Estimation of Wind Vector Profile Using a Hexarotor Unmanned Aerial Vehicle and Its Application to Meteorological Observation up to 1000 m above Surface

2018 ◽  
Vol 35 (8) ◽  
pp. 1621-1631 ◽  
Author(s):  
Tomoya Shimura ◽  
Minoru Inoue ◽  
Hirofumi Tsujimoto ◽  
Kansuke Sasaki ◽  
Masato Iguchi
Keyword(s):  
Wind Speed ◽  
Profile Measurement ◽  
Wind Vector ◽  
Doppler Lidar ◽  
Wind Speeds ◽  
Wide Range ◽  
Lidar Measurements ◽  
Ultrasonic Anemometer ◽  
Aerial Vehicle ◽  
Meteorological Observations

AbstractSmall unmanned aerial vehicles (UAVs), also known as drones, have recently become promising tools in various fields. We investigated the feasibility of wind vector profile measurement using an ultrasonic anemometer installed on a 1-m-wide hexarotor UAV. Wind vectors measured by the UAV were compared to observations by a 55-m-high meteorological tower, over a wide range of wind speed conditions up to 11 m s−1, which is a higher wind speed range than those used in previous studies. The wind speeds and directions measured by the UAV and the tower were in good agreement, with a root-mean-square error of 0.6 m s−1 and 12° for wind speed and direction, respectively. The developed method was applied to field meteorological observations near a volcano, and the wind vector profiles, along with temperature and humidity, were measured by the UAV for up to an altitude of 1000 m, which is a higher altitude range than those used in previous studies. The wind vector profile measured by the UAV was compared with Doppler lidar measurements (collected several kilometers away from the UAV measurements) and was found to be qualitatively similar to that captured by the Doppler lidar, and it adequately represented the features of the atmospheric boundary layer. The feasibility of wind profile measurement up to 1000 m by a small rotor-based UAV was clarified over a wide range of wind speed conditions.

scholarly journals Measurement and Prediction of Wind Fields at an Offshore Site by Scanning Doppler LiDAR and WRF

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 442 ◽  
Author(s):  
Jay Prakash Goit ◽  
Atsushi Yamaguchi ◽  
Takeshi Ishihara
Keyword(s):  
Wind Speed ◽  
Internal Boundary Layer ◽  
Data Availability ◽  
Analytical Models ◽  
Internal Boundary ◽  
Doppler Lidar ◽  
Wind Fields ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Lidar Measurements

LiDAR-based wind speed measurements have seen a significant increase in interest in wind energy. However, reconstruction of wind speed vector from a LiDAR-measured radial wind speed is still a challenge. Furthermore, for extensive application of LiDAR technology, it can be used as a means to validate simulation and analytical models. To that end, this study employed scanning Doppler LiDAR for assessment of wind fields at an offshore site and compared Weather Research and Forecasting (WRF)-based mesoscale simulations and several wake models with the measurements. Firstly, the effect of carrier-to-noise-ratio (CNR) and data availability on the quality of scanning LiDAR measurements was evaluated. Analysis of vertical profiles show that the average wind speed is higher for wind blowing from the sea than that blowing from the land. Furthermore, profiles obtained from the WRF simulation also show a similar tendency in the LiDAR measurements in general, though it overestimates the wind speeds at higher altitudes. A method for reconstruction of wind fields from plan-position indicator (PPI) and range height indicator (RHI) scans of LiDAR-measured line of sight velocities was then proposed and first used to investigate the effect of coastal terrain. An internal boundary layer with strong shear could be observed to develop from the coastline. Finally, the flow field around wind turbine was measured using PPI scan and used to validate wake models.

scholarly journals Reviewing Wind Measurement Approaches for Fixed-Wing Unmanned Aircraft

Atmosphere ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 422 ◽  
Author(s):  
Alexander Rautenberg ◽  
Martin Graf ◽  
Norman Wildmann ◽  
Andreas Platis ◽  
Jens Bange
Keyword(s):  
Wind Speed ◽  
Unmanned Aircraft ◽  
Flow Sensor ◽  
Navigation Satellite ◽  
Wind Vector ◽  
Data Set ◽  
Vector Measurement ◽  
Wide Range ◽  
Global Navigation ◽  
Global Navigation Satellite

