Evaluation and application of hydrometeor classification algorithm outputs inferred from multi‐frequency dual‐polarimetric radar observations collected during HyMeX

Abstract

International audienceA fuzzy logic hydrometeor classification algorithm (HCA), allowing discrimination between six microphysical species regardless of the radar wavelength is presented and evaluated. The proposed method is based upon combination sets of dual-polarimetric observables (reflectivity at horizontal polarization ZH, differential reflectivity ZDR, specific differential phase KDP, correlation coefficient ρHV) along with temperature data inferred from a numerical weather prediction model output.The performance of the HCA is evaluated using 20 h of multi-frequency dual-polarimetric radar data collected during the first Special Observation Period (SOP1) of the Hydrological Cycle in the Mediterranean Experiment (HyMeX). A new method based upon intercomparisons of retrieved hydrometeor data deduced from pairs of neighbouring radars (S-band vs. S-band and S-band vs. C-band) over a common sampling area is proposed to evaluate the consistency of hydrometor classification outputs. S-/C-band radar comparisons generally show better consistency than S-/S-band radar comparisons due to issues with the identification of the 0°C isotherm on one of the two S-band radars. Imperfect attenuation correction at C-band may also lead into differences in hydrometeor fields retrieved from the C- and S-band radars in convective situations, but retrieved hydrometeor data are globally very consistent from one radar to another. Comparisons against in situ airborne data also confirm the overall good performance of the HCA.In a second experiment, an original method allowing the production of multi-radar three-dimensional (3D) hydrometeor fields from single-radar 2D hydrometeor data is tested on a bow-echo convective system observed with C- and S-band radars. The resulting 3D hydrometeor fields provide a detailed view of the bow-echo microphysical structure and confirm the good performance of both the HCA and interpolation technique

Relationships between total lightning activity, microphysics and kinematics during the 24 September 2012 HyMeX bow‐echo system

“…Once pre‐processed dual‐polarimetric radar observables (horizontal reflectivity ( Z H ), and differential ( Z DR ) reflectivity, differential phase ( Φ DP ) and coefficient correlation ( ρ HV )) are ingested into a modified version of the fuzzy logic, hydrometeor classification algorithm initially proposed by Al‐Sakka et al (), this new version of the algorithm (Ribaud et al , 2015) improves hydrometeor classification through discriminating between stratiform and convective precipitation and now allows for graupel identification. Hydrometeor fields are retrieved for each radar at the temporal resolution of 15 min before being aggregated to produce a two‐radar composite over the domain of analysis shown in Figure .…”

“…Three-dimensional hydrometeor fields are derived from the analysis of Montclar (C-band) and Nîmes (S-band) dualpolarization radar observations ( Figure 1). Dual-polarimetric radar data are processed according to the procedures described in Figueras i Ventura et al (2012) and Ribaud et al (2016). The pre-processing consists in the six steps described hereafter: (i) correction for potential differential reflectivity (Z DR ) miscalibration following the approaches of Illingworth and Blackman (2002) and Gourley et al (2006); (ii) discrimination between meteorological and non-meteorological echoes (Gourley et al, 2007); (iii) estimation of the 0 • C isotherm altitude from polarimetric data (Giangrande et al, 2008) and operational model analyses (here located at ∼3.5 km above mean sea level (AMSL) for the present case-study); (iv) estimation of the specific differential phase (K DP ); (v) correction of signal attenuation following the approach of Tabary et al (2009); (vi) application of thresholds on signal-to-noise ratio (15 dB) and partial beam blockage (10%).…”

Assimilation of radar dual‐polarization observations in the AROME model

“…This profile was selected in the most active part of a convective line observed at 0600 UTC on 24 September 2012, as can be seen with maximum reflectivities around 58 dBZ (black line in Figure a), strong Z dr (∼ 2.4 dB) and K dp (up to 3.3° km −1 ). The hydrometeor classification scheme (Al‐Sakka et al , ) suggests the presence of hail within this profile (not shown), which is consistent with the study of Ribaud et al s*() who also indicated that hail was produced by this convective system.…”

Thunderstorm hail and lightning detection parameters based on dual‐polarization Doppler weather radar data

“…Waldvogel et al, 1979;Auer, 1994;Witt et al, 1998;Holleman, 2001) and in recent years from polarimetric radar observables (e.g. Kaltenboeck and Ryzhkov, 2013;Ribaud et al, 2015;Ortega et al, 2016). As national weather radar networks adopt dual-polarization radar technology, the hail detection methods will also transition to those based on dual-polarization hydrometeor classification.…”