Radar Wind Profiler

Lehmann, Volker; Brown, William O.

doi:10.1007/978-3-030-52171-4_31

Cited by 3 publications

(1 citation statement)

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“…Radar wind profilers (hereafter RWPs) are designed to retrieve the vertical profile of the wind, through processing Doppler spectra, typically using wavelengths between 20 cm to 6 m, where attenuation by rain can be considered negligible. Bragg and Rayleigh backscattering at these wavelengths, respectively, allows detection of atmospheric echoes caused by both clear air and hydrometeor particles, respectively [1,2]. Depending on the operating frequency, RWPs are often classified as Very High Frequency (VHF band, from 30 MHz to 300 MHz) and Ultra-high frequency (UHF band, from 300 MHz to 3 GHz).…”

Section: Introductionmentioning

confidence: 99%

Multiple Characteristics of Precipitation Inferred from Wind Profiler Radar Doppler Spectra

et al. 2022

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A methodology to process radar wind profiler Doppler spectra is presented and implemented for an UHF Degreane PCL1300 system. First, double peak signal detection is conducted at each height level and, then, vertical continuity checks for each radar beam ensure physically consistent measurements. Second, horizontal and vertical wind, kinetic energy flux components, Doppler moments, and different precipitation-related variables are computed. The latter include a new precipitation type estimate, which considers rain, snow, and mixed types, and, finally, specific variables for liquid precipitation, including drop size distribution parameters, liquid water content and rainfall rate. The methodology is illustrated with a 48 h precipitation event, recorded during the Cerdanya-2017 field campaign, carried out in the Eastern Pyrenees. Verification is performed with a previously existing process for wind profiler data regarding wind components, plus precipitation estimates derived from Micro Rain Radar and disdrometer observations. The results indicated that the new methodology produced comparable estimates of wind components to the previous methodology (Bias < 0.1 m/s, RMSE ≈ 1.1 m/s), and was skilled in determining precipitation type when comparing the lowest estimate of disdrometer data for snow and rain, but did not correctly identify mixed precipitation cases. The proposed methodology, called UBWPP, is available at the GitHub repository.

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Section: Introductionmentioning

confidence: 99%