1. Multiple characteristics of precipitation inferred from wind profiler radar Doppler spectra
- Author
-
Albert Garcia-Benadi, Joan Bech, Mireia Udina, Bernard Campistron, Alexandre Paci, Centre Tecnològic de Vilanova i la Geltrú, Universitat Politècnica de Catalunya [Barcelona] (UPC), Universitat de Barcelona (UB), Laboratoire d'aérologie (LAERO), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), and The Cerdanya-2017 field campaign was a research effort organized by the University of the Balearic Islands, the University of Barcelona, METEO-FRANCE and the Meteorological Service of Catalonia (SMC). This research was funded by the Spanish Government through projects CGL 2009-12797-C03-02 and CGL 2009-12797-C03-03 and the Water Research Institute (IdRA) of the University of Barcelona.
- Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere ,Radar ,Radarmeteorologia ,pulsed radar ,Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Radar [Àrees temàtiques de la UPC] ,Doppler ,hydrometeor type estimation ,Efecte de Doppler ,Precipitacions (Meteorologia) -- Mesurament ,Winds ,Vents ,Doppler effect ,Precipitation (Meteorology) -- Measurement ,Hydrometeor type estimation ,Pluja ,wind profiler ,Wind profiler ,Pulsed radar ,Enginyeria electrònica::Instrumentació i mesura::Sensors i actuadors [Àrees temàtiques de la UPC] ,Rain and rainfall ,Radar meteorology ,[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,General Earth and Planetary Sciences - Abstract
International audience; 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.
- Published
- 2022