Variability Of Wind Field Research Articles

STUDY ON SENSITIVITY OF WIND FIELD VARIATION TO STRUCTURE AND DEVELOPMENT OF CONVECTIVE STORMS

In order to study the impacts of wind field variations in the middle and lower troposphere on the development and structure of storms, we carried out numerical experiments on cases of severe convection in the Jianghuai area under the background of cold vortex on April 28, 2015. The results show that the structure and development of convective storms are highly sensitive to the changes of wind fields, and the adjustment of wind fields in the middle or lower troposphere will lead to significant changes in the development and structure of storms. When the wind field in the middle or lower troposphere is weakened, the development of convective storms attenuates to some extent compared with that in the control experiment, and the ways of attenuation in the two experiments are different. In the attenuation test of wind field at the middle level, convective storms obviously weaken at all stages in its development, while for the wind field at the low level, the convective storms weaken only in the initial stage of storm. On the contrary, the enhancement of the wind field in the middle or lower troposphere is conducive to the development of convection, especially the enhancement in the middle troposphere. In contrast, the convective storms develop rapidly in this test, as the most intensive one. The wind field variations have significant impacts on the structure and organization of the storm. The enhancement of wind field in the middle troposphere facilitates the intension of the middle-level rotation in convective storm, the reduction of the storm scale, and the organized evolution of convective storms. The strengthening of the wind field in the lower troposphere is conducive to the development of the low-level secondary circulation of the storm and the cyclonic vorticity at the middle and low levels on the inflowing side of the storms.

Seasonal Characteristics of Mesoscale Coupling between the Sea Surface Temperature and Wind Speed in the South China Sea

AbstractThe seasonal characteristics of the mesoscale coupling between sea surface temperature (SST) and wind speed in the South China Sea (SCS) are investigated using satellite observations. The correlation between mesoscale SST and wind speed is highest in winter. The region of high correlation is located in the central SCS in the early stage of the winter monsoon. It then gradually shifts northward in the following months and is located in the northern SCS in the late stage of the winter monsoon. In summer, the region of high correlation is located to the east of the Vietnam coast. Two controlling factors are crucial in mesoscale SST–wind speed coupling: the mesoscale SST gradient and the wind speed steadiness. The mesoscale SST gradient is fundamental in mesoscale coupling, but a steady wind speed also plays an important role. The development of significant coupling depends on the relative contribution of these two factors. For regions where the mesoscale SST gradient is relatively weak, a very steady wind field is required for detectable mesoscale coupling to occur, whereas in regions where the wind speed is less steady, a stronger mesoscale SST gradient must exist for coupling to develop. Variations in wind speed steadiness can well explain the inconsistency between the spatial patterns of the mesoscale SST gradient and the intensity of coupling. The wind speed steadiness is a good factor with which to evaluate the constraining effect of the background wind field variability on the development of mesoscale coupling in the SCS.

