Abstract:

Using three Doppler scanning LiDARs, three Optical Particle Counters (OPCs), one Ceilometer, and one 3-D sonic anemometer, atmospheric measurements were conducted at the Surface Layer Turbulence and Environmental Science Test (SLTEST) facility in Dugway, Utah, during the period of 2019-06-10 to 2019-07-15. This unique location provides a natural facility to investigate near walled turbulence for a range of over 240 km streamwise and more than 48km spanwise in favorable conditions. Coupled with the sonic anemometer, the LiDARs provide high frequency and long-ranged simultaneous measurements of wind velocity and atmospheric backscatter field under all atmospheric stability regimes and wind directions. Moreover, the OPCs helps calibrate the simultaneous backscatter measurements from the LiDAR and Ceilometer (vertical profiles) to estimate collocated aerosol concentration throughout the domain range. This unique dataset will help investigate the coupling of a passive scalar in a near-wall turbulent flow under various flow regimes. Simultaneous data have been collected from all these instruments using coupled scanning strategies which provide a unique opportunity to study passive scalar entrainment and coupling with atmospheric turbulence. This dataset contains raw and processed vertical profiles of backscatter from the ceilometer, as well as the instruments user guide, daily quick-look plots, and a Readme file; raw and summary data from the sonic anemometer, in addition to a Readme file and Matlab scripts for processing the data; raw and processed data from each LiDAR instrument and a Readme file; and data for each ceilometer, including data from each of four units measuring at 6 m on the 28m tower.

Suggested Citation:

Valerio Iungo, Giacomo, Yajat Pandya, and Di Yang. 2022. Atmospheric turbulence and aerosol measurements in Surface Layer Turbulence and Environmental Science Test (SLTEST) facility in Dugway, Utah from 2019-06-10 to 2019-07-15. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/G2FE156A

Purpose:

Numerous computational and experimental studies have been conducted to investigate Very Large Scale Motions (VLSMs) in the atmospheric surface layer. However, the correlation of a passive scalar with the surface layer turbulence has been a challenging study since last few decades. PM1, PM2.5, and PM10 OPC measurements will provide unique methodology to have multi-parameter calibration for the LiDAR and Ceilometer derived atmospheric backscatter. Using such calibration methods, the LiDAR data will be used to investigate the flow as direct measurements of doppler velocity and aerosol concentration at the same spatio-temporal coordinates under different flow regimes. The dataset provides simultaneous measurements from all the afore-mentioned instruments using coupled scanning strategies which provide a unique opportunity to investigate the problem.

Data Parameters and Units:

Anemometer: ID number [enum], Year [2019], Yearday [XXX], hours and minutes [UTC, 24 hour time format], seconds, Ux [m/s], Uy [m/s], Uz [m/s], temperature [degrees C]. In addition to the raw data, there is a summary Matlab file for each data containing Matlab format timestamp, zonal, meridional, and vertical velocity, and temperature in a structure named Sonic. Ceilometer: Backscatter [/m/sterdian], radial height (10 m resolution), tilt (angle from vertical axis, [degrees]), time (epoch format, UTC (Vertical profiles). Lidar: The parameters and units for the six types of LiDAR files included are described in the file Readme_filenaming.txt contained in the Lidar directory. Common parameters are date, time, azimuth, elevation, pitch, roll, intensity, and backscatter. Optical Particle Counters: Date/Time (Matlab script for conversion to UTC provided), counts per second in size Bin00 – Bin15, MeanToFBin1/Bin3/Bin5/Bin7 (used for dynamic fan compensation of the inlet fan), count/s, sample period [s], temperature [x], PM1 [ug/m^3], PM2.5 [ug/m^3], PM10 [ug/m^3], rolling mean PM1 [ug/m^3], rolling mean PM2.5 [ug/m^3], and rolling mean PM10 [ug/m^3].

Methods:

LiDAR: Laser doppler velocimetry principle embedded in the LiDARs purchased from Halo Photonics and Vaisala (Windcube 200S). This helps in retrieving the line-of-sight velocity and atmospheric backscatter for equally spaced range gates for over 2 km radial range. The 28 m and LA towers are 297 m apart. All the LiDARs were placed on wooden platforms on the desert bed; the scanner heights relative to the ground were 1.35 m (200S), 0.89 m (UTD Halo), and 1.19 m (UU Halo). The five OPCs were mounted at 9 m, 12 m, and 18 m on the 28-m tower and at 2 m and 9 m on the LA1 tower. The ceilometer measuring height was 0.62 m. Sonic: Sonic anemometry principle Ceilometer: Similar principle of LiDAR, but it points vertically upwards with a higher range. Optical Particle Counter (OPC): Laser illuminated optical system which allows particle sampling by collecting the scattered light from each particle with a solid-state detector.

Instruments:

CSAT3 sonic anemometer (Campbell Scientific), Ceilometer CL31 (Vaisala), Halo Photonics LiDARs, WindCube 200S Lidar (Vaisala), OPC-N2 optical particle sensor (Alphasense, Ltd.).

Individual Files: