Meiyu-front rainstorm is one of the main disastrous weather events in summer in East China. In this study, seven assimilation experiments of multi-type observation data such as wind profile data, microwave radiometer data and radiosonde sounding data are designed to forecast the Meiyu-front rainstorm on 15 June 2020. The results show that the seven experiments can basically simulate the orientation of rain belt. The comprehensive experiment which assimilates all types of observations performs the best in simulating the location of heavy rainstorm and shows good performance in simulating the precipitation above moderate rain. For the comprehensive experiment, the forecast deviation of rainstorm and heavy rainstorm is small, and the equitable threat score has also been greatly improved compared with other experiments. It is found that the convective available potential energy is enhanced after the assimilation of surface observation data. In addition, the wind convergence and water vapor transportation are modified after assimilating wind profile data. Accordingly, the precipitation efficiency is improved in the comprehensive experiment. The profiles of pseudo-equivalent potential temperature, vorticity and divergence show that, the assimilation of new-types observation data from wind profiler radar and microwave radiometer increases the instability of atmospheric stratification and enhances the ascending motion in the heavy precipitation center. The above results show that the introduction of various some new-type data before the numerical simulation can reduce the forecast deviation. In addition, the combined assimilation of microwave radiometer and sounding data presents better performance than single data assimilation, which indicates that data mutual complementation is essential to improving forecast accuracy.

Enhancing radar data assimilation at cloud-resolving scales is essential for advancing typhoon analysis and forecasting. This study focuses on Typhoon Linfa, the 10th Pacific Typhoon of 2015, and proposes T-TREC-IS (Typhoon Circulation Tracking Radar Echo by Correlations with Iterative Smoothing), an enhanced version of the T-TREC algorithm. The enhancement incorporates an iterative smoothing constraint into the T-TREC algorithm, which improves the continuity of the retrieved wind field and mitigates the effects of velocity aliasing in radar data, thereby increasing the operational feasibility of the method. Building on this improvement, we evaluate the effectiveness of assimilating the T-TREC-IS-retrieved wind field for analyzing and forecasting Typhoon Linfa. The results demonstrate that the iterative smoothing constraint effectively filters out velocity de-aliasing errors during radar data quality control, enhances wind field intensity near the typhoon core, and retrieves the typhoon circulation more accurately. The refined wind field exhibits improved consistency and continuity, resulting in superior performance in subsequent assimilation analyses and forecasts.

Using multi-source observation data including automatic stations, radar, satellite, new detection equipment, and the Fifth Generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA-5) data, along with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) platform, an analysis was conducted on a rainstorm process that occurred in Nanjing on 15 June 2020, with the aim of providing reference for future urban flood control planning and heavy rainfall forecasting and early warning. The results showed that this rainstorm process was generated under the background of an eastward-moving northeast cold vortex and a southward retreat of the Western Pacific Subtropical High. Intense precipitation occurred near the region of large top brightness temperature (TBB) gradient values or the center of low TBB values on the northern side of the convective cloud cluster. During the heavy precipitation period, the differential propagation phase shift rate (K_DP), differential reflectivity factor (Z_DR), and zero-lag correlation coefficient (ρ_HV) detected by the S-band dual-polarization radar all increased significantly. The vertical structure of the wind field detected by the wind profile radar provided a good indication of changes in precipitation intensity, showing a strong correspondence between the timing of maximum precipitation and the intrusion of upper-level cold air. The abrupt increase in the integrated liquid water content observed by the microwave radiometer can serve as an important indicator of the onset of stronger precipitation. During the Meiyu season in Nanjing, convective precipitation was mainly composed of small to medium raindrops with diameters less than 3 mm, with falling velocities of raindrops mainly clustering between 2 and 6 m·s⁻¹. The rainstorm process featured four water vapor transport channels: the mid-latitude westerly channel, the Indian Ocean channel, the South China Sea channel, and the Pacific Ocean channel. During heavy rainfall, the Pacific Ocean water vapor channel was the main channel at the middle and lower levels, while the South China Sea water vapor channel was the main channel at the upper level, both accounting for a trajectory proportion of 34.2%.