Vergleich von Windmessungen verschiedener Doppler Lidarscanstrategien und zweier Lidarmarken mit einem Ultraschallanemometer

2021 ◽  
Author(s):  
Kevin Wolz ◽  
Norman Wildmann ◽  
Frank Beyrich ◽  
Eileen Päschke ◽  
Carola Detring ◽  
...  
Keyword(s):  

<p>Die Technologie hat einen Punkt erreicht an dem bodenbasierte Fernerkundungsinstrumente die Möglichkeit haben die räumliche und zeitliche Datendichte im Vergleich zu konventionellen Instrumenten stark zu erhöhen. Das bietet die große Chance das Verständnis über einzelne Prozesse zu verbessern und die Vorhersagefähigkeiten von numerischen Wettermodellen zu erhöhen und ihre Ungenauigkeiten zu verringern. Das Ziel der Studie ist es diese Messungenauigkeiten und die Nutzbarkeit von Doppler Lidar Systemen für diese Zwecke zu überprüfen. Die Daten wurden während der FESST@MOL 2020 Messkampagne, organisiert von dem Deutschen Wetterdienst (DWD) und initiiert von dem Hans-Ertel-Zentrum für Wetterforschung (HErZ), auf dem Grenzschichtmessfeld (GM) des DWD in Falkenberg (Tauche), Deutschland erhoben. Während der Messkampagne waren insgesamt acht Doppler Lidare der Marken Halo Photonics und Leosphere in verschiedenen Betriebsmodi aktiv. In dieser Arbeit vergleichen wir die Ergebnisse von Triple und Single Lidar Setups, von Geräten der Marke Halo Photonics und Triple Lidar Setups von Geräten der Marke Leosphere mit den Messungen eines Ultraschallanemometers, angebracht auf einer Höhe von 90 m an dem 99 m hohem, mit Instrumenten bestückten, Messturm in Falkenberg. Der Fokus der Betriebsmodi liegt auf verschiedenen virtuellen Turm (VT) Messungen und Velocity Azimuth Display (VAD) Messungen mit den Mittelungszeiten von zehn und dreißig Minuten des mittleren horizontalen Windes. Die Diskrepanz der Messwerte zwischen VT und VAD Messungen nimmt mit steigender Höhe über dem Boden zu.</p>

2021 ◽  
Vol 13 (13) ◽  
pp. 2433
Author(s):  
Shu Yang ◽  
Fengchao Peng ◽  
Sibylle von Löwis ◽  
Guðrún Nína Petersen ◽  
David Christian Finger

Doppler lidars are used worldwide for wind monitoring and recently also for the detection of aerosols. Automatic algorithms that classify the lidar signals retrieved from lidar measurements are very useful for the users. In this study, we explore the value of machine learning to classify backscattered signals from Doppler lidars using data from Iceland. We combined supervised and unsupervised machine learning algorithms with conventional lidar data processing methods and trained two models to filter noise signals and classify Doppler lidar observations into different classes, including clouds, aerosols and rain. The results reveal a high accuracy for noise identification and aerosols and clouds classification. However, precipitation detection is underestimated. The method was tested on data sets from two instruments during different weather conditions, including three dust storms during the summer of 2019. Our results reveal that this method can provide an efficient, accurate and real-time classification of lidar measurements. Accordingly, we conclude that machine learning can open new opportunities for lidar data end-users, such as aviation safety operators, to monitor dust in the vicinity of airports.


Author(s):  
Ahmed Khalil ◽  
Nicolas Fezans

AbstractGust load alleviation functions are mainly designed for two objectives: first, alleviating the structural loads resulting from turbulence or gust encounter, and hence reducing the structural fatigue and/or weight; and second, enhancing the ride qualities, and hence the passengers’ comfort. Whilst load alleviation functions can improve both aspects, the designer will still need to make design trade-offs between these two objectives and also between various types and locations of the structural loads. The possible emergence of affordable and reliable remote wind sensor techniques (e.g., Doppler LIDAR) in the future leads to considering new types of load alleviation functions as these sensors would permit anticipating the near future gusts and other types of turbulence. In this paper, we propose a preview control design methodology for the design of a load alleviation function with such anticipation capabilities, based on recent advancements on discrete-time reduced-order multi-channel $$H_\infty $$ H ∞ techniques. The methodology is illustrated on the DLR Discus-2c flexible sailplane model.


2013 ◽  
Vol 94 (6) ◽  
pp. 883-902 ◽  
Author(s):  
Robert M. Banta ◽  
Yelena L. Pichugina ◽  
Neil D. Kelley ◽  
R. Michael Hardesty ◽  
W. Alan Brewer

Addressing the need for high-quality wind information aloft in the layer occupied by turbine rotors (~30–150 m above ground level) is one of many significant challenges facing the wind energy industry. Without wind measurements at heights within the rotor sweep of the turbines, characteristics of the flow in this layer are unknown for wind energy and modeling purposes. Since flow in this layer is often decoupled from the surface, near-surface measurements are prone to errant extrapolation to these heights, and the behavior of the near-surface winds may not reflect that of the upper-level flow.


2014 ◽  
Author(s):  
Songhua Wu ◽  
Jiaping Yin ◽  
Bingyi Liu ◽  
Jintao Liu ◽  
Rongzhong Li ◽  
...  

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 50
Author(s):  
Hongwei Zhang ◽  
Xiaoying Liu ◽  
Qichao Wang ◽  
Jianjun Zhang ◽  
Zhiqiang He ◽  
...  

Low-level wind shear is usually to be a rapidly changing meteorological phenomenon that cannot be ignored in aviation security service by affecting the air speed of landing and take-off aircrafts. The lidar team in Ocean University of China (OUC) carried out the long term particular researches on the low-level wind shear identification and regional wind shear inducement search at Beijing Capital International Airport (BCIA) from 2015 to 2020 by operating several pulsed coherent Doppler lidar (PCDL) systems. On account of the improved glide path scanning strategy and virtual multiple wind anemometers based on the rang height indicator (RHI) modes, the small-scale meteorological phenomenon along the glide path and/or runway center line direction can be captured. In this paper, the device configuration, scanning strategies, and results of the observation data are proposed. The algorithms to identify the low-level wind shear based on the reconstructed headwind profiles data have been tested and proved based on the lidar data obtained from December 2018 to January 2019. High spatial resolution observation data at vertical direction are utilized to study the regional wind shear inducement at the 36L end of BCIA under strong northwest wind conditions.


Author(s):  
Zhaoai Yan ◽  
Xiong Hu ◽  
Wenjie Guo ◽  
Shangyong Guo ◽  
Yongqiang Cheng ◽  
...  

1992 ◽  
Author(s):  
Claude Loth ◽  
Alain M. Dabas ◽  
Pierre H. Flamant ◽  
D. Oh ◽  
J. Delume ◽  
...  
Keyword(s):  

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