CIRCULACIÓN OCEÁNICA DEL GOLFO DE URABÁ USANDO CAMPOS DE VIENTO DE ALTA RESOLUCIÓN TEMPORAL

Los procesos físicos que tienen mayor influencia en la dinámica oceánica al interior del golfo de Urabá son las descargas fluviales, los viento y las diferencias de densidad. La influencia del río Atrato en la circulación se ve afectada por la dinámica de los vientos que se rigen por la variación latitudinal de la Zona de Convergencia Intertropical, que genera dos épocas climáticas: época seca (diciembre a marzo) y época lluviosa (mayo a noviembre). La circulación oceánica del golfo de Urabá (GU) tiene impactos en sus ecosistemas marino-costeros, en la calidad de las aguas, e incluso en las actividades económicas de la zona. Con el propósito de avanzar en el conocimiento hidrodinámico del golfo de Urabá (GU), en este trabajo se analizó la modulación que producen los vientos sobre las corrientes en esta zona para la escala intra e interanual. Se utilizó el modelo numérico de circulación oceánica regional CROCO, bajo un forzamiento atmosférico de tiempo variable durante el periodo 2010-2015. Se encontró que, teniendo en cuenta solo el forzamiento del viento, el golfo puede dividirse dinámicamente en tres zonas (norte, centro y sur). Los resultados sugieren que la modulación del viento a la circulación del golfo de Urabá, confina las aguas dulces en el sur cuando su dirección (norte-sur) es contraria al flujo del río Atrato. En este escenario se encontraron las menores magnitudes de la corriente superficial, principalmente para la zona centro y sur, con valores promedio de 0.1 m/s. En este caso, el mar Caribe tiene una mayor influencia sobre la circulación en su parte profunda. Cuando el esfuerzo del viento está en la misma dirección del flujo del río Atrato (sur-norte), las corrientes superficiales siguen esa dirección, con aguas saliendo del golfo por su costado este (escenario común). Se encontró, además, que la descarga fluvial de los ríos al interior del golfo tiene influencia en gran parte de su área aproximadamente hasta los 3 m de profundidad. Entre los 4 m y 8 m se encuentra la haloclína, formada por la transición de aguas dulces a saladas. En esta profundidad se forma un corte de velocidades, que permite la formación de remolinos en las aguas profundas del golfo. Finalmente, a partir de los 10 m es notoria la influencia de algunos sistemas de corrientes del mar Caribe en la circulación del golfo. Cabe resaltar que en bahía Colombia se encontró un flujo de tres capas con un corte de velocidades casi permanente, dando lugar a una mayor circulación de las masas de agua en JAS y un mayor intercambio de flujo en la zona central del GU. Por último, los resultados sugieren que en el periodo de tiempo analizado las fases del ENSO no modulan la variación atmosférica y oceánica al interior del golfo de Urabá, debido a que en esta zona dominan los fenómenos locales. En trabajos futuros se recomienda emplear bases de datos de viento con una resolución espacial fina y tener en cuenta el aporte de otros afluentes importantes como el río León.

Impact of model resolution on the representation of the wind speed field: An example from the United Kingdom

AbstractThe United Kingdom (UK) is experiencing rapid growth in wind farm development, primarily in the south as well as in offshore regions. As such, reliable long‐term wind statistics are integral in planning future development. Given the scarcity of in situ data, atmospheric reanalyses are beginning to be used for this purpose. However, most reanalyses have resolutions of ∼50 km or lower – scales too coarse to capture many topographic and coastal effects. To address this, dynamical downscaling has been used to obtain higher‐resolution data. However, it is unclear how the downscaling process impacts the temporal and spatial representation of the wind field. Here a set of reanalysis and analysis datasets with a common lineage and with horizontal resolutions ranging from ∼75 to ∼9 km are used to investigate the impact of model resolution on the representation of the spatial and temporal variability in the wind field in the UK. To assess this impact, the decorrelation length and temporal scale – DCLS and DCTS, respectively – are used to characterize spatial and temporal variability. The results can be classified into two categories – resolution‐dependent and resolution‐independent features. Resolution‐dependent results suggest that even resolutions of ∼30 km do not capture the wind field's variability, especially in coastal and mountainous regions. However, resolution‐independent results suggest that there are regions, such as central Ireland, over the oceans, and southeastern England, where the 30 km resolution captures the wind fields' variability. Results also support the historic choice of wind farm development in the UK, namely, the southern/southwestern tip of England as well as off the southern shore.

