Improvement of X-Band Polarization Radar Melting Layer Recognition by the Bayesian Method and ITS Impact on Hydrometeor Classification

Using melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasUsing melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.ted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.

Statistics-based Optimization of the Polarimetric Radar Hydrometeor Classification Algorithm and Its Application for a Squall Line in South China

A modified hydrometeor classification algorithm （HCA） is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results---especially in the mixed rain-hail region--can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar- detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.

Possibility of Solid Hydrometeor Growth Zone Identification Using Radar Spectrum Width

In this study,the correlation between simulated and measured radar velocity spectrum width(σ_(v))is investigated.The results show that the dendrites growth zones(DGZs)and needles growth zones(NGZs)mostly contain dendrites(DN)and needles(NE),respectively.Clearσ_(v) zones(1.1<σ_(v)(m s^(-1))<1.3 and 0.3<σ_(v)(m s^(-1))<0.7 for the DGZ and NGZ,respectively)could be identified in the case studies(27 and 28 February 2016)near altitudes corresponding to temperatures of–15°C and–5°C,according to the Japan Meteorological Agency and mesoscale model reanalysis data.Oblate particles with diverse particle shapes were observed in the DGZ withσ_(v)>1.2 m s^(-1),a differential reflectivity(ZDR)higher than 0 dB,and a cross-correlation coefficient(ρhv)less than 0.96.In contrast,prolate particles with relatively uniform shapes were observed in the NGZ withσ_(v)<0.6 m s^(-1),a ZDR less than 0 dB,andρhv higher than 0.97.The simulation results show that the DN exhibited a largerσ_(v) compared to the NE,and this observedσ_(v) was strongly dependent on the wind fluctuations(v’)due to turbulence or wind shear.In contrast,the NE exhibited a significantly smallσ_(v)~0.55 m s^(-1),which converges irrespective of v’.In addition,a strong correlation between the measuredσ_(v) values at five radar elevation angles(θ=6.2°,9.1°,13.1°,19°,and 80°)and those simulated in this study confirmed the significance of the analysis results.

Classification of Precipitation Types Using Fall Velocity–Diameter Relationships from 2D-Video Distrometer Measurements

Fall velocity–diameter relationships for four different snowflake types（dendrite,plate,needle,and graupel） were investigated in northeastern South Korea,and a new algorithm for classifying hydrometeors is proposed for distrometric measurements based on the new relationships.Falling ice crystals（approximately 40 000 particles） were measured with a two-dimensional video disdrometer（2DVD） during a winter experiment from 15 January to 9 April 2010.The fall velocity–diameter relationships were derived for the four types of snowflakes based on manual classification by experts using snow photos and 2DVD measurements：the coefficients（exponents） for different snowflake types were 0.82（0.24） for dendrite,0.74（0.35） for plate,1.03（0.71） for needle,and 1.30（0.94） for graupel,respectively.These new relationships established in the present study（PS） were compared with those from two previous studies.Hydrometeor types were classified with the derived fall velocity–diameter relationships,and the classification algorithm was evaluated using 3 × 3 contingency tables for one rain–snow transition event and three snowfall events.The algorithm showed good performance for the transition event：the critical success indices（CSIs） were 0.89,0.61 and 0.71 for snow,wet-snow and rain,respectively.For snow events,the algorithm performance for dendrite and plate（CSIs = 1.0 and 1.0,respectively） was better than for needle and graupel（CSIs = 0.67 and 0.50,respectively）.

Variability of Raindrop Size Distribution during a Regional Freezing Rain Event in the Jianghan Plain of Central China

The characteristics of the raindrop size distribution(DSD)during regional freezing rain(FR)events that occur throughout the phase change(from liquid to solid)are poorly understood due to limited observations.We investigate the evolution of microphysical parameters and the key formation mechanisms of regional FR using the DSDs from five disdrometer sites in January 2018 in the Jianghan Plain(JHP)of Central China.FR is identified via the size and velocity distribution measured from a disdrometer,the discrete Fréchet distancemethod,surface temperature,human observations,and sounding data.With the persistence of precipitation,the emergence of graupel or snowflakes significantly reduces the proportion of FR.The enhancement of this regional FR event is mainly dominated by the increase in the number concentration of raindrops but weakly affected by the diameters.To improve the accuracy of quantitative precipitation estimation for the FR event,a modified second-degree polynomial relation between the shapeμand slopeΛof gamma DSDs is derived,and a new Z-R(radar reflectivity to rain rate)relationship is developed.The mean values of mass-weighted mean diameters(D_(m))and generalized intercepts(lgN_(w))in FR are close to the stratiform results in the northern region of China.Both the melting of tiny-rimed graupels and large-dry snowflakes are a response to the formation of this regional FR process in the JHP,dominated by the joint influence of the physical mechanism of warm rain,vapor deposition,and aggregation/riming coupled with the effect of weak convective motion in some periods.

Operational Evaluation of the Quantitative Precipitation Estimation by a CINRAD-SA Dual Polarization Radar System

In this paper,a quantitative precipitation estimation based on the hydrometeor classification(HCA-QPE)algorithm was proposed for the first operational S band dual-polarization radar upgraded from the CINRAD/SA radar of China.The HCA-QPE algorithm,localized Colorado State University-Hydrometeor Identification of Rainfall(CSUHIDRO)algorithm,the Joint Polarization Experiment(JPOLE)algorithm,and the dynamic Z-R relationships based on variational correction QPE(DRVC-QPE)algorithm were evaluated with the rainfall events from March 1 to October 30,2017 in Guangdong Province.The results indicated that even though the HCA-QPE algorithm did not use the observed rainfall data for correction,its estimation accuracy was better than that of the DRVC-QPE algorithm when the rainfall rate was greater than 5 mm h-1;and the stronger the rainfall intensity,the greater the QPE improvement.Besides,the HCA-QPE algorithm worked better than the localized CSU-HIDRO and JPOLE algorithms.This study preliminarily evaluated the improved accuracy of QPE by a dual-polarization radar system modified from CINRAD-SA radar.