Multiple Characteristics of Precipitation Inferred from Wind Profiler Radar Doppler Spectra

被引:6
作者
Garcia-Benadi, Albert [1 ,2 ]
Bech, Joan [2 ,3 ]
Udina, Mireia [2 ]
Campistron, Bernard [4 ]
Paci, Alexandre [5 ]
机构
[1] Univ Politecn Cataluna, SARTI, Vilanova I La Geltru 08800, Spain
[2] Univ Barcelona, Dept Appl Phys Meteorol, Barcelona 08028, Spain
[3] Univ Barcelona, Water Res Inst, Barcelona 08007, Spain
[4] Univ Paul Sabatier, Lab Aerol, F-31400 Toulouse, France
[5] Univ Toulouse, CNRS, METEO FRANCE, CNRM, F-38400 Toulouse, France
关键词
hydrometeor type estimation; Doppler; wind profiler; pulsed radar; MOMENTS ESTIMATION; NETWORK; RAIN; IDENTIFICATION; PERFORMANCE; VELOCITY; AIR;
D O I
10.3390/rs14195023
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 approximate to 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.
引用
收藏
页数:23
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