Concurrent Field Experiments and Satellite Surveys for Assessing Environmental Risk in the Coastal Zone of Southeast Baltic

The results of field experiments concurrent to satellite surveys conducted in the summer periods of 2014-2019 in the southeastern part of the Baltic Sea off Sambian Peninsula are presented. The main goal was to study coastal currents in a highly variable wind field and its impact on the transport of potential marine pollution. Southeast Baltic is, on the one hand, an area of active navigation, fishing, off-shore oil production, and, on the other hand, a rapidly developing recreation area. It is also an area of frequent massive blooming of harmful algae. Considering these facts, studying coastal currents and their impact on antropogenic and biogenic pollution propagation in the area is highly important. Our main research instrument was drifting Lagrangian buoys (mini-drifters) that are quite often used in oceanography today, Acoustic Doppler Current Profiler (ADCP) and CTD probe measuring temperature, conductivity (salinity) and pressure (depth) and in-situ turbidity and CHL-a In addition, we used satellite remote sensing data publicly available from European and American databases. Mainly, these were data obtained from Sentinel-2 (MSI), Landsat-8 (OLI/TIRS), Sentinel-3 (OLCI) and MODIS (Aqua/Terra) satellites. The experimental data allowed us to describe in detail the alongshore current structure and identify the areas most affected by marine pollution, among which are the most popular places of the region: the beaches of the Yantarniy settlement and Curonian Spit, a national nature reserve and a UNESCO World Heritage Site.

Storm-time mesoscale field-aligned currents and interplanetary parameters

Present paper studies Field aligned currents (FACs) estimated by employing Ampere's law to the magnetic field recorded by CHAMP satellite during 24 geomagnetic storms. Low-pass filtered FACs with a cutoff period of 20 s (scale size~150 km) are used to determine FAC range, which is defined as a peak-to-peak amplitude of FAC density. Thus we are considering only the strongest positive and negative FACs emerging either from Region 1, Region 2, Region 0, or substorm current wedge systems. It is known that the FACs significantly depend on the highly variable solar wind (SW) and interplanetary magnetic field (IMF) conditions and also on the processes internal to magnetospheric-ionospheric system such as substorm. The correlation analysis carried out here shows that sometimes the FAC range, correlates well with SymH, AsyH, AsyD, AL, am and Kp indices (>95% significance), but not always. The variation of the FAC range with magnetic local times shows distinctly different patterns during southward and northward IMF conditions, with peaks near dawn-dusk during southward IMF and near local noon-midnight during northward IMF. These results are in agreement with the earlier reports. However, the seasonal dependence reveals that the noon time peak is essentially associated with the summer season. We have determined a new parameter called ‘occurrence rate of FAC range ≥1 μA/m2’ and examined it under various solar wind and IMF conditions. It is found that the probability of FAC range ≥1 μA/m2 have a clear dependence on the clock angle, suggesting more frequent intensifications during southward IMF. Clear linear dependence on the cone angle demonstrates higher occurrence probability of FAC range ≥ 1 μA/m2 when the IMF is perpendicular to the Sun-Earth line (cone angle nearing 90°). All these results based on the newly defined parameters such as FAC range and probability of FAC range ≥1 μA/m2, for the storm time mesoscale FAC are consistent with the previous studies. The FAC ranges are found to have a linear dependence on the values of IMF BY, BYZ, BT and BZ, though saturation is apparent at higher values of the IMF parameters. FAC range shows distinctly different dependence for slow and fast solar wind, suggesting the importance of the composition and properties of SW in controlling the FAC strengths.

Estimating power plant CO2 emission using OCO-2 XCO2 and high resolution WRF-Chem simulations

Anthropogenic CO2 emission from fossil fuel combustion has major impacts on the global climate. The Orbiting Carbon Observatory 2 (OCO-2) observations have previously been used to estimate individual power plant emissions with a Gaussian plume model assuming constant wind fields. The present work assesses the feasibility of estimating power plant CO2 emission using high resolution chemistry transport model simulations with OCO-2 observation data. In the new framework, 1.33 km Weather Research and Forecasting-Chem (WRF)-Chem simulation results are used to calculate the Jacobian matrix, which is then used with the OCO-2 XCO2 data to obtain power plant daily mean emission rates, through a maximum likelihood estimation. We applied the framework to the seven OCO-2 observations of near mid-to-large coal burning power plants identified in Nassar et al (2017 Geophys. Res. Lett. 44, 10045–53). Our estimation results closely match the reported emission rates at the Westar power plant (Kansas, USA), with a reported value of 26.67 ktCO2/day, and our estimated value at 25.82–26.47 ktCO2/day using OCO-2 v8 data, and 22.09–22.80 ktCO2/day using v9 data. At Ghent, KY, USA, our estimations using three versions (v7, v8, and v9) range from 9.84–20.40 ktCO2/day, which are substantially lower than the reported value (29.17 ktCO2/day). We attribute this difference to diminished WRF-Chem wind field simulation accuracy. The results from the seven cases indicate that accurate estimation requires accurate meteorological simulations and high quality XCO2 data. In addition, the strength and orientation (relative to the OCO-2 ground track) of the XCO2 enhancement are important for accurate and reliable estimation. Compared with the Gaussian plume model based approach, the high resolution WRF-Chem simulation based approach provides a framework for addressing varying wind fields, and possible expansion to city level emission estimation.

