Fourteen-month precipitation measurements from a second-generation PARSIVEL disdrometer deployed in Beijing, northern China, were analyzed to investigate the microphysical structure of raindrop size distribution and its implications on polarimetric radar applications. Rainfall types are classified and analyzed in the domain of median volume diameter $D_0$ and the normalized intercept parameter $N_w$ . The separation line between convective and stratiform rain is almost equivalent to rain rate at 8.6 mm h⁻¹ and radar reflectivity at 36.8 dBZ. Convective rain in Beijing shows distinct seasonal variations in ${\log }_{10}{N}_w–D_0$ domain. X-band dual-polarization variables are simulated using the T-matrix method to derive radar-based quantitative precipitation estimation (QPE) estimators, and rainfall products at hourly scale are evaluated for four radar QPE estimators using collocated but independent rain gauge observations. This study also combines the advantages of individual estimators based on the thresholds on polarimetric variables. Results show that the blended QPE estimator has better performance than others. The rainfall microphysical analysis presented in this study is expected to facilitate the development of a high-resolution X-band radar network for urban QPE applications.

Beijing, China, is located in a region of complex terrain with high mountain ridges to the northwest and the Bohai Sea to the southeast. The origin of convective storms occurring on the plains can often be traced to the upstream mountains. Under weakly forced conditions, these convective storms most frequently evolve into squall lines (SL) and convective clusters (CC) when reaching the plains. In this study, we analyze 18 SL and 15 CC storm systems and assess their environmental and mesoscale differences between the two phenomena. By analyzing the frequency of convective occurrence for the two types of storms based on composite radar reflectivity, it is found that the high frequencies are located in the south of Beijing for SL and near the center of Beijing for CC. Using storm‐scale reanalysis data produced by a rapid update four‐dimensional variational analysis system that assimilates Doppler radar observations, distinct features of the SL and CC storms are revealed in terms of their convective environments and mesoscale structures, such as cold pool, horizontal wind convergence, and humidity distribution. It is found that low convective inhibition and high low‐level wind speed on the plains are common to both SL and CC, whereas higher vertical shear over the plains and stronger wind speed on both mountains and plains distinguishes SL from CC. We further show that the stronger wind and vertical shear in SL generate stronger and more organized downdrafts, producing a deeper cold pool, strong outflow and convergence, which explains the formation of the high‐frequency center in the south of Beijing. In contrast, the cold pool produced in CC is shallower and weaker, resulting in weaker outflow and convergence and convective activities that are located only in central Beijing.

This study assesses the benefit of convective‐scale data assimilation (DA) for model initialization using well‐known functional relationships between lightning flash rate and vertical velocity. Based on the relationships, a lightning DA scheme to update model kinematic states was implemented in the Weather Research and Forecasting Data Assimilation (WRFDA) three‐dimensional variational (3DVar) system. This scheme combines total lightning observations with model‐based prescribed vertical velocity profiles to retrieve kinematic information through a DA scheme. With the availability of space‐borne lightning imagers in recent years, total lightning observations from the Lightning Mapping Imager (LMI) on board the FY‐4A geostationary satellite were assimilated in combination with radar DA. A detailed analysis of the impact of the lightning DA scheme on convective precipitation forecasting was conducted using a squall line case over Beijing on 13 July 2017. The assimilation of LMI data provides added benefits to the assimilation of radar radial winds by reducing wind errors and strengthening convergence along the squall line in the analysis. Although the microphysical states are identical due to the assimilation of reflectivity, the lightning DA scheme helps in promoting updraft developments at lightning observation locations, which improves the representation of mixed‐phase convection. The quantitative verification of short‐term convective forecasts indicated that the lightning DA adds value to the radar DA by improving the precipitation forecast skill. The lightning DA scheme was evaluated further for a heavy rainfall case in 2018 over the Beijing metropolitan area and revealed overall similar forecast improvements for composite reflectivity and accumulated rainfall.

A proof-of-concept method for the assimilation of total lightning observations in the 4DVAR framework is proposed and implemented into the Variational Doppler Radar Analysis System (VDRAS). Its performance is evaluated for the very short-term precipitation forecasts of a localized convective event over northeastern China. The lightning DA scheme assimilated pseudo-observations for vertical velocity fields derived from observed total lightning rates and statistically computed vertical velocity profile from VDRAS analysis data. To reduce representative errors of the derived vertical velocity, a distance-weighted horizontal interpolation is applied to the input data prior to the DA. The case study reveals that although 0–2-h precipitation nowcasts are improved by assimilating lightning data alone compared to CTRL (no radar or lightning) and RAD (radar only), better results are obtained when the lightning data are assimilated with radar data simultaneously. The assimilation of both data sources results in improved dynamical consistency with enhanced updraft and latent heat as well as improved moisture distributions. Additional experiments are conducted to evaluate the sensitivity of the combined DA scheme to varied vertical velocity profiles, radii of horizontal interpolation, binning time intervals, and relationships used to estimate the maximum vertical velocity from lightning flash rates. It is shown that the scheme is robust to these variations with both radar and lightning assimilated data.