Abstract

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.

Highlights

  • Scanning coherent Doppler light detection and ranging systems have proven to be invaluable tools for wind measurements in research as well as commercial applications

  • Five Doppler lidars (HRDL, D1, D2, University of Texas at Dallas (UTD) and University of Maryland Baltimore County (UMBC)) performed a set of complementary plan position indicator (PPI) scans that would ensure that at least two Doppler beams overlapped within each grid point within a 5 min update period

  • Note that in the vertical velocity comparisons, only measurements at and above the 150 m sonic are compared. This is due to the fact that at the lower sonic levels, the elevation angles in the virtual tower stares (VTS) scans were quite low and as a result the component we are trying to estimate is perpendicular to the lidar look direction, resulting in a noisy vertical velocity retrieval

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Summary

Introduction

Scanning coherent Doppler light detection and ranging (lidar) systems have proven to be invaluable tools for wind measurements in research as well as commercial applications. The simplest techniques to derive a profile of wind speed and direction using a single-Doppler lidar are the velocity azimuth display (VAD) technique (Browning and Wexler, 1968) and the Doppler beam swinging (DBS) technique (Strauch et al, 1984) These techniques assume horizontal homogeneity of the wind in the measurement volume to estimate the profile of wind speed and direction. Three-dimensional wind-field measurements made using dual-Doppler intersecting RHI scans and using continuity to estimate the vertical velocity were used to study flow upstream and downstream of a utility-scale wind turbine (Newsom et al, 2015). In addition to multi-Doppler approaches to measuring complex flow, several techniques enable wind-field retrievals from single-Doppler lidars, which resolve the spatial variability measured by the lidar.

Experiment setup
Coordinated triple-Doppler virtual tower stares
Coordinated triple-Doppler sparse sampling
Uncoordinated triple-Doppler virtual tower
Uncoordinated multi-Doppler volume scan
Single-Doppler velocity retrievals
Determining baseline uncertainty
Validation of wind-field measurements
Virtual tower stares
Coordinated sparse sampling
Uncoordinated volume scan
Single-Doppler OI technique
Discussion of results
Conclusions
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