Wind Measurement Errors Research Articles

Implementation and simulation of direct Doppler wind measurement technology under regime of multi-longitudinal mode laser

<sec>Single-longitudinal-mode (SLM) direct Doppler wind lidar (DDWL) requires complex techniques of the seed injection, high precision frequency stability, and frequency locking to provide an output of the stable frequency SLM laser, resulting in a complex structure of DDWL. To reduce the technical difficulty and structural complexity of the excitation light source of DDWL, a multi-longitudinal mode (MLM) DDWL is proposed. In the MLM DDWL, a free-running MLM laser is directly used as an excitation light source and quadri-channel Mach-Zender interferometer (QMZI) with four periodic outputs is adopted as a spectral discriminator.</sec><sec>Firstly, for the typical Nd:YAG pulsed laser, the scattering spectra of atmospheric elastic echo excited by the MLM laser are analyzed which are coincident with the longitudinal modes of the MLM laser. The peaks of atmospheric elastic echo scattering spectra excited by the MLM laser overlap with each other. The overlaping degree is affected by the laser radiation linewidth, laser optical resonator length, laser center wavelength, and type of scattering particles. In addition, the scattering spectra of atmospheric elastic echo excited by each longitudinal mode of the MLM laser have the Doppler frequency shift introduced by atmospheric wind. Therefore, it is necessary to select an optical interferometer with the periodic transmittance curve as the spectral discriminator of MLM DDWL.</sec><sec>Subsequently, a QMZI is designed as the spectral discriminator to achieve high-precision measurement for the Doppler frequency shift of scattering spectra of atmospheric elastic echo excited by the MLM laser. The designed QMZI has four periodic output channels and the phase difference between adjacent channels is π/2. The mathematical model of the transmittance function of the QMZI is established. The effective transmittance of the QMZI for atmospheric elastic echo scattering spectrum excited by the MLM laser is analyzed based on the partial coherence theory of quasi-monochromatic light interference and the polarization effect of light. On this basis, the data inversion algorithm of MLM DDWL is constructed.</sec><sec>Finally, the simulation experiments of wind measurement are carried out. The QMZI simulation model is built by the non-sequential mode of Zemax optical simulation software. The atmospheric elastic echo scattering spectra excited by the MLM laser are configured by the SPCD files of Zemax optical simulation software under different theoretical wind speeds ranging from -50 to 50 m/s, laser optical resonator lengths (<i>L</i> = 30 mm and 300 mm), and laser center wavelengths (<i>λ</i> = 1064 nm, 532 nm, and355 nm). The SPCD files are fed to the QMZI simulation model as input signals. At the same time, the ray tracing on input signal is performed based on the principle of Monte Carlo simulation s, and the output signals of the four channels of the QMZI simulation model are recorded to retrieve the atmospheric wind information. The simulation results show that the proposed MLM DDWL can achieve high-precision measurement of atmospheric wind information. With the laser optical resonator length of 300 mm and laser center wavelengths <i>λ</i> = 1064 nm, <i>λ</i> = 532 nm, <i>λ</i> = 355 nm, the maximum detectable wind speeds of MLM DDWL are about 50 m/s, 30 m/s, and 20 m/s, and the wind measurement errors can be controlled within 2.5 m/s, 3.0 m/s, and 4.0 m/s, respectively. When the center wavelength of each laser is 532 nm, and the lengths of laser optical resonator are 30 mm and 300 mm, then the maximum detectable wind speeds of MLM DDWL are about 50 m/s and 30 m/s, and the wind measurement errors can be controlled within 2.0 m/s and 3.0 m/s, respectively. Therefore, the longer the laser center wavelength and the shorter the laser optical resonator length, the larger the wind measurement range will be and the smaller the wind measurement error.</sec>

Detection of Atmospheric Wind Speed by Lidar Based on Quadrichannel Mach–Zehnder Interferometer