One of the biggest challenges in probing the atmospheric boundary layer with small unmanned aerial vehicles is the turbulent 3D wind vector measurement. Several approaches have been developed to estimate the wind vector without using multi-hole flow probes. This study compares commonly used wind speed and direction estimation algorithms with the direct 3D wind vector measurement using multi-hole probes. This was done using the data of a fully equipped system and by applying several algorithms to the same data set. To cover as many aspects as possible, a wide range of meteorological conditions and common flight patterns were considered in this comparison. The results from the five-hole probe measurements were compared to the pitot tube algorithm, which only requires a pitot-static tube and a standard inertial navigation system measuring aircraft attitude (Euler angles), while the position is measured with global navigation satellite systems. Even less complex is the so-called no-flow-sensor algorithm, which only requires a global navigation satellite system to estimate wind speed and wind direction. These algorithms require temporal averaging. Two averaging periods were applied in order to see the influence and show the limitations of each algorithm. For a window of 4 min, both simplifications work well, especially with the pitot-static tube measurement. When reducing the averaging period to 1 min and thereby increasing the temporal resolution, it becomes evident that only circular flight patterns with full racetracks inside the averaging window are applicable for the no-flow-sensor algorithm and that the additional flow information from the pitot-static tube improves precision significantly.

scholarly journals One decade of parallel fine (PM<sub>2.5</sub>) and coarse (PM<sub>10</sub>–PM<sub>2.5</sub>) particulate matter measurements in Europe: trends and variability

2012 ◽  
Vol 12 (7) ◽  
pp. 3189-3203 ◽  
Author(s):  
I. Barmpadimos ◽  
J. Keller ◽  
D. Oderbolz ◽  
C. Hueglin ◽  
A. S. H. Prévôt
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Stationary Point ◽  
Generalized Additive Models ◽  
Negative Relationship ◽  
Additive Models ◽  
Wind Speeds ◽  
East Wind ◽  
Pm10 And Pm2.5 ◽  
Meteorological Observations

Abstract. The trends and variability of PM10, PM2.5 and PMcoarse concentrations at seven urban and rural background stations in five European countries for the period between 1998 and 2010 were investigated. Collocated or nearby PM measurements and meteorological observations were used in order to construct Generalized Additive Models, which model the effect of each meteorological variable on PM concentrations. In agreement with previous findings, the most important meteorological variables affecting PM concentrations were wind speed, wind direction, boundary layer depth, precipitation, temperature and number of consecutive days with synoptic weather patterns that favor high PM concentrations. Temperature has a negative relationship to PM2.5 concentrations for low temperatures and a positive relationship for high temperatures. The stationary point of this relationship varies between 5 and 15 °C depending on the station. PMcoarse concentrations increase for increasing temperatures almost throughout the temperature range. Wind speed has a monotonic relationship to PM2.5 except for one station, which exhibits a stationary point. Considering PMcoarse, concentrations tend to increase or stabilize for large wind speeds at most stations. It was also observed that at all stations except one, higher PM2.5 concentrations occurred for east wind direction, compared to west wind direction. Meteorologically adjusted PM time series were produced by removing most of the PM variability due to meteorology. It was found that PM10 and PM2.5 concentrations decrease at most stations. The average trends of the raw and meteorologically adjusted data are −0.4 μg m−3 yr−1 for PM10 and PM2.5 size fractions. PMcoarse have much smaller trends and after averaging over all stations, no significant trend was detected at the 95% level of confidence. It is suggested that decreasing PMcoarse in addition to PM2.5 can result in a faster decrease of PM10 in the future. The trends of the 90th quantile of PM10 and PM2.5 concentrations were examined by quantile regression in order to detect long term changes in the occurrence of very large PM concentrations. The meteorologically adjusted trends of the 90th quantile were significantly larger (as an absolute value) on average over all stations (−0.6 μg m−3 yr−1).

scholarly journals Uncertainty model for dual-Doppler retrievals of wind speed and wind direction

2020 ◽  
Author(s):  
Nikola Vasiljević ◽  
Michael Courtney ◽  
Anders Tegtmeier Pedersen
Keyword(s):  
Wind Speed ◽  
Elevation Angle ◽  
Velocity Estimation ◽  
Horizontal Wind ◽  
Doppler Lidar ◽  
Horizontal Wind Speed ◽  
Uncertainty Model ◽  
Lidar Measurements ◽  
Python Package ◽  
Propagation Of Uncertainties

