Snow particle size distribution (PSD) information is important in understanding the microphysics and quantitative precipitation estimation over complex terrain. Measurement and interpretation of the snow PSDs is a topic of active research. This study investigates snow PSDs during 3 year of observations from Parsivel² disdrometers and precipitation imaging packages (PIP) at five different sites in the PyeongChang region of South Korea. Variabilities in the values of the density of snow ($\rho$), snowfall rate ($S$), and ice water content ($IWC$) are studied. To further understand the characteristics of snow PSD at different density and snowfall rate, the snow particle size distribution measurements are divided into six classes based on the density values of snowfall and five classes based on snowfall rates. The mean shape factors ($D_m$, $lo{g}_{10}{N}_w$, and $\mu$) of normalized gamma distribution are also derived based on different density and snowfall rate classes. The $D_m$ decreases and $lo{g}_{10}{N}_w$ and μ increase as the density increases. The $D_m$ and $lo{g}_{10}{N}_w$ increase and μ decreases with the increase of snowfall rate. The power-law relationship between $\rho$ and $D_m$ is obtained and the relationship between $S$ and $IWC$ is also derived.

The seasonal variations of raindrop size distribution (DSD) and rainfall are investigated using three-year (2016–2018) observations from a two-dimensional video disdrometer (2DVD) located at a suburban station (40.13° N, 116.62° E, ~30 m AMSL) in Beijing, China. The annual distribution of rainfall presents a unimodal distribution with a peak in summer with total rainfall of 966.6 mm, followed by fall. Rain rate (R), mass-weighted mean diameter (D_m), and raindrop concentration (N_t) are stratified into six regimes to study their seasonal variation and relative rainfall contribution to the total seasonal rainfall. Heavy drizzle/light rain (R2: 0.2~2.5 mm h⁻¹) has the maximum occurrence frequency throughout the year, while the total rainfall in summer is primarily from heavy rain (R4: 10~50 mm h⁻¹). The rainfall for all seasons is contributed primarily from small raindrops (D_m2: 1.0~2.0 mm). The distribution of occurrence frequency of N_t and the relative rainfall contribution exhibit similar behavior during four seasons with N_t of 10~1000 m⁻³ registering the maximum occurrence and rainfall contributions. Rainfall in Beijing is dominated by stratiform rain (SR) throughout the year. There is no convective rainfall (CR) in winter, i.e., it occurs most often during summer. DSD of SR has minor seasonal differences, but varies significantly in CR. The mean values of log₁₀N_w (N_w: mm⁻¹m⁻³, the generalized intercept parameter) and D_m of CR indicate that the CR during spring and fall in Beijing is neither continental nor maritime, at the same time, the CR in summer is close to the maritime-like cluster. The radar reflectivity (Z) and rain rate ($R$) relationship (Z = $a$R^$b$) showed seasonal differences, but were close to the standard NEXRAD Z-R relationship in summer. The shape of raindrops observed from 2DVD was more spherical than the shape obtained from previous experiments, and the effect of different axis ratio relations on polarimetric radar measurements was investigated through T-matrix-based scattering simulations.

In order to improve the performance of X-band dual-polarization radars, it is necessary to conduct attenuation correction before using the X-band radar data. This study analyzes a variety of attenuation correction methods for the X-band radar reflectivity, and proposes a high-resolution slide self-consistency correction (SSCC) method, which is an improvement of Kim et al.’s method based on Bringi et al.’s original method. The new method is comprehensively evaluated with the observational data of convective cloud, stratiform cloud, and the stratiform cloud with embedded convection. Comparing with the intrinsic reflectivity at X-band calculated from the reflectivity at S-band, it is found that the new method can effectively reduce the correction errors when calculating differential propagation shift increments using the conventional self-consistency attenuation correction method. This method can efficiently correct the X-band dual-polarization radar reflectivity, in particular, for the echoes with reflectivity greater than 35 dBZ.

Based on environmental monitoring data and meteorological observation data of the Chinese major energy province, Shanxi, from 2015 to 2020, using the satellite remote sensing data of Atmospheric Infrared Sounder Instrument (AIRS) and Ozone Monitoring Instrument (OMI) in 2017, we analyzed the characteristics of surface ozone (O₃) pollution and its correlation with meteorological factors, as well as the vertical distribution of O₃ in typical pollution cities in Shanxi Province. The results showed that surface O₃ became the primary pollutant in Shanxi. Surface O₃ has shown a zonal distribution with a high level in the south and a low level in the north region since 2017. Surface O₃ pollution was severe in 2019, and the maximum daily 8 h running average of O₃ (MDA8 O₃) decreased, but annual mean O₃ in northern and central regions showed a slow rising trend in 2020. Comprehensive analyses of the influence of meteorological factors on surface O₃ indicated that O₃ pollution in Linfen, Yuncheng and Taiyuan was mainly caused by local photochemical reactions, while that in Jincheng, Xinzhou, Lvliang and Yangquan resulted from regional transports. O₃ volume mixing ratios (VMR) in the middle and lower troposphere generally increased with altitude, peaking at 120 ppbv at approximately 400 hPa. The positive vertical gradient of O₃ in the boundary layer was obvious in Taiyuan in summer and significant in the surface layer in Taiyuan and Linfen during winter and spring, which was associated with greater atmospheric dynamic stability and suppressed vertical mixing. Due to the lack of direct detection of O₃ in the lower troposphere in this region, O₃ vertical distribution retrieved by satellite observation is critical for the study of vertical mixing and transport of local O₃, as well as its regional transport characteristics.

A heavy rainstorm occurred in Beijing on 19–20 July 2016. The Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) was used to investigate the effects of anthropogenic aerosols on precipitation and microphysical processes. Three conditions were simulated by altering the anthropogenic emissions. When the anthropogenic emissions were increased by 10 times, the area-average accumulated rainfall amount and maximum accumulated rainfall amount both decreased. The cloud water mixing ratio increased and the rain mixing ratio decreased. The radii of cloud droplets decreased, and the collision efficiency of cloud water by rain and the autoconversion rate of cloud water into rain were both low. When the anthropogenic emission was 10% of the original emission, the area of accumulated rainfall amounts greater than 25 mm in the Beijing area was 10% larger than those of the other two tests. The collision efficiency and autoconversion rate of cloud water into rain were high for large contact areas and large cloud droplets. The graupel mixing ratio was the largest. Thus, the process of melting of graupel into rain was the largest. In the WRF-Chem model, the aerosols did not participate as ice nuclei (IN) in the ice-phase microphysical processes, and therefore the aerosols could influence only the warm rain processes and mix-phased processes near the freezing level line. For no influence on ice-phase microphysical processes, the snow and ice mixing ratios did not show many differences among the different tests.