For a long time, wind speed profile measurement has been the primary task of weather forecasting. Therefore, the detection of atmospheric wind speed is extremely important for studying the changes in atmospheric motion. In order to solve the problems of insufficient data collection, low resolution, and low accuracy in atmospheric wind field detection, this paper introduces the relevant theories of wind speed detection, completes the optical design of the system according to the research objectives, and determines the selection of optical devices. At the same time, a Doppler wind lidar system based on a quadrichannel Mach–Zehnder interferometer is designed and built to carry out ground-based observation experiments, collect echo signal data, and inverse the atmospheric radial wind speed. Furthermore, the wind measurement error is analyzed. Firstly, the paper introduces the basic principle of the wind measurement system, i.e., using the Doppler effect of light, and then analyzes the frequency discrimination device of the system in detail, and obtains the theoretical calculation method of atmospheric wind speed inversion. At the same time, the relevant datasets of wind measurement system are analyzed, including backscattering ratio, aerosol, and molecular extinction coefficient, and the emission mechanism of the large pulse laser is also studied in detail, which provides a theoretical basis for the model construction of Doppler lidar and the research on the enhancement of pulsed laser emission energy. Secondly, according to the research index of wind measurement, a Doppler wind measurement lidar system based on a quadrichannel Mach–Zehnder interferometer is designed, including the design of ab external light path transceiver system, internal light path interferometer, software and hardware, and algorithm. The calibration of the quadrichannel Mach–Zehnder interferometer is completed, with its maximum interference contrast reaching 0.869. Through the self-developed optical transceiver system and data acquisition system, the echo signal of lidar is received and detected. Lastly, the data of echo signals collected by the interferometer are analyzed, the radial atmospheric wind speed profile is inversed, and the signal-to-noise ratio and wind speed measurement error of the system are evaluated. The experimental results show that the maximum signal-to-noise ratio (SNR) of the system can reach 1433 when the emission pulse energy of the large pulse laser is adjusted to 255 mJ, and the farthest wind speed detection distance is about 8 km. The high-precision wind speed detection range can reach 2 km, the actual wind measurement errors in this range are all within 1.593 m/s, and the minimum error is only 0.418 m/s. In addition, the backscattering coefficient and extinction coefficient of atmospheric molecules and aerosols in the range of 8 km and the atmospheric temperature in the range of 10 km are also measured. The measurement accuracy of the aerosol extinction coefficient is ±0.001 m−1, and the measurement error of atmospheric temperature within 10 km is within 2 K, achieving the expected goals.

Research on wind direction measurement of wind turbine based on fluid simulation

For horizontal-axis wind turbines, wind turbines typically alignment nacelle to the wind using yaw system, realizing max energy capture. If the wind turbine’s nacelle has a large error to the wind, the captured wind energy loss will be large, and it will also cause an increase in the load of the unit, which will pose a major risk to the safety of the wind turbine. Affecting the wind measurement error in addition to the performance of the sensor itself, the installation position of the wind measurement equipment also accounts for an important factor, this paper on the basis of the calculation of fluid dynamics simulation results, through the lateral and longitudinal comparison of the simulation results, pointed out the best installation location of the wind direction sensor, optimize the loss caused by wind measurement error of wind turbine in design, and provide guidance for the installation of the wind direction sensor on site.

A comparative study of three methods to detect the upper atmospheric wind speed by DASH

