On the afternoon of 14 February 2020, an extremely rare large hail event occurred in Enshi, Yichang, located insouthwestern Hubei Province, producing hailstones larger than 5 cm in diameter along with numerous smaller hailstones. Based on observations from automatic weather stations, radar and satellite, and the ECMWF ERA5 reanalysis data, this study analyzes environmental characteristics, triggering mechanisms, the storm structure, and causes of large hails in this hailstorm event. Results show that before convective initiation, the 0—6 km vertical wind shear reached 19 m/s, yet the convective available potential energy (CAPE) was only 438 J/kg, indicating a rare large hail event in a high-shear low-CAPE (HSLC) environment. At 850 hPa, the peripheral shear line of the southwestern vortex led to strong convergence between the warm-moist low-level southeasterlies and cold-dry northeasterlies in the mountainous area of northern Enshi. Combined with orographic lifting, this circulation pattern resulted in the development of two convective cells into supercells (hereafter referred to as cell A and cell B). Cell A is an isolated classical supercell, while cell B is an embedded supercell within a multicell storm, and both produced large hailstones. Estimates of updrafts in the two supercells based on divergence and perturbation pressure methods show that after the mesocyclones intensified, the dynamic perturbation pressure gradient force in the mid-lower levels of the storms contributed more significantly to the updrafts than in the mid-upper levels. The maximum updraft occurred near 6—7 km above the ground level. In the high-shear environment, the accelerations of both linear and nonlinear dynamic vertical perturbation pressure gradients were equally important for storm development. In the early stage of the storm, the mesocyclone was weak, the contribution of the nonlinear term was small, and the low-level updraft was dominated by the linear component. As the mesocyclone intensified, the nonlinear term became the dominant factor in the updraft. The mesocyclone prolonged the residence time of hail embryos in the region rich in supercooled water, allowing them to grow into large hailstones. More importantly, the perturbation pressure generated by the mesocyclone compensated for the insufficient buoyant vertical acceleration in the low-CAPE environment, enhancing the updraft. This, in turn, enabled the updraft to support larger hailstones and further extended their residence time.

Up to now there is no study on thunderstorm climatology based on long-term hourly observations over mainland China. Using hourly thunderstorm observations collected at 796 national-level stations during 1971—2010, the temporal and spatial evolution and duration characteristics of hourly thunderstorms over China are revealed, and some new findings are obtained. Over China, the spatial distribution pattern of annual average thunderstorm hours is close to that of annual average thunderstorm days. However, the situation is different in the Qinghai-Tibet Plateau, where the number of annual average thunderstorm days is high but the number of annual average thunderstorm hours is low, indicating that the duration of convective activity is shorter than that in the plain area. It is also found that the annual relative variability in areas of high annual average thunderstorm days and hours is significantly lower than that in areas of low annual average thunderstorm days and hours. Among the four seasons, the number of annual average thunderstorm hours in winter is the smallest, and many thunderstorms occur in the first half of the night. They account for the largest proportion of thunderstorms in the whole day. Nocturnal thunderstorms occur most frequently in summer, but their proportion of the thunderstorms in the whole day is the lowest. Nocturnal thunderstorms in Sichuan Basin are significant all year round. The diurnal peak of thunderstorm hours at each station mostly occurs in the afternoon and the trough largely occurs in the morning, and there are more thunderstorm hours in the first half of the night than in the second half. Affected by the East Asian summer monsoon, over most parts of China to the south and east of the Hu Huanyong line, the number of thunderstorm hours per thunderstorm day is not less than 3 h, whereas the number is significantly less than 3 h to the north and west of the Hu Huanyong line. For thunderstorms of different durations, thunderstorms that can last for 2 h occur most frequently over China and over different regions. The decadal variations of thunderstorm hours over China and over different regions all show a decreasing trend, but nocturnal thunderstorm hours have increased significantly since 2000. The significant decrease in thunderstorm hours in China is mainly due to the significant decrease of thunderstorm hours in the afternoon, and the increase in thunderstorm hours since 2000 is attributed to the increase in thunderstorm hours at night.