Doppler Radar Measurements of Spatial Turbulence Intensity in the Atmospheric Boundary Layer

AbstractRemote sensing instruments that scan have the ability to provide high-resolution spatial measurements of atmospheric boundary layer winds across a region. However, the time required to collect the volume of measurements used to produce this spatial representation of atmospheric winds typically limits the extraction of atmospheric turbulence information using traditional temporal analysis techniques. To overcome this constraint, a spatial turbulence intensity (STI) metric was developed to quantify atmospheric turbulence intensity (TI) through analysis of spatial wind field variability. The methods used to determine STI can be applied throughout the measurement domain to transform the spatially distributed velocity fields to analogous measurement maps of STI. This method enables a comprehensive spatial characterization of atmospheric TI. STI efficacy was examined across a range of wind speeds and atmospheric stability regimes using both single- and dual-Doppler measurements. STI demonstrated the ability to capture rapid fluctuations in TI and was able to discern large-scale TI trends consistent with the early evening transition. The ability to spatially depict atmospheric TI could benefit a variety of research disciplines such as the wind energy industry, where an understanding of wind plant complex flow spatiotemporal variability is limited.

Simulation of Hurricane Wind Fields for Community Resilience Applications: A Data-Driven Approach Using Integrated Asymmetric Holland Models for Inner and Outer Core Regions

AbstractAccurate modeling of the damage caused by hurricanes making landfall to physical infrastructure relies on the accurate modeling of temporally and spatially varying wind fields. However, win...

Modeling Study of the Air Quality Impact of Record-Breaking Southern California Wildfires in December 2017.

We investigate the air quality impact of record-breaking wildfires in Southern California during 5-18 December 2017 using the Weather Research and Forecasting model with Chemistry in combination with satellite and surface observations. This wildfire event was driven by dry and strong offshore Santa Ana winds, which played a critical role in fire formation and air pollutant transport. By utilizing fire emissions derived from the high-resolution (375 × 375 m2) Visible Infrared Imaging Radiometer Suite active fire detections, the simulated magnitude and temporal evolution of fine particulate matter (PM2.5) concentrations agree reasonably well with surface observations (normalized mean bias = 4.0%). Meanwhile, the model could generally capture the spatial pattern of aerosol optical depth from satellite observations. Sensitivity tests reveal that using a high spatial resolution for fire emissions and a reasonable treatment of plume rise (a fair split between emissions injected at surface and those lifted to upper levels) is important for achieving decent PM2.5 simulation results. Biases in PM2.5 simulation are relatively large (about 50%) during the period with the strongest Santa Ana wind, due to a possible underestimation of burning area and uncertainty in wind field variation. The 2017 December fire event increases the 14-day averaged PM2.5 concentrations by up to 231.2 μg/m3 over the downwind regions, which substantially exceeds the U.S. air quality standards, potentially leading to adverse health impacts. The human exposure to fire-induced PM2.5 accounts for 14-42% of the annual total PM2.5 exposure in areas impacted by the fire plumes.