Abstract. In this paper we present an analytical model for estimating the uncertainty of the horizontal wind speed based on dual-Doppler lidar measurements. The model follows the propagation of uncertainties method and takes into account the uncertainty of radial velocity estimation, azimuth and elevation pointing angles, and ranging. The model is achieved by coupling ranging and elevation angle to uncertainty of the probed wind speed through a simple power-law shear model. The model has been implemented in Python and made freely available through as the Python package YADDUM.

scholarly journals A Comparison of Meteorological Observations from South Pole Station before and after Installation of a New Instrument Suite

2009 ◽  
Vol 26 (8) ◽  
pp. 1605-1613 ◽  
Author(s):  
L. M. Keller ◽  
K. A. Baker ◽  
M. A. Lazzara ◽  
J. Gallagher
Keyword(s):  
Wind Speed ◽  
South Pole ◽  
Flow Distortion ◽  
Wind Speeds ◽  
New Instrument ◽  
Before And After ◽  
Clean Air ◽  
New Instrumentation ◽  
Meteorological Observations ◽  
Pole Surface

Abstract The Amundsen–Scott South Pole surface meteorological instrument suite was upgraded in 2004. To ensure that the new and old instruments were recording similar information, the two suites of instruments ran simultaneously for a year. Statistical analysis of the time series of temperature, pressure, and wind was performed to determine if there were any significant differences in the observations. Significant differences were found in some of the winter months for temperature and wind speed. No differences were found for the wind direction distribution. There are also noticeable differences in wind speed between the Clean Air platform near the Clean Air facility and the platform at the approach end of the skiway. Wind speeds are lower at the skiway tower when the wind is from the northeast quadrant and at the Clean Air tower when the wind is from the southwest quadrant, reflecting the effect of increased surface roughness and flow distortion over and around the station structures. Because of a change in elevation of the pressure sensor, the pressure data were recalculated at a common station elevation (2836 m). Although the resulting differences are small (around 0.1 hPa), there is a systematic sign change between summer and winter. The results of this analysis, while revealing some significant differences, show that the new instrumentation at South Pole station is generally reporting observations that are similar to those of the old instrumentation, and most of the differences are within the accuracy of the instruments. However, the instrument placement and construction of official aviation routine weather reports (METARs) do have an impact on the usefulness of the data for research.

scholarly journals Estimation of bubble-mediated air–sea gas exchange from concurrent DMS and CO<sub>2</sub> transfer velocities at intermediate–high wind speeds

2017 ◽  
Vol 17 (14) ◽  
pp. 9019-9033 ◽  
Author(s):  
Thomas G. Bell ◽  
Sebastian Landwehr ◽  
Scott D. Miller ◽  
Warren J. de Bruyn ◽  
Adrian H. Callaghan ◽  
...  
Keyword(s):  
Wind Speed ◽  
Gas Exchange ◽  
North Atlantic ◽  
Gas Transfer ◽  
Data Set ◽  
Wind Speeds ◽  
Wide Range ◽  
Carbon Dioxide Co2 ◽  
The Impact

Abstract. Simultaneous air–sea fluxes and concentration differences of dimethylsulfide (DMS) and carbon dioxide (CO2) were measured during a summertime North Atlantic cruise in 2011. This data set reveals significant differences between the gas transfer velocities of these two gases (Δkw) over a range of wind speeds up to 21 m s−1. These differences occur at and above the approximate wind speed threshold when waves begin breaking. Whitecap fraction (a proxy for bubbles) was also measured and has a positive relationship with Δkw, consistent with enhanced bubble-mediated transfer of the less soluble CO2 relative to that of the more soluble DMS. However, the correlation of Δkw with whitecap fraction is no stronger than with wind speed. Models used to estimate bubble-mediated transfer from in situ whitecap fraction underpredict the observations, particularly at intermediate wind speeds. Examining the differences between gas transfer velocities of gases with different solubilities is a useful way to detect the impact of bubble-mediated exchange. More simultaneous gas transfer measurements of different solubility gases across a wide range of oceanic conditions are needed to understand the factors controlling the magnitude and scaling of bubble-mediated gas exchange.

scholarly journals Investigation of Marine Wind Veer Characteristics Using Wind Lidar Measurements

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1178
Author(s):  
Zhenru Shu ◽  
Qiusheng Li ◽  
Yuncheng He ◽  
Pak Wai Chan
Keyword(s):  
Wind Speed ◽  
Atmospheric Stability ◽  
Offshore Wind ◽  
Hilly Terrain ◽  
Open Sea ◽  
Wide Range ◽  
Lidar Measurements ◽  
Mean Wind Speed ◽  
Wind Characteristics ◽  
Wind Lidar

A proper understanding of marine wind characteristics is of essential importance across a wide range of engineering applications. While the offshore wind speed and turbulence characteristics have been examined extensively, the knowledge of wind veer (i.e., turning of wind with height) is much less understood and discussed. This paper presents an investigation of marine wind field with particular emphasis on wind veer characteristics. Extensive observations from a light detection and ranging (Lidar) system at an offshore platform in Hong Kong were examined to characterize the wind veer profiles up to a height of 180 m. The results underscored the occurrence of marine wind veer, with a well-defined two-fold vertical structure. The observed maximum wind veer angle exhibits a reverse correlation with mean wind speed, which decreases from 2.47° to 0.59° for open-sea terrain, and from 7.45° to 1.92° for hilly terrain. In addition, seasonal variability of wind veer is apparent, which is most pronounced during spring and winter due to the frequent occurrence of the low-level jet. The dependence of wind veer on atmospheric stability is evident, particularly during winter and spring. In general, neutral stratification reveals larger values of wind veer angle as compared to those in stable and unstable stratification conditions.

scholarly journals First results of a promising Doppler lidar configuration to derive wind gusts within the FESSTVaL campaign

2021 ◽  
Author(s):  
Carola Detring ◽  
Julian Steinheuer ◽  
Eileen Päschke ◽  
Ronny Leinweber ◽  
Markus Kayser ◽  
...  
Keyword(s):  
Sonic Anemometer ◽  
Stream Line ◽  
Doppler Lidar ◽  
Wind Speeds ◽  
Wind Gusts ◽  
Lidar Measurements ◽  
Complete Measurement ◽  
First Results ◽  
Measurement Mode ◽  
Spatio Temporal

&lt;p&gt;A central aspect of the Field Experiment on Sub-Mesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL, www.fesstval.de) is the investigation of wind gusts with Doppler lidar measurements. Compared to meteorological tower observations, they have the advantage of being able to probe higher altitudes of the atmosphere, they thus offer the possibility to record a vertical profile of wind gusts with a resolution of about 30 m in the atmospheric boundary layer. Nevertheless, it is difficult to capture wind gusts with these instruments as it is challenging to measure fluctuations of short duration with an instrument which needs a certain time for one complete measurement.&lt;/p&gt;&lt;p&gt;Based on the research of Suomi et al. (2017), different configurations were tested in a pre-campaign in autumn 2019 to identify a suitable measurement mode for Halo Photonics Stream Line Scanning Doppler LiDAR systems. Different lidars were operated in parallel to compare configurations against each other. A promising mode was tested during the FESST@MOL campaign in summer 2020 for a three month period. This is a continous scan mode (CSM) configuration that takes about 3.4 seconds per circulation and performs measurements in 10-11 directions.&lt;/p&gt;&lt;p&gt;The derived wind gusts and mean wind speeds are compared with high resolution sonic anemometer measurements at 90.3 m to verify the quality of the lidar measurements. In a first comparison good agreement is shown despite the different measuring principles. In addition, various parameters are tested to identify optimal thresholds that allow a reliable derivation of wind gusts.&lt;/p&gt;&lt;p&gt;In summer 2021 this fast CSM mode will be operated and further tested in the FESSTVaL campaign in parallel with UAS measurements. Moreover lidars will be installed at different locations to analyse the spatial characteristics of wind gusts with this scanning configuration.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Reference&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Suomi, I., Gryning, S.&amp;#8208;E., O'Connor, E.J. and Vihma, T. (2017), Methodology for obtaining wind gusts using Doppler lidar. Q.J.R. Meteorol. Soc., 143: 2061-2072. https://doi.org/10.1002/qj.3059&lt;/p&gt;

scholarly journals Minute-scale power forecast of offshore wind turbines using long-range single-Doppler lidar measurements

