Polarimetric radar measurements and products perform as the cornerstones of modern severe weather warning and nowcast systems. Two radar quantitative precipitation estimation (QPE) frameworks, one based on a radar-gauge feedback mechanism and the other based on standard rain drop size distribution (DSD)-derived rainfall retrieval relationships, are both evaluated and investigated through an extreme severe convective rainfall event that occurred on 23 June 2015 in the mountainous region over eastern China, using the first routinely operational C-band polarimetric radar in China. Complex rainstorm characteristics, as indicated by polarimetric radar observables, are also presented to account for the severe rainfall field center located in the gap between gauge stations. Our results show that (i) the improvements of the gauge-feedback-derived radar QPE estimator can be attributed to the attenuation correction technique and dynamically adjusted Z–R relationships, but it greatly relies on the gauge measurement accuracy. (ii) A DSD-derived radar QPE estimator based on the specific differential phase (K_DP) performs best among all rainfall estimators, and the interaction between the mesocyclone and the windward slope of the mountainous terrain can account for its apparent overestimation. (iii) The rainstorm is mainly dominated by small-sized and moderate-sized raindrops, with the mean volume diameter being less than 2 mm, but its K_DP column (K_DP > 3°·km⁻¹) has a liquid water content that is higher than 2.4815 g·m⁻³, and a high raindrop concentration (N_w) with log₁₀(N_w) exceeding 5.1 mm⁻¹m⁻³. In addition, small hailstones falling and melting are also found in this event, which further aggregates N_w upon the severe rainfall center in the gap between gauge stations.

The millimeter-wave cloud radar, ceilometer, and disdrometer have been widely used to observe clouds and precipitation. However, there are some drawbacks when those three instruments are solely employed due to their own limitations, such as the fact that radars usually suffer from signal attenuation and ceilometers/disdrometers cannot provide measurements of the hydrometeors of aloft clouds and precipitation. Thus, in this paper, we developed an integrated technology by combining and utilizing the advantages of three instruments together to investigate the vertical structure and diurnal variation of warm clouds and precipitation, and the raindrop size distribution. Specifically, the technology consists of appropriate data processing, quality control, and retrieval methods. It was implemented to study the warm clouds and precipitation in South China during the pre-flood season of 2016. The results showed that the hydrometeors of warm clouds and precipitation were mainly distributed below 2.5 km and most of the rainfall events were very light with a rain rate less than 1 mm h⁻¹, however, the stronger precipitation primarily contributed the accumulated rain amount. Furthermore, a rising trend of cloud base height from 1000 to 1900 BJT was found. The cloud top height and cloud thickness gradually increased from 1200 BJT to reach a maximum at 1600 BJT (Beijing Standard Time, UTC+8), and then decreased until 2000 BJT. Also, three periods of the apparent rainfall on the ground of the day, namely, 0400–0700 BJT, 1400–1800 BJT, and 2300–2400 BJT were observed. During three periods, the raindrops had wider size spectra, higher number concentrations, larger rain rates, and higher water contents than at other times. The hydrometeor type, size, and concentration were gradually changed in the vertical orientation. The raindrop size distributions of warm precipitation in the air and on the ground were different, which can be expressed by $\gamma$ distributions N(D) = 1.49 × 10⁴D^−0.9484exp(−6.79D) in the air and N(D) = 1.875 × 10³D^0.862exp(−2.444D) on the ground, where D and N(D) denote the diameter and number concentration of the raindrops, respectively.

Precipitation microphysics over the Tibetan Plateau (TP) remain insufficiently understood, due to the lack of observations and studies. This paper presents a comprehensive investigation of the raindrop size distribution (DSD) for rainfall that happened on the eastern slope of TP in summer. DSD differences between different rain types and under different rain rates are investigated. Confidential empirical relationships between the gamma shape and slope parameters, and between reflectivity and rain rate are proposed. DSD properties in this area are also compared with those in other areas. The results indicate that the stratiform and convective rains contribute to different rain duration and amount, with diverse rainfall macro- and microphysical properties. The rain spectra of two rain types can become broader with higher concentrations as the rain rate increases. DSDs in this area are different to those in other areas. The stratiform DSD is narrower than that in the non-plateau area. The two rain types of this area both have higher number concentrations for 0.437–1.625 mm raindrops than those of the mid-TP. The relationships of shape–slope parameters and reflectivity–rain rate in this area are also different from those in other areas. The rain spectra in this area can produce a larger slope parameter under the same shape parameter than in the mid-TP. The convective rain can produce a smaller rain rate under the same reflectivity. The accuracy proposed reflectivity–rain rate relationship in application to quantitative rainfall estimation is also discussed. The results show that the relationship has an excellent performance when the rain rate exceeds 1 mm h⁻¹.

