate 60-70% reduction in cost of transport as compared with flight in ground effect. A relatively small increase in swell amplitude or decrease in flight height allows up to 100% of the cost of transport to be offset by wave-slope soaring behavior.ConclusionsThe theoretical development presented here suggests there are energy savings associated with wave-slope soaring. Individual brown pelicans may significantly decrease their cost of transport utilizing this mode of flight under typical ocean conditions. Thus wave-slope soaring may provide fitness benefit to these highly mobile organisms that depend on patchy prey distribution over large home ranges.

IntelliO3-ts v1.0: a neural network approach to predict near-surface ozone concentrations in Germany

Abstract. The prediction of near-surface ozone concentrations is important for supporting regulatory procedures for the protection of humans from high exposure to air pollution. In this study, we introduce a data-driven forecasting model named “IntelliO3-ts”, which consists of multiple convolutional neural network (CNN) layers, grouped together as inception blocks. The model is trained with measured multi-year ozone and nitrogen oxide concentrations of more than 300 German measurement stations in rural environments and six meteorological variables from the meteorological COSMO reanalysis. This is by far the most extensive dataset used for time series predictions based on neural networks so far. IntelliO3-ts allows the prediction of daily maximum 8 h average (dma8eu) ozone concentrations for a lead time of up to 4 d, and we show that the model outperforms standard reference models like persistence models. Moreover, we demonstrate that IntelliO3-ts outperforms climatological reference models for the first 2 d, while it does not add any genuine value for longer lead times. We attribute this to the limited deterministic information that is contained in the single-station time series training data. We applied a bootstrapping technique to analyse the influence of different input variables and found that the previous-day ozone concentrations are of major importance, followed by 2 m temperature. As we did not use any geographic information to train IntelliO3-ts in its current version and included no relation between stations, the influence of the horizontal wind components on the model performance is minimal. We expect that the inclusion of advection–diffusion terms in the model could improve results in future versions of our model.

Variational bias correction for Mode-S aircraft derived winds

A variational bias correction (VarBC) technique is proposed within the three-dimensional variational (3D-Var) assimilation system of the Météo-France convective scale model AROME to remove biases present in horizontal wind components derived from aircraft Mode-S data. A set of two predictors derived from the geometry between ground and air speeds has been chosen in order to correct the aircraft speed and heading. Data collected from a set of 8 ADS-B antennas located over France for two periods in 2018 (April and October) have been used to assess the VarBC. Thanks to the availability of anchoring data (radiosoundings, AMDAR aircraft reports), the adaptive bias correction scheme is very efficient for improving the quality of Mode-S derived winds to a level that is similar to those from AMDAR and Mode-S bias corrected by the KNMI. The heading bias correction is the most important one in order to reach background departure values around 2.5 m/s. The behaviour of the VarBC is assessed more precisely for specific aircraft where its capacity to adapt to rapid changes due for example to aircraft maintenance is demonstrated. Moreover, when examining separately predictors for both wind components they appear to converge most of the time towards similar speed and heading corrections. Additional quality controls have allowed to reach background departure values of 2.2 m/s while increasing by a factor of ten the number of aircraft observations to be assimilated in the AROME-France domain.

Validation of Aeolus wind products above the Atlantic Ocean

Abstract. In August 2018, the first Doppler wind lidar in space called Atmospheric Laser Doppler Instrument (ALADIN) was launched on board the satellite Aeolus by the European Space Agency (ESA). Aeolus measures profiles of one horizontal wind component (i.e., mainly the west–east direction) in the troposphere and lower stratosphere on a global basis. Furthermore, profiles of aerosol and cloud properties can be retrieved via the high spectral resolution lidar (HSRL) technique. The Aeolus mission is supposed to improve the quality of weather forecasts and the understanding of atmospheric processes. We used the opportunity to perform a unique validation of the wind products of Aeolus by utilizing the RV Polarstern cruise PS116 from Bremerhaven to Cape Town in November/December 2018. Due to concerted course modifications, six direct intersections with the Aeolus ground track could be achieved in the Atlantic Ocean west of the African continent. For the validation of the Aeolus wind products, we launched additional radiosondes and used the EARLINET/ACTRIS lidar PollyXT for atmospheric scene analysis. The six analyzed cases prove that Aeolus is able to measure horizontal wind speeds in the nearly west–east direction. Good agreements with the radiosonde observations could be achieved for both Aeolus wind products – the winds observed in clean atmospheric regions called Rayleigh winds and the winds obtained in cloud layers called Mie winds (according to the responsible scattering regime). Systematic and statistical errors of the Rayleigh winds were less than 1.5 and 3.3 m s−1, respectively, when compared to radiosonde values averaged to the vertical resolution of Aeolus. For the Mie winds, a systematic and random error of about 1 m s−1 was obtained from the six comparisons in different climate zones. However, it is also shown that the coarse vertical resolution of 2 km in the upper troposphere, which was set in this early mission phase 2 months after launch, led to an underestimation of the maximum wind speed in the jet stream regions. In summary, promising first results of the first wind lidar space mission are shown and prove the concept of Aeolus for global wind observations.

Fenômeno de meandro do vento e a função de autocorrelação calculada com base na concentração de poluentes simulada pelo modelo transiente 3D-GILTT

The aim of this work is to present a pollutants dispersion transient model in low wind conditions to simulate the behavior of the pollutants plume in the atmosphere, considering in the model the u e v horizontal wind components simulated by the LES-PALM model. The dispersion model is based in the advection-diffusion equation and represent by this methodology the wind meandering phenomenon. The Generalized Integral Laplace Transform Technique in three dimensions (3D- GILTT) solves the transient advection-diffusion equation. The data utilized to initialize the simulations are data of the low wind INEL (Idaho National Engineering Laboratory) experiment accomplished in EUA. The results show that the dispersion model reproduces the wind meandering phenomenon, in other words, the autocorrelation function of the concentration simulated over an hour presents the negative lobule, similarly to observed lobules in the u and v wind components. Therefore, the model simulates the pollutants plume in a satisfactory way and can be used to air quality regulatory applications in low wind and wind meandering conditions.