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Understanding the characteristics of the raindrop size distribution (DSD) is crucial to improve our knowledge of the microphysical processes of precipitation and to improve the accuracy of radar quantitative precipitation estimation (QPE). In this study, the spatial variability of DSD in different regions of Beijing and its influence on radar QPE are analyzed using 11 disdrometers. The DSD data are categorized into three regions: Urban, suburban, and mountainous according to their locations. The DSD exhibits evidently different characteristics in the urban, suburban, and mountain regions of Beijing. The average raindrop diameter is smaller in the urban region compared to the suburban region. The average rain rate and raindrop number concentration are lower in the mountainous region compared to both urban and suburban regions. The difference in DSD between urban and suburban regions is due to the difference in DSD for the same precipitation types, while the difference in DSD between mountain and plains (i.e., urban and suburban regions) is the combined effect of the convection/stratiform ratio and the difference of DSD for the same precipitation types. Three DSD-based polarimetric radar QPE estimators were retrieved and estimated. Among these three QPE estimators, R(ZH), R(Kdp), and R(Kdp, ZDR), R(Kdp, ZDR) performs best, followed by R(Kdp), and R(ZH) performs worst. R(Kdp) is more sensitive to the representative parameters, while R(ZH) and R(Kdp, ZDR) are more sensitive to observational error and systematic bias (i.e., calibration). [ABSTRACT FROM AUTHOR]

We studied the characteristics of quasi-two-day wave (QTDW) using the meridional wind in the mesosphere and lower thermosphere (MLT) obtained from a meteor radar over Kototabang (KB, 0.2 ° S, 100.3 ° E) from 2003 to 2012. Atmospheric oscillations have a crucial impact on atmospheric dynamics, which contributes to more accurate space weather forecasting, thus providing a more secure space environment for human space exploration activities such as remote sensing and satellite navigation. QTDWs are typical atmospheric oscillations in the upper stratosphere, mesosphere and lower thermosphere. The occurrence time, amplitudes, periods and vertical wavelengths of QTDW events are analyzed statistically. Data obtained from the TIMED Doppler Interferometer (TIDI), which can measure wind and temperature and is onboard the Thermosphere, Ionosphere, Mesosphere Energetics and Dynamics (TIMED) satellite, are used to analyze the global distribution and spatial structure of QTDWs with different zonal wavenumbers. The characteristics of the QTDWs over KB are compared with the QTDWs at the middle latitudes using the meridional wind data from a meteor radar over Wuhan (114.4 ° E, 30.6 ° N), Beijing (116.5 ° E, 39.9 ° N) and Mohe (121.1 ° E, 50.1 ° N). The amplitudes of the QTDW and spectral analysis are calculated by the least squares fitting method. Our results demonstrate that QTDWs are present almost all year around over KB. The occurrence time, amplitudes, periods and vertical wavelengths of QTDW events with different zonal wavenumbers are determined in this study. We also find that the statistical characteristics of the QTDWs in KB are different from those at middle latitudes. The westward zonal wavenumber −4 (W4) events gradually increase with increasing latitude, whereas westward zonal wavenumbers −1, −2, and −3 (W1, W2 and W3, respectively) events all decrease with increasing latitude. [ABSTRACT FROM AUTHOR]

Severe hailstorms frequently occurred in Beijing between May and August 2021, leading to extensive hail damage. These hailstorms were observed by radar and satellite data, and reported by surface observers. In this study, the spectral and cloud microphysical characteristics of typical Beijing events in 2021 were analyzed using Himawari-8 satellite products and ground-based S-band weather radar data obtained from the Beijing Meteorological Bureau. The relationship between Himawari-8 brightness temperature differences (BTD) and radar reflectivity was also investigated. The results revealed that the significant spectral depression of brightness temperatures (BTs) in hail clouds was observed by a satellite. Furthermore, the stronger the radar reflectivity was, the more rapidly BTD decreased, with a nonlinear relationship between them. The results of cloud physical characteristics show that, for cloud-top heights above 10 km, the cloud effective radius was about 25 μm, with a cloud-top temperature of 225 K during these hail events. By means of Gaussian fitting, the BT threshold value (11.2 μm) was determined by satellite at 230 K, with a BTD focused on 1.9 K when hailstorms occurred. These results will help us better understand the characteristics of hailstorms, while also providing information for future hail suppression in Beijing. [ABSTRACT FROM AUTHOR]

Based on three years of data observed by Beijing MST radar between 2012 and 2014, this study gives the distribution characteristics of the turbulence energy dissipation rate ε and the vertical turbulence diffusion coefficient K z in the troposphere–lower stratosphere over Beijing based on the spectral width method. Additionally, from the perspective of atmospheric stability expressed by the Brunt–Väisälä frequency N and the gradient Richardson number Ri, the seasonal variations of turbulence parameters at different heights are analyzed. The results show that ε ( K z ) is distributed in the range of 10−4 to 10−1.5 m2 s−3 (100 to 101 m2 s−1), with median values of 10−3 to 10−2.5 m2 s−3 (100.4 to 100.75 m2 s−1). In the height range of −1 km to about +1 km from the tropopause, the profiles of ε have no noticeable seasonal difference from October to next May, and ε increases sharply with the slope of linear regression ∇log(ε)/∇h = 0.25 (m2 s−3) km−1. The seasonal variation of turbulence parameters has noticeable differences at different atmospheric layers. Furthermore, the atmospheric static/dynamic stability and turbulence intensity are the influencing factors of turbulence parameters. From the tropopause to 14 km, the values of ε and N both have a peak from October to next May, and this peak layer disappears from July to August. Within the range of 2–4 km from the ground, K z and the frequency of Ri < 0.25 have a significant positive correlation, with a Pearson correlation coefficient greater than 0.5, and both have large value layers in March to May and September to October. The turbulence intensity above 15 km is likely the main factor affecting the turbulence dissipation rate and vertical turbulence diffusion coefficient. [ABSTRACT FROM AUTHOR]