The impact of wind field spatial heterogeneity and variability on short-term wind power forecast errors

Wind power is associated with uncertainties in scheduling and dispatching to the power grid, because the availability of wind speed is unknown in advance, and precise wind power forecasts are crucial to reducing these uncertainties. However, the accuracy of the wind power prediction, which is driven by average wind speed forecasting, is influenced by the spatial variability of the wind field. In this paper, the mechanisms of how wind power prediction errors are caused by the spatial heterogeneity of wind speeds and wind turbine power curves are analyzed. The degree of spatial heterogeneity of wind farms and errors caused by this are defined, and the relationships between various errors are revealed. We choose wind data collected from one observation site in northeast China as a sample; the results indicate that the short-term wind power prediction error is mainly caused by the inhomogeneity of the power curves. Moreover, these forecast errors can vary with season and installed wind farm capacity.

Predicting Wave‐Induced Sediment Resuspension at the Perimeter of Lakes Using a Steady‐State Spectral Wave Model

AbstractA steady‐state spectral wave model, STWAVE, is evaluated as a tool for predicting wave‐induced sediment resuspension in lake littoral zones. Steady‐state wave height and bed‐shear stress estimates are tested against 2 years of high‐frequency wave height and turbidity data from six littoral measurement stations in Lake Tahoe. Average wave and sediment resuspension response to a broad range of wind conditions are well captured by the model. Despite steady‐state assumptions, the model reproduces patterns in wave height and sediment resuspension under time‐varying wind conditions at sites with different wave exposure. Model results are insensitive to the measurement location of wind data input among six offshore meteorological buoys. Uniform and variable wind field assumptions yield similar resuspension predictions. Results representing the steady‐state response to spatially uniform wind speed‐direction combinations enable output from a single set of model runs to serve as a reasonable static reference for hindcasting and predicting wave resuspension patterns. This obviates the need for repeated model runs, making STWAVE output an efficient tool for exploring long‐term spatio‐temporal patterns in nearshore wave forcing. Application of this tool is limited by wave height overprediction for short fetches and presumably by the validity of uniform wind field assumptions over very long fetches. Applied successfully at Lake Tahoe, we find that the north and east shores, exposed to the prevailing southwesterly winds, see resuspension conditions upward of 3,000 hr/year, while the south and west shores typically see less than 500. Location‐specific resuspension hours can vary by upward of ±200 hr/year due to shifting interannual wind patterns.

Feature analysis of stratospheric wind and temperature fields over the Antigua site by rocket data

The wind and temperature fields at 20 to 55 km above the Antigua launch site (17°N, 61°W) were analyzed by using sounding rocket data published by the research organization on Stratosphere-Troposphere Processes and their Role in Climate (SPARC). The results showed distinct variations in the wind and temperature fields at different heights from the 1960s to the 1990s. The overall zonal wind speed showed a significant increasing trend with the year, and the overall change in meridional wind speed showed a falling trend from 1976 to 1990, whereas the temperature field showed a significant cooling trend from 1964 to 1990. The times the trends mutated varied at different levels. By taking the altitudes at 20, 35, and 50 km as representatives, we found that the zonal wind speed trend had mutated in 1988, 1986, and 1986, respectively; that the meridional wind speed trend had mutated in 1990, 1986, and 1990, respectively; and that the temperature trend had mutated separately in 1977, 1973, and 1967, respectively. Characteristics of the periodic wind and temperature field variations at different heights were also analyzed, and obvious differences were found in time scale variations across the different layers. The zonal and meridional wind fields were basically characterized as having a significant periodic variation of 5 years across the three layers, and each level was characterized as having a periodic variation of less than 5 years. Temperature field variation at the three levels was basically characterized as occurring in 10-year and 5-year cycles.