The DASH (Doppler asymmetric spatial heterodyne) is used to detect the upper atmospheric wind speed by its imaging Fizeau interference fringes. There are two wind measurement methods: Fourier series method (FSM) and popular Fourier transform method (FTM). However, the wind speed measurement accuracy of FTM is greatly influenced by window function, and the calculation is relatively complicated. The Four-point algorithm (FPA) for DASH’s wind speed measurement is proposed in this paper. The contents of wind speed measurement principle, forward modeling, noise and inversion by the FSM, FTM and FPA are wholly compared and studied. The three wind speed measurement methods are all derived from the phase difference transformation of DASH Fizeau interference fringes. The Fizeau interference fringes with wind speed of 0–100 m/s at the interval of 10 m/s are simulated, and the forward wind speeds are obtained by FSM, FTM and FPA, and the corresponding wind measurement errors are 2.93%, 4.67% and 3.00%, respectively. After artificially adding Gaussian noise with a mean value of 0 and a standard deviation of 0.1, FSM, FTM and FPA are used to forward the Fizeau interference fringes after flat field, and the corresponding relative errors are 2.30%, 11.66% and 2.27%, respectively. After artificially adding Gaussian noise, the Fizeau interference fringes of wind speeds of 31–39 m/s with 1 m/s interval and 30.1–30.9 m/s with 0.1 m/s interval are simulated, and the forward wind speeds are obtained by FSM and FPA. In both cases, the wind speed measurement errors of FSM are 3.55% and 4.15% higher than those of FPA. The O(<sup>1</sup>S) 557.7 nm airglow at peak altitude of 98 km in Xi’an was photographed by using our GBAII (ground based airglow imaging interferometer)-DASH, and the imaging interferograms with zenith angles of 0° and 45° were obtained. Then by the methods of Fourier series, Fourier transform and FPA are used to obtain the inversion wind speed of 32.21 m/s, 43.55 m/s and 32.17 m/s, respectively. From the forward and inversion results of DASH, we can see that the FPA has a better result for detecting the upper atmospheric wind due to its simple calculation and smaller wind measurement error.

Modification of DFIG's Active Power Control Loop for Speed Control Enhancement and Inertial Frequency Response

This paper proposes a fuzzy-based speed controller for the doubly fed induction generator (DFIG)-based wind turbines with the rotor speed and wind speed inputs. The controller parameters are optimized using the particle swarm optimization algorithm. To accelerate tracking the maximum power point trajectory, the conventional controller is augmented with a feed-forward compensator, which uses the wind speed input and includes a high-pass filter. The proposed combined speed controller is robust against wind measurement errors and as the accuracy of anemometers increases the speed regulation tends toward the ideal controller. The cutoff frequency of the applied filter is determined considering a compromise between the sensitivity to measurement errors and speed of regulation process. We also design an auxiliary frequency controller to equip the DFIGs with an inertial frequency response. In the proposed controller, two important constraints are taken into account: the feasible rotor speed range during the injection period, and the minimum time to recover the DFIG's speed. The impacts of the proposed controllers are evaluated through extensive time-domain simulations on an IEEE 9-bus test system using the DIgSILENT/PowerFactory software. Results confirm the effectiveness of the proposed controllers in serious transients and load disturbances.

Mean wind vector estimation using the velocity–azimuth display (VAD) method: an explicit algebraic solution

Abstract. This paper deals with the analysis of the sampling setup for Doppler profilers aiming at the determination of vertical profiles of the wind. An explicit solution for the retrieval of mean wind vectors under the assumption of local homogeneity is presented for the case of a symmetric velocity–azimuth display sampling, and a stability analysis is performed. Furthermore, the explicit solution allows a detailed investigation of the propagation of radial wind measurement errors on the retrieved wind vector.

A Tiny Fabry-Perot Interferometer with Postpositional Filter for Measurement of the Thermospheric Wind

A tiny and low-cost ground-based Fabry-Perot interferometer (FPI) was designed using a filter behind etalon and Galilean telescope system for the thermospheric wind observation with OI 630.0 nm nightglow emissions (~250 km). Based on the instrument, experiments were carried out at Langfang (39.40° N, 116.65° E) site for a rough comparison and Kelan (38.71° N, 111.58° E) site for a detailed validation. Wind results of Langfang experiment are well consistent with measurements of two other FPIs deployed at Xinglong (40.40° N, 117.59° E) and Kelan which are retrieved by the American National Center for Atmospheric Research (A-NCAR). In Kelan experiment, the averaged wind deviation between our FPI and A-NCAR FPI is 11.8 m/s. The averaged deviation of wind measurement error between them is 2.9 m/s. The comparisons suggest good agreement. Then, the analysis of influencing factors was made. The center determination offset has an exponential relation with wind deviation, while the radius calculation offset is linear with wind deviation.