The similarities and differences in environmental conditions between daytime and nighttime torrential precipitation processes in North China have not been fully clarified. Based on precipitation data collected at 981 surface meteorological stations and ERA5 reanalysis data, the spatial and temporal distribution characteristics and environmental conditions of daytime and nighttime types of torrential precipitation processes in North China during the period from May to September of 2013—2023 are comprehensively analyzed. The objective classification method of the obliquely rotated T-mode principal component analysis is used to classify the circulation situations of daytime and nighttime types of torrential precipitation processes, and the characteristics of environmental physical variables of their corresponding circulation situations are then compared and analyzed. Direct comparison reveals that the environmental conditions of the nighttime heavy precipitation process in North China are different from that of the daytime heavy precipitation process, which provides an important basis for deepening our understanding of the formation mechanism of nighttime heavy rainfall in North China. The results show that the nighttime type torrential precipitation processes in North China develop more often after midnight, and have more occurrences over more concentrated regions, while the daytime processes and the first half-night precipitation of the nighttime processes have stronger convection and they mainly occur in July and August. Moisture of nighttime type is richer than that of daytime type, while CAPE of daytime type is higher than that of nighttime type. The distributions of both 850 hPa and 500 hPa temperature difference and 850 hPa vertical velocity are similar between the two types. Low-level wind speed and 0—1 km vertical wind shear are significantly higher in the nighttime type than in the daytime type. Low troughs and vortices at the edge of the subtropical high are the main synoptic systems influencing torrential precipitation processes in North China. The distribution characteristics of physical variable of the environments in different types of circulation situations are somewhat different. Moisture of deep trough circulation of daytime type and cold vortex circulation of nighttime type are the worst. 0—6 km vertical wind shear (SHR₆) and 0—3 km vertical wind shear (SHR₃) are generally not strong. SHR₆ of daytime torrential precipitation processes is slightly stronger than that of nighttime type, and SHR₃ of nighttime torrential precipitation processes is slightly stronger than that of daytime type. The above results indicate that the nighttime heavy rainfall over North China is closely related to the East Asian summer monsoon, which is characterized by abundant water vapor, high θ_se value, appropriate CAPE value and strong wind speed in the lower atmosphere. The low-level wind field and SHR₃ distribution indicate that one of the dominant factors of nighttime heavy rainfall over North China is the diurnal variations of low level jet or strong wind speed.

Tornado disasters are intense and have been attracting significant social attention. This article reviews recent research progress on tornado mechanisms, intensity scales, and damage survey methodologies. It examines key aspects such asprocesses of tornadic vortex formation and dissipation, challenges in field surveys and intensity estimation, and so on,and provides outlool for future research. While the favorable environmental conditions for mesocyclone tornadoes are well documented, several critical questions remain unresolved: The role of low-level atmospheric humidity under cold vortex conditions, the influence of convective available potential energy in tropical cyclone tornadoes, and the environmental prerequisites for tornado outbreak events. The formation of mesocyclone tornadoes involves multiple stages: Development of mesocyclones, generation and organization of near-surface vortex patches, subsequent intensification, and the critical influence of surface friction leading to the development of tornado vortex boundary layers and corner flow regions. Topography exerts complex effects on tornado behavior, typically causing weakening during uphill movement and intensification during descent. Tornado dissipation mechanisms vary, with any disruption to sustaining factors potentially leading to vortex demise. Common tornado intensity scales include the Fujita (F), Enhanced Fujita (EF), and TORRO (T) scales. The T-scale features the most detailed categorization (11 levels), while the EF-scale remains the most widely adopted standard internationally. China’s national tornado intensity classification system aligns directly with the EF-scale. Significant advancements have been made in severe wind damage survey methods and procedures, with extensive tornado case data now available in China. However, the complex disaster mechanisms of tornadoes introduce substantial uncertainty in intensity assessment. Continued improvements are needed in high-resolution observations, damage survey techniques, physical mechanism studies, and forecasting/warning capabilities to enhance tornado preparedness and mitigation efforts.

This article reviews advances in monitoring and nowcasting of severe convective weather (SCW), along with developments in operational nowcasting systems. It focuses on deep learning (DL)-based techniques using multisource data, highlighting associated challenges and opportunities. Based on multisource observations including those from dual-polarization weather radars and geostationary satellites, the monitoring capabilities of SCW types and intensities, convective initiation, and identification and tracking of convective storm cells have been significantly improved using advanced technologies, including storm structural feature recognition, fuzzy logic, and DL. Among these approaches, deep generative models have proven particularly effective, substantially improving the accuracy and extending the lead time of SCW nowcasting. The performance of the China Meteorological Administration's Severe Weather Analysis and Forecasting (SWAN) 3.0 system continues to advance, with widespread operational adoption across China. Future efforts will leverage higher-resolution observations and numerical weather prediction products at the hundred-meter resolution to enhance the understanding of the underlying mechanisms of SCW development at meso-γ- and microscales. Current purely data-driven AI models are transitioning toward physics-informed frameworks for SCW nowcasting. Integrating forecasters' operational expertise with state-of-the-art AI technology will further enhance operational capabilities in monitoring and nowcasting extreme SCW events.

