Recovery of the three-dimensional wind and sonic temperature data from a physically deformed sonic anemometer

• Published in: Atmospheric Measurement Techniques
• Main Authors: X. Zhou, Q. Yang, X. Zhen, Y. Li, G. Hao, H. Shen, T. Gao, Y. Sun, N. Zheng
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2018
• Subjects: Environmental engineering; TA170-171; Earthwork. Foundations; TA715-787; Antarc*; Antarctica
• Online Access: https://doi.org/10.5194/amt-11-5981-2018; https://doaj.org/article/83f220930cdd40208234567b89bbf135

A sonic anemometer reports three-dimensional (3-D) wind and sonic temperature ( T s ) by measuring the time of ultrasonic signals transmitting along each of its three sonic paths, whose geometry of lengths and angles in the anemometer coordinate system was precisely determined through production calibrations and the geometry data were embedded into the sonic anemometer operating system (OS) for internal computations. If this geometry is deformed, although correctly measuring the time, the sonic anemometer continues to use its embedded geometry data for internal computations, resulting in incorrect output of 3-D wind and T s data. However, if the geometry is remeasured (i.e., recalibrated) and to update the OS, the sonic anemometer can resume outputting correct data. In some cases, where immediate recalibration is not possible, a deformed sonic anemometer can be used because the ultrasonic signal-transmitting time is still correctly measured and the correct time can be used to recover the data through post processing. For example, in 2015, a sonic anemometer was geometrically deformed during transportation to Antarctica. Immediate deployment was critical, so the deformed sonic anemometer was used until a replacement arrived in 2016. Equations and algorithms were developed and implemented into the post-processing software to recover wind data with and without transducer-shadow correction and T s data with crosswind correction. Post-processing used two geometric datasets, production calibration and recalibration, to recover the wind and T s data from May 2015 to January 2016. The recovery reduced the difference of 9.60 to 8.93 °C between measured and calculated T s to 0.81 to −0.45 °C, which is within the expected range, due to normal measurement errors. The recovered data were further processed to derive fluxes. As data reacquisition is time-consuming and expensive, this data-recovery approach is a cost-effective and time-saving option for similar cases. The equation development can be a reference for related ...