Representativeness of wind measurements in fire experiments: Lessons learned from large-eddy simulations in a homogeneous forest

Experimental fires often aim to relate fire behavior to fuel and weather conditions, such as wind speeds. These experiments are typically limited to short durations (∼300s) and small lateral extents (∼100m). Although most studies include measurements of wind velocities, such measurements are often taken at some distance from the fire experiments, and may not represent conditions at the fire location. This disparity may potentially introduce errors of unknown magnitude in empirical models based upon the data collected. At present, little guidance is available regarding how well remote anemometry measurements are actually representative of wind velocities at the fire front. A number of factors may affect this representativeness, including the fire itself (size, spread rate and duration), the reference height for fire wind measurement, the sensors (number and location), the vegetation, and weather conditions (wind speed and atmospheric stability).In the present study, we use large-eddy simulations of wind flows to compute fire-front wind (at a virtual moving fire line) and measured wind (at anemometer locations) corresponding to hypothetical fire experiments. Replicates of these hypothetical experiments were used to quantify wind measurement representativeness, by computing the errors resulting from the estimation of the fire-front wind by remote anemometers. We then examine the sensitivity of these errors to the factors mentioned above.We found that the main factors were the size of the experiment, the reference height for wind measurement, the ratio of ambient wind speed to expected spread rate, and the number of sensors. Convective instability and distance between anemometers and fire plots played a minor role in most cases. We propose a simple model to characterize this error as it is influenced by the main factors.The simple model reproduces and generalizes outcomes reported by an earlier field study and shows a clear picture of the respective role of the factors cited above. It can be used to estimate errors in wind measurement in completed experiments. Practical guidelines are provided to apply this model to the design of future experiments.

Direct-detection Doppler wind measurements with a Cabannes–Mie lidar: B Impact of aerosol variation on iodine vapor filter methods

Atmospheric line-of-sight (LOS) wind measurement by means of incoherent Cabannes- Mie lidar with three frequency analyzers, two double-edge Fabry-Perot interferometers, one at 1064 nm (IR-FPI) and another at 355 nm (UV-FPI), as well as an iodine vapor filter (IVF) at 532 nm, utilizing either a single absorption edge, single edge (se-IVF), or both absorption edges, double edge (de-IVF), was considered in a companion paper [Appl. Opt. 46, 4434 (2007)], assuming known atmospheric temperature and aerosol mixing ratio, Rb. The effects of temperature and aerosol variations on the uncertainty of LOS wind measurements are investigated and it is found that while the effect of temperature variation is small, the variation in R(b) can cause significant errors in wind measurements with IVF systems. Thus the means to incorporate a credible determination of R(b) into the wind measurement are presented as well as an assessment of the impact on wind measurement uncertainty. Unlike with IVF methods, researchers can take advantage of design flexibility with FPI methods to desensitize either molecular scattering for IR-FPI or aerosol scattering for UV-FPI. The additional wind measurement uncertainty caused by R(b) variation with FPI methods is thus negligible for these configurations. Assuming 100,000 photons from Cabannes scattering, and accounting for the Rb measurement incorporated into the IVF method in this paper, it is found that the lowest wind uncertainty at low wind speeds in aerosol-free air is still with UV-FPI, ~32% lower than with de-IVF. For 0.05<R(b)<0.07, the LOS wind uncertainty is lowest with de-IVF, and for R(b)>0.07, the IR-FPI outperforms all other methods. In addition to LOS wind uncertainty comparison under high wind speed conditions, the need of an appropriate and readily available narrowband filter for operating the wind lidar at visible wavelengths under sunlit condition is discussed; with such a filter the degradation of LOS wind measurement attributable to clear sky background is estimated to be 5% or less for practical lidar systems.

