Overview
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minutes. The eight Tritons are located at various sites around the WFIP2 study area.
Data Details
Regarding the minimum requirements for the site description, a Keyhole Markup Language (KML) file is attached with all of the AON Triton locations. Unfortunately, there are no photos of the sites. The layout of each site is simple. At all locations, the Triton Wind Profiler is placed on the ground with the solar panel facing due south. Each unit is solar powered and communicates its data via satellite, so there are no cables of any kind. Also, the specified start and end dates are for the entire AON network. Some individual units start later or end earlier. All start/end dates for the individual units are given as follows:
AON1 (z17): 10/1/2015 -- 7/31/2017
AON2 (z14): 10/1/2015 -- 7/31/2017
AON3 (z18): 10/1/2015 -- 7/31/2017
AON4 (z12): 12/5/2015 -- 7/31/2017
AON5 (z06): 10/1/2015 -- 7/31/2017
AON6 (z05): 10/1/2015 -- 7/31/2017 (w/gap 2016-08-01 -- 2016-09-28)
AON7 (z02): 10/1/2015 -- 7/31/2017 (w/gap 2016-07-01 -- 2016-11-18)
AON8 (z01): 12/7/2015 -- 4/9/2016
AON9 (z20): 11/19/2016 -- 7/31/2017
Data Quality
The Triton firmware has a quality assessment algorithm that assigns a quality factor (“quality” or QF) to each time/height measurement of wind, expressed as a percent value in the range 0-100. In addition, the upward Doppler velocity (“vert”) is measured and can be used as an indicator of falling precipitation, which negatively affects data quality. In this data level ("a0"), no filtering has been applied based on these two (or any other) criteria, although the two variables, QF and vertical velocity, are provided. The purpose of the a0 data level is to provide expert users an opportunity to view and quality control (QC) all the data at their discretion, using whatever filtering procedures they wish. For guidance, two commonly used filtering criteria (used in both the 00 and b0 data levels) set data to a missing value (null in the CSV file) when either “quality” < 90% or “vert” < -1.5 m/s. However, these have not been applied in this "expert version" (level b0) of the data. Note, the QF applies to all variables, except turbulence. Turbulence has its own QF, which should be used separately for filtering the turbulence variable (although vertical velocity filtering remains appropriate to perform on turbulence as well). Finally, the data have been visually inspected for time periods that are obviously suspect, and a suspect_flag is defined, which is set to "0" at times that look reasonable and to "1" at times that look obviously bad. Again, the data have not been filtered on this flag. However, the flag is provided for users to filter as they choose.
Uncertainty
When compared to nearby towers instrumented with cup anemometers and wind vanes, the root mean square (RMS) difference in 10-minute wind speed between the Triton and met tower typically is around 0.5 m s-1. When tested at 30 different sites in a recent validation study, the RMS difference in long-term mean wind speed between the Triton and met tower is 1.3%.
Constraints
Various meteorological and environmental conditions can lead to either weaker returns or enhanced noise, resulting in a poor measurement. The higher the target point, the more difficult it is to retrieve a strong signal. Hence, a common situation is that good data will be obtained up to some height then not above it. The percentage of time that good data are recovered at a particular height is the data recovery rate. In a recent validation study, data recovery rates were around 98% at lower heights, slowly dropping off to 96% at 100 m, 83% at 160 m, and 70% at 200 m.