Tornado disasters are intense and have been attracting significant social attention. This article reviews recent research progress on tornado mechanisms, intensity scales, and damage survey methodologies. It examines key aspects such as processes of tornadic vortex formation and dissipation, challenges in field survey and intensity estimation, and so on, and provides outlook for future research. While the favorable environmental conditions for mesocyclone tornadoes are well documented, several critical questions remain unresolved: the role of low-level atmospheric humidity under cold vortex conditions, the influence of convective available potential energy in tropical cyclone tornadoes, and the environmental prerequisites for tornado outbreak events. The formation of mesocyclone tornadoes involves multiple stages: development of mesocyclones, generation and organization of near-surface vortex patches, subsequent intensification, and the critical influence of surface friction leading to the development of tornado vortex boundary layers and corner flow regions. Topography exerts complex effects on tornado behavior, typically causing weakening during uphill movement and intensification during descent. Tornado dissipation mechanisms vary, with any disruption to sustaining factors potentially leading to vortex demise. Common tornado intensity scales include the Fujita (F), Enhanced Fujita (EF), and TORRO (T) scales. The T-scale features the most detailed categorization (11 levels), while the EF-scale remains the most widely adopted standard internationally. China’s national tornado intensity classification system aligns directly with the EF-scale. Significant advancements have been made in severe wind damage survey methods and procedures, with extensive tornado case data now available in China. However, the complex disaster mechanisms of tornadoes introduce substantial uncertainty in intensity assessment. Continued improvements are needed in high-resolution observations, damage survey techniques, physical mechanism studies, and forecasting/warning capabilities to enhance tornado preparedness and mitigation efforts.

This article reviews advances in monitoring and nowcasting of severe convective weather (SCW), along with developments in operational nowcasting systems. It focuses on deep learning (DL)-based techniques using multisource data, highlighting associated challenges and opportunities. Based on multisource observations including those from dual-polarization weather radars and geostationary satellites, the monitoring capabilities of SCW types and intensities, convective initiation, and identification and tracking of convective storm cells have been significantly improved using advanced technologies, including storm structural feature recognition, fuzzy logic, and DL. Among these approaches, deep generative models have proven particularly effective, substantially improving the accuracy and extending the lead time of SCW nowcasting. The performance of the China Meteorological Administration’s Severe Weather Analysis and Forecasting (SWAN) 3.0 system continues to advance, with widespread operational adoption across China. Future efforts will leverage higher-resolution observations and numerical weather prediction products at the hundred-meter resolution to enhance the understanding of the underlying mechanisms of SCW development at meso-γ- and microscales. Current purely data-driven AI models are transitioning toward physics-informed frameworks for SCW nowcasting. Integrating forecasters’ operational expertise with state-of-the-art AI technology will further enhance operational capabilities in monitoring and nowcasting extreme SCW events.

Boundary layer convergence lines (BLCLs), an important type of weather system that can trigger deep moist convection, correspond to quasi-linearly extending airflow confluence zones in the boundary layer. Multiple types of BLCLs exist, and mechanisms for their triggering of convection are complicated. This paper summarizes the existing studies on the climatological statistics of BLCLs (excluding cold fronts) and mechanisms for their triggering of convection, and the effects of local temperature and moisture disturbances on the convection triggering. These studies have presented that the triggering probability, the storm location and time correlation are all affected by different synoptic systems and BLCL types in different regions. Under certain favorable conditions, local temperature and moisture can not only affect BLCL intensity, but also affect the distribution of atmospheric stratification near BLCLs, and thus convection initiation can occur. Moreover, the dynamical and thermal interactions between local temperature and moisture disturbances and the environment make the convection triggering mechanisms more complicated. The paper also discusses some convection triggering issues that need to be further studied. Based on fine observations and numerical simulation, it is also suggested to carry out more systematic studies on the characteristics and mechanisms of convection triggering for different regions and different types of BLCLs in the future.