The detection of hurricane asymmetries from aircraft reconnaissance flight data: Some simulation experiments

A series of observational system simulation experiments designed to investigate the data requirements for determining the flow asymmetry of a hurricane are described. Of particular interest is the azimuthal wave-number-one component of the asymmetry, which, together with the mean flow across the storm, is responsible for the storm motion. A principal finding is that the accuracy of retrieval of this component from wind data obtained from airborne omega dropwindsonde soundings depends on the orientation of aircraft flight patterns relative to that of the asymmetry. Since the orientation of the asymmetry is not known in advance, there will be an inherent uncertainty in the accuracy with which the asymmetry is determined. The simulation experiments enable one to estimate probable errors in the determination of the asymmetry and their implications for hurricane track errors. The track errors are assessed by comparing the vortex track in a high-resolution control experiment with those that result from initial analyses based on simulated data sets of varying data density and quality. In some of the experiments, an increase in resolution along the flight tracks, or additional data in the storm environment, does not lead to an improvement in the forecast track, in contrast to increased data coverage on a regular grid. This at first sight surprising result is likely to be a consequence of the constant influence radius used in the objective analysis scheme, a factor which is currently being investigated. The addition of random wind-measurement errors to the simulated data, comparable in magnitude to those in dropwindsonde measurements, does not lead to significantly inferior analyses or track forecasts based on them, suggesting that such errors are not the major cause of inaccuracy in diagnosing the vortex asymmetry. Moreover, the accuracy of the analysis is nearly independent of whether the data are taken at an instant of time, or over a typical nine-hour flight duration and then corrected to a storm-centred coordinate system.

Errors in Wind Measurements Estimated by Five-Beam Phased Array Doppler Sodar

Abstract Estimation of the errors in sodar wind measurements using the phased array Doppler sodar operated under five-beam observation has been made. When compared with the sonic anemometer on the tower nearby, the variances or second-order moments of sodar-derived horizontal wind, σu and συ , are about twice as large as those measured at the tower, even though the mean horizontal wind u and the second moment of vertical wind σw are in reasonable agreement with the tower. The random errors in the measured wind variances, which can be separated in the five-beam detection system, are estimated to be about 0.41 m s−1 for the vertical component and 0.46 m s−1 for the tilted beam axis component. If the compensation is made for each component along the antenna beams, the horizontal wind variances averaged over 60 min agree with those values obtained by the sonic anemometer on the tower. An analysis of the power spectra suggests that the discrepancies in σu and συ are mainly caused by the excess of sodar spectra...

The Accuracy of Divergence Estimates Calculated Using the Linear Vector Point Function Method and Three Profilers

Abstract The effects of spatial, combined spatial and temporal sampling errors, and wind measurement errors on profiler-derived divergence estimates computed using the linear vector point function method are examined. Analysis indicates that divergence errors are minimized when the ratio between the spacing of the profilers and the sampled wavelength (Δx/Lx) is between 0.15 and 0.24 and the ratio between the profiler sampling time to the timescale of the weather system (Δt/T) is less than 0.055. When Δx/Lx ≤ 0.24, synoptic-scale divergence smaller than ±1.0 × 10−5 s−1 cannot be measured, because the error in the profiler wind estimates is larger than the horizontal velocity gradients. The expected errors in divergence calculations given typical profiler spatial and temporal sampling strategies are examined.

Systematic Errors in Radar Wind Estimation: Implications for Comparative Measurements

SA, IDI, and DBS horizontal wind estimators are examined and demonstrated to share common biases under inhomogeneous flow field conditions. The biases can reach magnitudes of several tens of meters per second at mesospheric heights, contaminate gravity wave flow field measurements, cause distortions in measured flow field spectra, and possibly account for large wind measurement errors evidenced in recent experimental studies including the AIDA'89 effort. However, being a linear response to gravity wave flow field fluctuations, the biases are expected to cancel out in long‐term wind and tidal statistics compiled with radar wind data.

