**1. Introduction**

Characteristics of raindrop size distribution (DSD) are of great importance in various disciplinary research. They are the physical basis in the formation of clouds and precipitation [1]. Understanding the DSD is critical for the microphysical parameterizations in numerical weather prediction models [2–4], and quantitative precipitation estimation (QPE) using remote sensing technologies, such as radar and satellite [5,6]. The DSDs can also be utilized to estimate the kinetic energy of rain [7], which is a key factor in assessing the degree of soil erosion [8]. To this end, numerous studies have been conducted around the world to characterize the DSD in different climate regions and rainfall types, using a variety of in situ and remote sensing instruments [9–16].

The DSD can be affected by many factors [17], including microphysical processes, such as condensation, evaporation, collision–coalescence and breakup [18], updrafts and downdrafts [19], horizontal winds [20], orographic effects [21], and aerosol effects [22].

The climatological characteristics of precipitation in Beijing, China, have been examined using rainfall data collected at automatic weather stations [23,24] and radar reflectivity mosaics [25,26]. However, the microphysical structure of surface precipitation in Beijing is rarely reported, due to the lack of long-term ground-based DSD measurements. Using a first-generation laser-optical particle size and velocity (PARSIVEL) disdrometer manufactured by OTT Hydromet, Germany [27], Tang et al. [28] compared the characteristics of measured and fitted DSDs, as well as the retrieved dual-polarization radar variables for stratiform and convective precipitation in Beijing. However, the DSD samples used by Tang et al. [28] were only collected from July to October 2008, which did not include precipitation occurred in June that makes a significant contribution to the total annual rainfall in Beijing [24,29]. In addition, those DSD data were collected mainly under the conditions of improved air quality and lower aerosol concentration associated with strict emission-reduction during the Beijing Olympic and Paralympic Games [30], which may not be sufficient to represent normal air quality conditions in Beijing [31], since the concentrations and components of aerosols could potentially affect the DSD properties [22,32]. A second-generation PARSIVEL disdrometer (hereafter referred to as PARSIVEL2) was used to study the snowfall properties over the mountains in northwestern Beijing [33]. Unfortunately, no long-term rainfall observations were reported using this instrument.

From 2017, a PARSIVEL<sup>2</sup> disdrometer was deployed at a national weather station in Beijing (116.47◦E, 39.8◦N; 31.3 m a.s.l.) to perform continuous microphysical measurements of rainfall on the ground, which provides an opportunity to investigate the characteristics of local DSD comprehensively. In addition, the DSD data can provide a means for improving the accuracy of remote sensing retrievals, such as polarimetric radar quantitative precipitation estimation (QPE) [34,35] and enhance the operational weather forecast model in Beijing (i.e., the Rapid-refresh Multi-scale Analysis and Prediction System–RMAPS [36]). This study aims to conduct a detailed investigation of DSD characteristics in Beijing using this disdrometer data. This paper is organized as follows. Section 2 describes the data and analysis methods, including the data quality control procedure and DSD parameters to be included in this study. Based on the quality-controlled disdrometer dataset, Section 3 describes the microphysical properties of DSDs in log10 *Nw*–*D*<sup>0</sup> domain, as well as the comparison with other climate regions. Classification of different rain types is also detailed in Section 3. Section 4 derives the radar-based QPE estimators and quantifies the associated errors of various estimators using collocated gauge measurements. Major conclusions are summarized in Section 5.
