Calculation of area‐averaged vertical profiles of the horizontal wind velocity from volume‐imaging lidar data

Schols, J. L.; Eloranta, E. W.

doi:10.1029/92jd01051

Cited by 42 publications

(30 citation statements)

References 11 publications

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“…Volume-imaging lidars track the motion of backscatter inhomogeneities assumed to move with the wind (Schols and Eloranta, 1992) or measure line-of-sight velocity using Doppler shift (Grund et al, 2001). However, lidars can fail in air containing optically-thick cloud, precipitation, insects, birds, or insufficient aerosol.…”

Section: Introductionmentioning

confidence: 99%

All-weather volume imaging of the boundary layer and troposphere using the MU radar

Worthington

2004

Ann. Geophys.

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Abstract. This paper shows the first volume-imaging radar that can run in any weather, revealing the turbulent threedimensional structure and airflow of convective cells, rain clouds, breaking waves and deep convection as they evolve and move. Precipitation and clear air can be volume-imaged independently. Birds are detected as small high-power echoes moving near horizontal, at different speeds and directions from background wind. The volume-imaging method could be used to create a real-time virtual-reality view of the atmosphere, in effect making the invisible atmosphere visible in any weather.

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Section: Introductionmentioning

confidence: 99%

All-weather volume imaging of the boundary layer and troposphere using the MU radar

Worthington

2004

Ann. Geophys.

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“…2.1 of this paper, the laser source works in the IR-B region and the pulse energy is low, compared with previous works. 21,22 As a consequence, the system operates within the exposure limits imposed by European directive 2006/25/EC, 23 and it is eye-safe. It should be noted that our system was not originally conceived for wind speed tracking but only for CO 2 concentration measurements.…”

Section: Introductionmentioning

confidence: 99%

Fast tracking of wind speed with a differential absorption LiDAR system: first results of an experimental campaign at Stromboli volcano

et al. 2017

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Abstract. Carbon dioxide (CO 2 ) is considered a precursor gas of volcanic eruptions by volcanologists. Monitoring the anomalous release of this parameter, we can retrieve useful information for the mitigation of volcanic hazards, such as for air traffic security. From a dataset collected during the Stromboli volcano field campaign, an assessment of the wind speed, in both horizontal and vertical paths, performing a fast tracking of this parameter was retrieved. This was determined with a newly designed shot-per-shot differential absorption LiDAR system operated in the near-infrared spectral region due to the simultaneous reconstruction of CO 2 concentrations and wind speeds, using the same sample of LiDAR returns. A correlation method was used for the wind speed retrieval in which the transport of the spatial inhomogeneities of the aerosol backscattering coefficient, along the optical path of the system, was analyzed.

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“…An open question is the importance of quantization error in this regard, i.e., do 12 bit gray scale images with 4,096 levels significantly outperform 8 bit gray scale images. Related to this is the importance of image histogram equalization Schols and Eloranta [17] and to better utilize the image spectrum Piironen and Eloranta [12].…”

Section: Image Filtering and Processingmentioning

confidence: 99%

“…In Schols and Eloranta [17] high pass temporal filtering is used to remove structures that do not move with the wind. For wind farm citing applications, ground returns from towers, buildings, telephone poles, etc., are removed by mapping the LIDAR field of view at the beginning of the survey.…”

Section: Image Filtering and Processingmentioning

confidence: 99%

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Four Methods for LIDAR Retrieval of Microscale Wind Fields

Howard

Naini

2012

Remote Sensing

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This paper evaluates four wind retrieval methods for micro-scale meteorology applications with volume and time resolution in the order of 30 m 3 and 5 s. Wind field vectors are estimated using sequential time-lapse volume images of aerosol density fluctuations. Suitably designed mono-static scanning backscatter LIDAR systems, which are sensitive to atmospheric density aerosol fluctuations, are expected to be ideal for this purpose. An important application is wind farm siting and evaluation. In this case, it is necessary to look at the complicated region between the earth's surface and the boundary layer, where wind can be turbulent and fractal scaling from millimeter to kilometer. The methods are demonstrated using first a simple randomized moving hard target, and then with a physics based stochastic space-time dynamic turbulence model. In the latter case the actual vector wind field is known, allowing complete space-time error analysis. Two of the methods, the semblance method and the spatio-temporal method, are found to be most suitable for wind field estimation.

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Calculation of area‐averaged vertical profiles of the horizontal wind velocity from volume‐imaging lidar data

Cited by 42 publications

References 11 publications

All-weather volume imaging of the boundary layer and troposphere using the MU radar

All-weather volume imaging of the boundary layer and troposphere using the MU radar

Fast tracking of wind speed with a differential absorption LiDAR system: first results of an experimental campaign at Stromboli volcano

Four Methods for LIDAR Retrieval of Microscale Wind Fields

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