Estimation of winter time NOx emissions in Hefei, a typical inland city of China, using mobile MAX-DOAS observations

In this paper, we present a quantitative determination of the NOx emission in Hefei using mobile Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements. The measurements were carried out during winter time from December 2016 to February 2017. The measured NO2 vertical column densities (VCDs) show a strong spatial gradient with higher values within the city center, indicating the majority of NOx emission sources are located at the city center. A significant “holiday effect” was found by comparing measurements taken during weekdays and weekend. The weekend reduction is more significant in the suburban (∼28%) compared to the city center (∼13%). Mobile measurements of NO2 vertical column densities (VCDs) were analyzed together with meteorological data to determine the NOx emission by applying the loop-integral method. Detailed error analysis of the NOx emission shows the variation of wind field and large measurement gap dominated the total error of NOx emission calculation. The result shows the NOx emission in Hefei during winter time varies in a wide range from 10 × 1024 to 40 × 1024molecs−1 with an average of 18.44 × 1024molecs−1. Our estimation is about 43% lower than the number reported in the previous emission inventory in 2012. The reduction of NOx emission reflects the successful implementation of emission control measures in recent years. Our result also shows about 73% of the total NOx in the city were transported from outside of the city during winter. The impacts of transported NOx are especially large when air masses originated from heavily polluted regions, i.e. North China Plain and Yangtze River Delta. The result presented provides a better understanding of the impacts of local emissions and transportation of pollutants on the local air quality of Hefei.

Site-specific data-driven probabilistic wind field modeling for the wind-induced response prediction of cable-supported bridges

In this study, full-scale wind velocity measurements are conducted at eight locations on the Hardanger Bridge girder to investigate the possibility of a probabilistic representation of the turbulence field along the bridge span. Using appropriate assumptions, the two-dimensional turbulence field along the structure is reduced to six turbulence parameters, which are considered as correlated lognormally distributed random variables. The directionality and wind speed dependence of the parameters are demonstrated by means of wind roses and scatter diagrams. Depending on the wind speed and direction, simulations of the turbulence field were carried out using random number generators. The performance of simulated wind fields in capturing the variability and correlation structures of an actual wind field at a site is tested by detailed comparisons with the measurement data. For the sake of illustration, simulations were also performed for the design wind speed of the Hardanger Bridge using the current model and another model from the literature. The resulting probabilistic model is suitable for implementation in reliability-based frameworks and long-term extreme response analysis.

Wind Dynamics Over a Highly Heterogeneous Oasis Area: An Experimental and Numerical Study

AbstractOases are unique heterogeneous landscapes that coexist within the Gobi desert in the arid and semiarid regions, which are vital for agricultural production and economic development. The heterogeneity of the land surface with vegetation will significantly influence the wind dynamics and airflow characteristics. The current study utilized an integrated approach, combining the computational fluid dynamics (CFD) method with the k‐ɛ turbulence model and high‐resolution ground‐measurement data to analyze the wind dynamics over an oasis. Specifically, (1) the Weather Research and Forecast model (WRF) data were used as boundary conditions to initiate the simulations; (2) the canopy leaf area density estimated from airborne laser scanning data was added as the source terms of the momentum and turbulence transport equations, which represented the highly heterogeneous vegetation structures in the oasis area. CFD‐simulated wind field results agreed well with the flux observation matrix data (17 tower measurements in a 5.5 km × 5.5 km experimental area). The spatial and temporal variations of wind fields affected by heterogeneous land surfaces were successfully captured. The CFD‐simulated wind fields also clearly showed the “wind shield effect” over highly heterogeneous land surfaces, wherein the existence of shorter and longer wind speed reduction areas at the windward and leeward sides of the shelterbelts contribute to protecting farmlands and orchards from wind erosion. In addition, the current approach of estimating aerodynamic roughness length (z0m) based on high‐resolution CFD‐simulated wind profiles was demonstrated to be a promising method of capturing wind dynamics over heterogeneous surfaces.