Inertial Drift Correction for Aircraft-Derived Wind Fields

Abstract During the last three decades, aircraft have assumed an increasingly important role as platforms for atmospheric measurement. Because of the nature of the wind measurement process, however, low-frequency winds remain susceptible to significant errors, which have their origin in the inertial navigation system (INS) of the aircraft. Computations are presented showing that the Electra, a state-of-the-art aircraft for meteorological measurements, experiences low-frequency wind measurement errors typically as large as 3 m s−1 in each component of the horizontal wind. Errors of this magnitude can produce can produce line-integral divergence errors of 10−4 s−1 in typical flight geometries. Use of the LORAN-C navigational information now received on the aircraft offers an order-of-magnitude reduction of errors from the INS.

Wind-fetch dependence of Seasat scatterometer measurements

This work is focused on the effects of large-scale wind-generated gravity waves on scatterometer wind-measurement accuracy. Theoretical and experimental evidence of the important role played by the degree of wind-wave coupling in surface geometry and therefore in microwave signatures is presented. Seasat scatterometer wind-measurement errors are analyzed, and an error bias is found to be related to the degree of wind-wave development. Attention is focused on a dynamic measure of wind-wave development that characterizes the rate of energy transfer from the mean wind to the energy-carrying portion of the wave spectrum. An explanation of the bias is suggested based on the consideration of an additional component of surface scattering caused by electromagnetic-wave diffraction at the crests of individual, sufficiently steep wavelets.

Accuracy of Wind Measurements Using an Airborne Doppler Lidar

Simulated wind fields and lidar data are used to evaluate two sources of airborne wind measurement error. The system is sensitive to ground speed and track angle errors, with accuracy required of the angle to within 0.2 degrees and of the speed to within 1 knot, if the recovered wind field is to be within five percent of the correct direction and 10 percent of the correct speed. It is found that errors in recovered wind speed and direction are dependent on wind direction relative to the flight path. Recovery of accurate wind fields from nonsimultaneous sampling errors requires that the lidar data be displaced to account for advection so that the intersections are defined by air parcels rather than fixed points in space.

Omega Windfinding and GATE

Abstract When fully implemented, Omega will be a system of eight very low frequency (VLF) transmitters providing global coverage for navigation. Recently, intensive design and development has exploited Omega for tracking sondes (both free-rising and free-falling) to determine wind velocity as a function of height. During the summer of 1974, several GATE measurement systems, including radiosondes launched from ships and dropsondes released from both aircraft and constant level balloons, will provide winds derived from Omega signals. While some GATE ship radiosonde systems will use other VLF transmitters for windfinding, the principles involved are essentially identical to those required for Omega windfinding. This paper formulates the analytical techniques needed to use Omega or other VLF transmitters for windfinding, discusses sources of measurement errors, reviews Omega wind measurement error experiments, and projects wind errors into the GATE “B” area near 10N latitude and 25W longitude.

Errors in Wind Measurements Associated with Tower-Mounted Anemometers1

Towers distort the wind flow and thereby may produce errors in wind speed and direction measurements obtained by anemometers mounted on them. To study this effect, a comparison was made of 5000 hourly wind observations obtained from each of two Aerovanes operating simultaneously. One was mounted on a lattice-type tower and the other was mounted on a utility pole free from the tower wind-shadow effect. Both instruments were located at the meteorological field site of the Argonne National Laboratory. The results show that there was a substantial reduction in the wind speed indicated by the tower-mounted anemometer when the wind passed through the tower before being measured. For some wind directions, the tower-mounted anemometer gave speed readings appreciably higher than those of the reference anemometer. Wind-direction measurements were also affected. The data indicate that for precise work the tower wind-shadow effect must be considered.