The evolution of microphysical characteristics of a rainband in Typhoon Matmo (2014) over eastern China, through its onset, developing, mature, and dissipating stages, is documented using observations from an S band polarimetric Doppler radar and a two‐dimensional video disdrometer (2DVD). The drop size distributions observed by the 2DVD and retrieved from the polarimetric radar measurements indicate that the convection in the rainband generally contains smaller drops and higher number concentrations than the typical maritime type convection described in Bringi et al. (2003). The average mass‐weighted mean diameter (Dm) of convective precipitation in the rainband is about 1.41 mm, and the average logarithmic normalized intercept (Nw) is 4.67 log10 mm−1 m−3. To further investigate the dominant microphysical processes, the evolution of the vertical structures of polarimetric variables is examined. Results show that complex ice processes are involved above the freezing level, while it is most likely that the accretion and/or coalescence processes dominate below the freezing level throughout the rainband life cycle. A combined examination of the polarimetric measurements and profiles of estimated vertical liquid and ice water contents indicates that the conversion of cloud water into rainwater through cloud water accretion by raindrops plays a dominant role in producing heavy rainfall. The high estimated precipitation efficiency of 50% also suggests that cloud water accretion is the dominant mechanism for producing heavy rainfall. This study represents the first time that radar and 2DVD observations are used together to characterize the microphysical characteristics and precipitation efficiency for typhoon rainbands in China.

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This paper studies the state of charge (SOC) estimation of supercapacitors and lithium batteries in the hybrid energy storage system of electric vehicles. According to the energy storage principle of the electric vehicle composite energy storage system, the circuit models of supercapacitors and lithium batteries were established, respectively, and the model parameters were identified online using the recursive least square (RLS) method and Kalman filtering (KF) algorithm. Then, the online estimation of SOC was completed based on the Kalman filtering algorithm and unscented Kalman filtering algorithm. Finally, the experimental platform for SOC estimation was built and Matlab was used for calculation and analysis. The experimental results showed that the SOC estimation results reached a high accuracy, and the variation range of estimation error was [−0.94%, 0.34%]. For lithium batteries, the recursive least square method is combined with the 2RC model to obtain the optimal result, and the estimation error is within the range of [−1.16%, 0.85%] in the case of comprehensive weighing accuracy and calculation amount. Moreover, the system has excellent robustness and high reliability.

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Severe convective precipitation is a major cause of many hazards such as floods and mudslides that lead to massive economic losses and casualties. Unfortunately, the characteristics such as rapid development, short life cycle and highly nonlinear dynamics of convective precipitation make it rather challenging to be precisely forecasted. Very short-term forecasting, that is, nowcasting, of convective precipitation using weather radar observations, has raised extensive research interest. Wilson et al. (1998) made a comprehensive review of convective storm characteristics and nowcasting methods, and pointed out that the insufficiency of data information and the ineffectiveness of nowcasting model are the two major challenges that convective precipitation nowcasting faces. Although improved over the past decades, these two deficiencies still remain to be settled (