2020 ◽  
Vol 5 (4) ◽  
pp. 1449-1468
Author(s):  
Frauke Theuer ◽  
Marijn Floris van Dooren ◽  
Lueder von Bremen ◽  
Martin Kühn
Keyword(s):  
Wind Speed ◽  
Wind Farm ◽  
Time Synchronization ◽  
Stock Exchange ◽  
Scanning Speed ◽  
Energy System ◽  
Offshore Wind ◽  
Doppler Lidar ◽  
Short Term ◽  
Lidar Measurements

Abstract. Decreasing gate closure times on the electricity stock exchange market and the rising share of renewables in today's energy system causes an increasing demand for very short-term power forecasts. While the potential of dual-Doppler radar data for that purpose was recently shown, the utilization of single-Doppler lidar measurements needs to be explored further to make remote-sensing-based very short-term forecasts more feasible for offshore sites. The aim of this work was to develop a lidar-based forecasting methodology, which addresses a lidar's comparatively low scanning speed. We developed a lidar-based forecast methodology using horizontal plan position indicator (PPI) lidar scans. It comprises a filtering methodology to recover data at far ranges, a wind field reconstruction, a time synchronization to account for time shifts within the lidar scans and a wind speed extrapolation to hub height. Applying the methodology to seven free-flow turbines in the offshore wind farm Global Tech I revealed the model's ability to outperform the benchmark persistence during unstable stratification, in terms of deterministic as well as probabilistic scores. The performance during stable and neutral situations was significantly lower, which we attribute mainly to errors in the extrapolation of wind speed to hub height.

scholarly journals One decade of parallel PM10 and PM2.5 measurements in Europe: trends and variability

2012 ◽  
Vol 12 (1) ◽  
pp. 1-43 ◽  
Author(s):  
I. Barmpadimos ◽  
J. Keller ◽  
D. Oderbolz ◽  
C. Hueglin ◽  
A. S. H. Prévôt
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Stationary Point ◽  
Generalized Additive Models ◽  
Negative Relationship ◽  
Additive Models ◽  
Wind Speeds ◽  
East Wind ◽  
Pm10 And Pm2.5 ◽  
Meteorological Observations

Abstract. The trends and variability of PM10, PM2.5 and PMcoarse concentrations at seven urban and rural background stations in five European countries for the period between 1998 and 2010 were investigated. Collocated or nearby PM measurements and meteorological observations were used in order to construct Generalized Additive Models, which model the effect of each meteorological variable on PM concentrations. In agreement with previous findings, the most important meteorological variables affecting PM concentrations were wind speed, wind direction, boundary layer depth, precipitation, temperature and number of consecutive days with synoptic weather patterns that favor high PM concentrations. Temperature has a negative relationship to PM2.5 concentrations for low temperatures and a positive relationship for high temperatures. The stationary point of this relationship varies between 5 and 15 °C depending on the station. PMcoarse concentrations increase for increasing temperatures almost throughout the temperature range. Wind speed has a monotonic relationship to PM2.5 except for one station, which exhibits a stationary point. Considering PMcoarse, concentrations tend to increase or stabilize for large wind speeds at most stations. It was also observed that at all stations except one, higher PM2.5 concentrations occurred for east wind direction, compared to west wind direction. Meteorologically adjusted PM time series were produced by removing most of the PM variability due to meteorology. It was found that PM10 and PM2.5 concentrations decrease at most stations. The average trends of the raw and meteorologically adjusted data are −0.4 μg m−3 yr−1 for PM10 and PM2.5 size fractions. PMcoarse have much smaller trends and after averaging over all stations, no significant trend was detected at the 95% level of confidence. It is suggested that decreasing PMcoarse in addition to PM2.5 can result in a faster decrease of PM10 in the future. The trends of the 90th quantile of PM10 and PM2.5 concentrations were examined by quantile regression in order to detect long term changes in the occurrence of very large PM concentrations. The meteorologically adjusted trends of the 90th quantile were significantly larger (as an absolute value) on average over all stations (−0.6 μg m−3 yr−1).

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