The complex precipitation microphysics associated with super typhoon Lekima (2019) and its potential impacts on the consistency of multi-source datasets and radar quantitative precipitation estimation were disentangled using a suite of in situ and remote sensing observations around the waterlogged area in the groove windward slope (GWS) of Yandang Mountain (YDM) and Kuocang Mountain, China. The main findings include the following: (i) the quality control processing for radar and disdrometers, which collect raindrop size distribution (DSD) data, effectively enhances the self-consistency between radar measurements, such as radar reflectivity (Z_H), differential reflectivity (Z_DR), and the specific differential phase (K_DP), as well as the consistency between radar, disdrometers, and gauges. (ii) The microphysical processes, in which breakup overwhelms coalescence in the coalescence–breakup balance of precipitation particles, noticeably make radar measurements prone to be breakup-dominated in radar volume gates, which accounts for the phenomenon where the high number concentration rather than the large size of drops contributes more to a given attenuation-corrected Z_H ($Z_{\mathrm{H}}^{\mathrm{C}}$ ) and the significant deviation of attenuation-corrected Z_DR ($Z_{\mathrm{DR}}^{\mathrm{C}}$ ) from its expected values (${\widehat{Z}}_{\mathrm{DR}}$ ) estimated by DSD-simulated Z_DR–Z_H relationships. (iii) The twin-parameter radar rainfall estimates based on measured Z_H ($Z_{\mathrm{H}}^{\mathrm{M}}$ ) and Z_DR ($Z_{\mathrm{DR}}^{\mathrm{M}}$ ), and their corrected counterparts $Z_{\mathrm{H}}^{\mathrm{C}}$ and $Z_{\mathrm{DR}}^{\mathrm{C}}$ , i.e., R($Z_{\mathrm{H}}^{\mathrm{M}}$ , $Z_{\mathrm{DR}}^{\mathrm{M}}$ ) and R($Z_{\mathrm{H}}^{\mathrm{C}}$ , $Z_{\mathrm{DR}}^{\mathrm{C}}$ ), both tend to overestimate rainfall around the GWS of YDM, mainly ascribed to the unique microphysical process in which the breakup-dominated small-sized drops above transition to the coalescence-dominated large-sized drops falling near the surface. (iv) The improved performance of R($Z_{\mathrm{H}}^{\mathrm{C}}$ , ${\widehat{Z}}_{\mathrm{DR}}$ ) is attributed to the utilization of ${\widehat{Z}}_{\mathrm{DR}}$ , which equals physically converting breakup-dominated measurements in radar volume gates to their coalescence-dominated counterparts, and this also benefits from the better self-consistency between $Z_{\mathrm{H}}^{\mathrm{C}}$ , ${\widehat{Z}}_{\mathrm{DR}}$ , and K_DP, as well as their consistency with the surface counterparts.

Polarimetric radar provides more choices and advantages for quantitative precipitation estimation (QPE) than single-polarization radar. Utilizing the C-band polarimetric radar in Hangzhou, China, six radar QPE estimators based on the horizontal reflectivity (Z_H), specific attenuation (A_H), specific differential phase (K_DP), and double parameters that further integrate the differential reflectivity (Z_DR), namely, R(Z_H, Z_DR), R(K_DP, Z_DR), and R(A_H, Z_DR), are investigated for an extreme precipitation event that occurred in Eastern China on 1 June 2016. These radar QPE estimators are respectively evaluated and compared with a local rain gauge network and drop size distribution data observed by two disdrometers. The results show that (i) although R(A_H, Z_DR) underestimates in the light rain scenario, it performs the best among all radar QPE estimators according to the normalized mean error; (ii) the optimal radar rainfall relationship and consistency between radar measurements aloft and their surface counterparts are both required to obtain accurate rainfall estimates close to the ground. The contamination from melting layer on A_H and K_DP can make R(A_H), R(A_H, Z_DR), R(K_DP), and R(K_DP, Z_DR) less effective than R(Z_H) and R(Z_H,Z_DR). Instead, adjustments of the α coefficient can partly reduce such impact and hence render a superior A_H–based rainfall estimator; (iii) each radar QPE estimator may outperform others during some time intervals featured by particular rainfall characteristics, but they all tend to underestimate rainfall if radar fails to capture the rapid development of rainstorms.

Under different water vapor and dynamic conditions, and the influence of topographies and atmospheric environments, stratiform precipitation over South China and the Tibetan Plateau can produce different features. In this study, stratiform precipitation vertical characteristics, bright-band (BB) microstructures, and the vertical variations of the raindrop size distribution (DSD) over a low-altitude site (Longmen site, 86 m) in South China and a high-altitude site (Nagqu site, 4507 m) on the Tibetan Plateau were comprehensively investigated and compared using measurements from a Ka-band millimeter-wave cloud radar (CR), a K-band microrain radar (MRR), and a Parsivel disdrometer (disdrometer). A reliable BB identification scheme was proposed on the basis of CR variables and used for stratiform precipitation sample selection and further statistics and analysis. Results indicate that melting layers over the Longmen are much higher and slightly thicker than those over the Nagqu due to significant differences in atmospheric conditions. For stratiform precipitation, vertical air motions and radar variables over the two sites show different variation trends from cloud top to the ground. Vertical air motions are very weak in the stratiform precipitation over the Longmen, whereas updrafts are more active over the Nagqu. Above the melting layer, radar equivalent reflectivity factor $Z_e$ (mean Doppler velocity $V_M$) gradually increases (decreases) as height decreases over the two sites, but the aggregation rate for ice particles over the Longmen can be faster. In the melting layer, $Z_e$ ($V_M$) at the BB bottom/center over the Longmen is larger (smaller) than those over the Nagqu for the reason that melted raindrops in the melting layers over the Longmen are larger than those over the Nagqu. Below the melting layer, profiles of radar variables and DSDs show completely different behaviors over the two sites, which reflects that the collision, coalescence, evaporation, and breakup processes of raindrops are different between the two sites. Over the Longmen, collision and coalescence dominate the precipitation properties; in particular, from 2.0–2.8 km, the breakup process competes with collision–coalescence processes but later is overpowered. In contrast, due to the lower BB heights over the Nagqu, collision and coalescence dominate raindrop properties. Comparisons of raindrop spectra suggest that the concentration of small (medium-to-large) raindrops over the Nagqu is much higher (slightly lower) than that over the Longmen. Therefore, the mass-weighted mean diameter $D_m$ (the generalized intercept parameter $N_w$) over the Nagqu is smaller (larger) than that over the Longmen.