Simultaneous observations of rainfall collected by a tipping bucket rain gauge (TBRG), a weighing rain gauge (WRG), an optical rain gauge (ORG), a present weather detector (PWD), a Joss–Waldvogel disdrometer (JWD), and a 2-D video disdrometer (2DVD) during January to October 2012 were analyzed to evaluate how accurately they measure rainfall and drop size distributions (DSDs). For the long-term observations, there were different discrepancies in rain amounts from six instruments on the order of 0% to 27.7%. The TBRG, WRG, and ORG have a good agreement, while the PWD and 2DVD record higher and the JWD lower rain rates when R > 20 mm h⁻¹, the ORG agrees well with JWD and 2DVD, while the TBRG records higher and the WRG lower rain rates when R > 20 mm h⁻¹. Compared with the TBRG and WRG, optical and impact instruments can measure the rain rate accurately in the light rain. The overall DSDs of JWD and 2DVD agree well with each other, except for the small raindrops (D < 1 mm). JWD can measure more moderate-size raindrops (0.3 mm < D < 1.5 mm) than 2DVD, but 2DVD can measure more small-size raindrops (D < 0.3 mm). 2DVD has a larger measurement range; more overall raindrops can be measured by 2DVD than by JWD in different rain rate regimes. But small raindrops might be underestimated by 2DVD when R > 15 mm h⁻¹. The small raindrops tend to be omitted in the more large-size raindrops due to the shadow effect of light. Therefore, the measurement accuracy of small raindrops in the heavy rainfall from 2DVD should be handled carefully.

Recently, the oblique earth-space links (OELs) between satellite and earth station have been used for rainfall monitoring as a supplement to existing observation methods. Most recent studies achieved the rainfall measurement by OELs based on the empirical method such as power-law (PL) model. In practice, two crucial issues need to be addressed: 1) identification of rain and no-rain periods; and 2) determination of attenuation baseline. To solve these problems, this article adopts several machine learning algorithms based on the analysis of earth-space link signal characteristics. For the first issue, we choose the support vector machine as a classifier and the adaptive synthetic sampling algorithm is deployed to eliminate the effects caused by the data imbalance. For the second issue, the long short-term neural network is selected for the determination of attenuation baseline since it has a good ability to solve time-series problem. In terms of the rainfall inversion, we establish a new model by combining the back-propagation (BP) network and genetic algorithm (GA). The PL model is also used as a comparison. To validate the proposed method, we set up an earth-space link that receives the signal from AsiaSat5 in 12.32 GHz. The results demonstrate that the two issues are successfully addressed and the inversion of precipitation is also carried out. Compared to disdrometer, the correlation and mean absolute error of GA-BP model are 0.83 and 1.30 mm/h, respectively, indicating a great potential to use densely OELs for global precipitation monitoring.

To compensate radar reflectivity for attenuation effect, a new method for attenuation correction of the radar reflectivity using arbitrary oriented microwave link (referred henceforth to as ACML) is developed and evaluated. Referring to the measurement of arbitrary oriented microwave link, the ACML method optimizes the ratio of specific attenuation to specific differential phase which is a key parameter in attenuation correction schemes. The proposed method was evaluated using real data of a dual-polarization X-band radar and measurements of two microwave links during two rainstorm events. The results showed that the variation range of the optimized ratio was overall consistent with the results of the previous studies. After attenuation correction with the optimal ratios, the radar reflectivity was significantly compensated, especially at long distances. The corrected reflectivity was more intense than the reflectivity corrected by the “self-consistent” (SC) method and closer to the reflectivity of a nearby S-band radar. The effectiveness of the method was also verified by comparing the rain rates estimated by the X-band radar with those derived by rain gauges. It is demonstrated that arbitrary oriented microwave link can be adopted to optimize the attenuation correction of radar reflectivity.

As rainfall exhibits high spatiotemporal variability, accurate and real-time rainfall monitoring is vitally important in fields such as hydrometeorological research, agriculture and disaster prevention and control. Nevertheless, the current dedicated rain sensors cannot fulfill the requirement for comprehensive precipitation observation, owing to their respective limitations. Within the last two decades, the utilization of commercial microwave links (CMLs) for rainfall estimation, as an opportunistic sensing method, has generated considerable attention. Relying on CML networks deployed and maintained by mobile network operators can provide near-surface precipitation information over large areas at a low cost. Although scholars have developed several algorithms for obtaining rainfall estimates from CML data, the rainfall estimation technique based on CMLs remains challenging due to the complex effect in the microwave radiation transmission process. In this paper, we provide a comprehensive review of the technical principles, developments and workflows for this technology, alongside its application in environmental monitoring and hydrological modeling. Furthermore, this paper outlines the current challenges and future research directions, which will hopefully draw the attention of researchers and provide valuable guidance.

Through the collision and freezing of supercooled droplets on the surface of snow particles, riming can change the density, fall velocity and aspect ratio of snow particles. Riming plays an important role in the formation of precipitation in cold clouds. To our knowledge, the impact of riming on snow microphysics is yet well understood, and there is a lack of observations obtained in China addressing this issue. For the first time in East China, the connection between riming and snow microphysical properties was investigated quantitatively during snow events in two winters. To quantify the degree of riming, the rime mass fraction (FR) is derived using the combination of a 2‐D video disdrometer (2DVD) and a weighing gauge. FR is added to the density‐diameter and fall velocity‐diameter relations, and a quantitative relation between riming and shapes of snowflakes is established based on the in situ observation of the 2DVD. The results show that riming can well explain the variability in the density and fall velocity of snowflakes. The changes in the shape of snowflakes can be divided into two distinct stages with increasing riming: in the initial stage (FR < 0.5), the aspect ratio increases very slowly, while in the later stage (FR > 0.5), the aspect ratio increases rapidly. Direct observations of the continuous changes in the shapes of snowflakes with riming are in good agreement with the retrieval results of radar.