Northeast China cold vortex is one of the important synoptic-scale systems that causes severe convective weather in the warm season in China. In order to compare and analyze the spatiotemporal relationship between Northeast China cold vortex system and different types of severe convective weather processes and their environmental characteristics, based on the Fifth Generation Atmospheric Reanalysis Product of European Centre for Medium-Range Weather Forecasts and hourly precipitation and wind data provided by the National Meteorological Information Centre of China, severe convective weather processes including nine thunderstorm wind gust, nine heavy precipitation and eight hybrid type processes associated with Northeast China cold vortex from April to September of 2017—2021 are screened out. Comparative analysis is carried out by dynamic synthesis approach. The results are as follows: (1) Differences in the spatiotemporal distribution of the three types of severe weather processes and Northeast China cold vortex system are significant. In the thunderstorm wind gust processes, more than 70% of thunderstorm wind gusts occur in the southwest or south of the cold vortex center. However, in the hybrid type processes, more than 70% of thunderstorm wind gusts occur in the southeast or south of the cold vortex center. More than 75% of the heavy precipitation events occur in the south to southeast of the cold vortex center in both the hybrid type processes and heavy precipitation processes, but a higher proportion of the latter occur in the southeast of the cold vortex. Processes of thunderstorm wind gust and heavy precipitation mainly occur in the development and maturity stages of the Northeast China cold vortex, while hybrid processes mainly occur in the maturity stage. (2) The characteristics of circulation patterns and environmental conditions of the three types of severe weather processes are significantly different. Thunderstorm wind gust processes are concentrated from May to June, generally corresponding to a stronger cold vortex, denser 500 hPa isotherms, a drier atmosphere, a larger vertical temperature lapse rate and stronger vertical wind shear. Thunderstorm wind gusts mostly occur near the front area. The cold and dry advection in the middle troposphere superimposing on the shallow warm and wet air in the lower layer is conducive to the growth of unstable stratification in the frontal zone. Meanwhile, the downdraft formed by evaporation and cooling of precipitation particles couples with the convergence in the frontal zone, leading to the formation of regional surface wind gusts. Heavy precipitation processes are concentrated from July to August, corresponding to a weaker cold vortex and sparsely distributed isotherms. Heavy precipitation generally occurs in the region of strong unstable stratification near the warm sector ahead of the front, which corresponds to an environment with more water vapor content, smaller temperature differences between middle and low layers and weaker vertical wind shear. The time period and cold vortex intensity corresponding to the hybrid type processes are closer to that of the heavy precipitation processes, and the conditions of water vapor, vertical temperature lapse rate and vertical wind shear are between those for the above two types of processes, but DCAPE is the largest in the three types of processes. However, compared with the environmental characteristics of thunderstorm wind gusts and short-term heavy precipitation in the middle and low altitudes of China, the three types of severe weather processes under the background of the Northeast China cold vortex correspond to stronger deep vertical wind shear condition, indicating that the cold vortex system provides strong synoptic scale dynamic forcing.

To improve the analysis and forecast ability of thunderstorm gusts (TGs) in Northeast China, climatic characteristics of TGs in Northeast China and their relation with Northeast China Cold Vortex (NCCV) are studied. TGs are identified based on comprehensive analysis of data collected at automatic weather stations and from lighting locators and Himiwari-8 satellite. In addition, the ERA5 reanalysis dataset is used to calculate the centers and radius of NCCV. The results show that TGs in Northeast China mainly occur in the regions from the Mongolian plateau to the west of the Greater Khingan mountains, Northeast China plain and the coastal area of Liaoning. About 50.6% of TGs are caused by NCCV and Liaohe plain is the area with the highest occurrence frequency of TGs caused by NCCV. The diurnal variation of TGs occurrence shows a high frequency in the afternoon, and the TGs caused by NCCV are more frequent in the late night and morning, accounting for 75%. The number of stations with TGs in one hour is generally less than 10, while the cases of regional TGs occurring at more than 10 stations are mostly related to NCCV and account for 56.5%. Compared with TGs not caused by NCCV, TGs caused by NCCV occur in a drier and colder environment with strong temperature lapse rate between 850 hPa and 500 hPa, strong vertical wind shear and storm bearing layer. The percentages of TGs occurring in different quadrants of NCCV in the NCCV TGs are 73.5% in the southeast quadrant, 17.5% in the southwest quadrant, 7.5% in the northeast quadrant and 1.5% in the northwest quadrant in descending order. The frequency of TGs occurring in the periphery of NCCV is more than that in the NCCV itself, and they are concentrated within 0.5—2 times of NCCV radius from the southeast quadrant of NCCV to the center of NCCV. In this area, there is a dry layer in the middle atmosphere, a large vertical temperature lapse rate in the lower atmosphere, a medium or higher vertical wind shear and a larger wind speed in the storm carrying layer, and they are more vulnerable to the impact of low-level shear line. This is the reason why NCCV TGs are concentrated in this area. The centers of NCCV that can cause TGs are concentrated over 45°—55°N and 111°—128°E, and the centers of NCCV that can cause regional TGs are concentrated at 116°E and 122°E with a meridional distribution. The geopotential height at the central and outermost areas of NCCV that can cause regional TGs is lower than that of NCCV responsible for local TGs, and the difference is more obvious in spring and autumn. Furthermore, the radius of NCCV that can cause local TGs in August slightly higher than that of NCCV that can cause regional TGs in spring and autumn, and vice versa. The results of this study have proved that NCCV is the most important system that causes TGs in Northeast China. The spatial distribution of TGs in different quadrants of NCCV and characteristics of NCCV that can generate regional TGs provide a reference for improving the forecast and early warning ability of TGs caused by NCCV.