Virtual Towers Using Coherent Doppler Lidar during the Joint Urban 2003 Dispersion Experiment

Calhoun, Ronald; Heap, R. D.; Princevac, Marko; Newsom, Rob; Fernando, H. J. S.; Ligon, David

doi:10.1175/jam2391.1

Cited by 93 publications

(81 citation statements)

References 11 publications

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“…The coordinated VTS scan pattern involves interrogating a common volume using multiple Doppler lidars at pre-defined heights at a given location to form a "virtual tower" (Calhoun et al, 2006;Mann et al, 2009;Fuertes et al, 2014;Gunter et al, 2015;Newman et al, 2016). A schematic of the triple lidar VTS scan tested during the XPIA field experiment is shown in Fig.…”

Section: Coordinated Triple-doppler Virtual Tower Staresmentioning

confidence: 99%

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Evaluation of single and multiple Doppler lidar techniques to measure complex flow during the XPIA field campaign

et al. 2017

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Abstract. Accurate three-dimensional information of wind flow fields can be an important tool in not only visualizing complex flow but also understanding the underlying physical processes and improving flow modeling. However, a thorough analysis of the measurement uncertainties is required to properly interpret results. The XPIA (eXperimental Planetary boundary layer Instrumentation Assessment) field campaign conducted at the Boulder Atmospheric Observatory (BAO) in Erie, CO, from 2 March to 31 May 2015 brought together a large suite of in situ and remote sensing measurement platforms to evaluate complex flow measurement strategies.In this paper, measurement uncertainties for different single and multi-Doppler strategies using simple scan geometries (conical, vertical plane and staring) are investigated. The tradeoffs (such as time-space resolution vs. spatial coverage) among the different measurement techniques are evaluated using co-located measurements made near the BAO tower. Sensitivity of the single-/multi-Doppler measurement uncertainties to averaging period are investigated using the sonic anemometers installed on the BAO tower as the standard reference. Finally, the radiometer measurements are used to partition the measurement periods as a function of atmospheric stability to determine their effect on measurement uncertainty.It was found that with an increase in spatial coverage and measurement complexity, the uncertainty in the wind measurement also increased. For multi-Doppler techniques, the increase in uncertainty for temporally uncoordinated measurements is possibly due to requiring additional assumptions of stationarity along with horizontal homogeneity and less representative line-of-sight velocity statistics. It was also found that wind speed measurement uncertainty was lower during stable conditions compared to unstable conditions.

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Section: Coordinated Triple-doppler Virtual Tower Staresmentioning

confidence: 99%

“…"Virtual towers" (Calhoun et al, 2006) use multiple Doppler lidars to interrogate a common volume in space in a temporally coordinated fashion, iterating through several height in order to create a wind profile. Several configurations of multi-Doppler scanning have been tested to quantify the skill in deriving 2-D and 3-D wind fields.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of single and multiple Doppler lidar techniques to measure complex flow during the XPIA field campaign

et al. 2017

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“…Seibert et al (2000) reviewed the various approaches that determine mixing layer height. Large field campaigns in urban areas in the past have included UBL monitoring by METROMEX in St. Louis (Changnon et al 1981), the IMADA-AVER Boundary Layer Experiment (Doran et al 1998), the 2001 Phoenix Sunrise Experiment (Doran et al 2003), AFO 2000 in Hanover (Emeis et al 2004), BUBBLE in Basel (Rotach et al 2005), ESCOMPTE in Marseille (Mestayer et al 2005), VTMX 2000 in Salt lake City (Fast et al , 2006 and Joint Urban 2003 in Oklahoma City (Calhoun et al 2006). Results of these filed campaigns suggest that urban areas show increased roughness and/or higher sensible heat fluxes than in rural areas.…”

Section: A Urban Atmospheric Boundary Layersmentioning

confidence: 99%

Progress in Urban Meteorology :A Review

Kanda

2007

Journal of the Meteorological Society of Japan

101

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This paper reviews the progress made in urban meteorology over the past few decades. The focus is on the impact of urban surfaces on the overlying atmosphere along the conventional meteorological frameworks. Section 1 details the difficulties in generalizing urban surfaces in a meteorological sense because of surface diversity, and considers whether conventional similarity law is applicable. Section 2 describes the characteristics of urban surfaces as the bottom boundary of the atmosphere and includes a discussion of land surface parameters and the resultant surface energy partitioning. Section 3 explains characteristics of the urban atmosphere, including temperature fields, local circulations and rainfall. Section 4 describes recent progress in numerical modeling and promising new technologies, thus revealing a possible future direction for urban meteorological studies.

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“…While single lidars require measurements around a scanning circle to estimate the three-dimensional velocity field, multiple scanning lidars can be pointed toward a particular volume of air to obtain turbulence estimates with much higher spatial resolution (e.g., Calhoun et al, 2006;Fuertes et al, 2014;Newsom et al, 2015;Newman et al, 2016a). To collect turbulence measurements, multi-lidar systems must be temporally and spatially synchronized with a high degree of accuracy.…”

Section: Multiple Lidarsmentioning

confidence: 99%

An error reduction algorithm to improve lidar turbulence estimates for wind energy

Newman

Clifton

2017

Wind Energ. Sci.

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Abstract. Remote-sensing devices such as lidars are currently being investigated as alternatives to cup anemometers on meteorological towers for the measurement of wind speed and direction. Although lidars can measure mean wind speeds at heights spanning an entire turbine rotor disk and can be easily moved from one location to another, they measure different values of turbulence than an instrument on a tower. Current methods for improving lidar turbulence estimates include the use of analytical turbulence models and expensive scanning lidars. While these methods provide accurate results in a research setting, they cannot be easily applied to smaller, vertically profiling lidars in locations where high-resolution sonic anemometer data are not available. Thus, there is clearly a need for a turbulence error reduction model that is simpler and more easily applicable to lidars that are used in the wind energy industry.In this work, a new turbulence error reduction algorithm for lidars is described. The Lidar Turbulence Error Reduction Algorithm, L-TERRA, can be applied using only data from a stand-alone vertically profiling lidar and requires minimal training with meteorological tower data. The basis of L-TERRA is a series of physics-based corrections that are applied to the lidar data to mitigate errors from instrument noise, volume averaging, and variance contamination. These corrections are applied in conjunction with a trained machine-learning model to improve turbulence estimates from a vertically profiling WINDCUBE v2 lidar. The lessons learned from creating the L-TERRA model for a WINDCUBE v2 lidar can also be applied to other lidar devices.L-TERRA was tested on data from two sites in the Southern Plains region of the United States. The physicsbased corrections in L-TERRA brought regression line slopes much closer to 1 at both sites and significantly reduced the sensitivity of lidar turbulence errors to atmospheric stability. The accuracy of machine-learning methods in L-TERRA was highly dependent on the input variables and training dataset used, suggesting that machine learning may not be the best technique for reducing lidar turbulence intensity (TI) error. Future work will include the use of a lidar simulator to better understand how different factors affect lidar turbulence error and to determine how these errors can be reduced using information from a stand-alone lidar.

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Virtual Towers Using Coherent Doppler Lidar during the Joint Urban 2003 Dispersion Experiment

Cited by 93 publications

References 11 publications

Evaluation of single and multiple Doppler lidar techniques to measure complex flow during the XPIA field campaign

Evaluation of single and multiple Doppler lidar techniques to measure complex flow during the XPIA field campaign

Progress in Urban Meteorology :A Review

An error reduction algorithm to improve lidar turbulence estimates for wind energy

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