Characterization of a two-dimensional static wind field using Radial Basis Functions

Radial Basis Functions are a modern way of creating a regression model of a multivariate function when sampled data points are not uniformly distributed in a perfect grid. Radial Basis Functions are well suited to atmospheric characterization when unmanned aerial vehicles (UAVs) are used to sample the given space. Multiple UAVs reduce the time for the Radial Basis Functions to yield a suitable solution to the measured data while data from all aircraft are aggregated and sent to Radial Basis Functions to fit the data. The research presented here focuses on the requirements for a high correlation value between the sampled data and the actual data. It is found that the number of centers is a large driver of the goodness of fit in the Radial Basis Function routine, much like aliasing is an issue in sampling a sinusoidal function. These centers act like a sampling rate for the spatially varying wind field. If the centers are dense enough to fully capture the spatial frequency of the wind field, the Radial Basis Functions will produce a suitable fit. This also requires the number of data points to be larger than the number of centers. The ratio between the number of centers and number of sampled data points declines as the number of centers increases. The results presented here are revealed using a two-dimensional Fourier series analysis coupled to a spatially varying atmospheric wind model and a Radial Basis Function regression model.

Evaluation of mast measurements and wind tunnel terrain models to describe spatially variable wind field characteristics for long-span bridge design

The quality of the information about the wind field characteristics is crucial for accurately predicting the structural response of a long-span bridge subjected to dynamic wind loads. In this paper, in situ mast measurements and terrain model wind tunnel tests are compared with full-scale measurements of the wind field along the Hardanger Bridge girder. The aim is to investigate the performance of mast measurements and wind tunnel terrain model tests in predicting the wind field characteristics for long-span bridges in complex terrains. Wind field spatial variations and statistical distributions for the mean wind velocity and turbulence intensity are investigated. Extreme value statistics have been applied to compare the mean wind velocity recordings from two different measurement periods. Results showing terrain-induced effects on the wind directions, turbulence intensities and mean wind velocities are presented. Simultaneous spanwise wind profiles for the mean wind velocity and along-wind turbulence intensity are compared between the terrain model wind tunnel tests and the full-scale measurements, and large nonuniformities are identified. The extreme profiles of the turbulence intensities vary as much as 100% along the span, and the mean wind velocity profiles vary up to 50% along the span.

Air Data Estimation by Fusing Navigation System and Flight Control System

A novel synthetic air data estimation method without using air data sensors is presented, and the method only relies on the information from the Navigation System (NS) and Flight Control System (FCS). The aircraft's aerodynamic model is also required to make a connection between the FCS control parameters and the NS measurements. The airspeed, angle of attack and sideslip, angular velocity and wind speed are defined as state vectors, and state equations are established through the aircraft's aerodynamic model and dynamics. Linear velocity and angular velocity provided by the navigation system are considered as the measurement vector. To deal with variable wind fields, a novel Initialised Three-step Extended Kalman Filter (ITEKF), which considers the wind speed as an unknown input, is developed to track the variation of wind speed. Simulation results based on a Generic Hypersonic Vehicle (GHV) model are presented and compared with an existing method. Factors affecting the method's accuracy include the navigation system accuracy and the aerodynamic model error, are also discussed.

In-flight wind identification and soft landing control for autonomous unmanned powered parafoils

ABSTRACTFor autonomous unmanned powered parafoil, the ability to perform a final flare manoeuvre against the wind direction can allow a considerable reduction of horizontal and vertical velocities at impact, enabling a soft landing for a safe delivery of sensible loads; the lack of knowledge about the surface-layer winds will result in messing up terminal flare manoeuvre. Moreover, unknown or erroneous winds can also prevent the parafoil system from reaching the target area. To realize accurate trajectory tracking and terminal soft landing in the unknown wind environment, an efficient in-flight wind identification method merely using Global Positioning System (GPS) data and recursive least square method is proposed to online identify the variable wind information. Furthermore, a novel linear extended state observation filter is proposed to filter the groundspeed of the powered parafoil system calculated by the GPS information to provide a best estimation of the present wind during flight. Simulation experiments and real airdrop tests demonstrate the great ability of this method to in-flight identify the variable wind field, and it can benefit the powered parafoil system to fulfil accurate tracking control and a soft landing in the unknown wind field with high landing accuracy and strong wind-resistance ability.