Jiangsu Province is located in the middle coastal area of East China, and has a relatively developed economy and a large population density. Severe convection often occurs in Jiangsu Province, and the lightning activities may cause great economic losses and social impact in this region. Based on the theory of natural disaster risk assessment, this study investigates the risk of hazard factors, the sensitivity of hazard-pregnant environment, and the frangibility of a hazard-bearing body in Jiangsu Province. Then, we select thunderstorm days, cloud-to-ground (CG) lightning density, CG lightning current intensity, altitude, topographic relief, soil-electric conductivity, drainage density, population density, gross domestic product (GDP) per land area, and soil utilization type as the influencing factors, and then we use the analytic hierarchy process and entropy weight method to calculate the weights of the influencing factors. Furthermore, all the factors are weighted stacked in ArcGIS, and finally the lightning disaster risk zoning map (1 × 1 km of Jiangsu Province is presented. The results show that the risk of lightning disaster in Jiangsu is low in the north and high in the south. The area of different risk level increases with the decrease in risk level. High-risk areas are mainly in the middle of Nanjing, eastern Changzhou, eastern Wuxi, and the middle of Suzhou. Medium-risk areas are mainly in northern Nanjing, eastern Changzhou, eastern Suzhou, the Tongshan District of Xuzhou City, the Chongchuan District of Nantong City, Lianyun District of Lianyungang City, and the Xiangshui County, Sheyang County, and Dafeng District of Yancheng City. The sub–low-risk areas are mainly in Xuzhou, Suqian, Huai’an, and the middle of Yangzhou City. The low-risk areas are mainly in Lianyungang, Yancheng, northern Nantong, Taizhou, Zhenjiang, southern Nanjing, western Changzhou, western Wuxi, and western Suzhou. We hope this study could provide some references for the lightning disaster prevention and mitigation in Jiangsu Province and East China.

The remote sensing products of the fraction of photosynthetically active radiation (FPAR) are widely used in large‐scale terrestrial vegetation condition monitoring and ecological modeling. However, the validation and evaluation of these products are still insufficient due to limited ground measurements. A framework is proposed in this study that does not rely on ground FPAR observations to evaluate the potential uncertainties of three FPAR data sets over a large scale. Two independent methods, including a statistical method named extended triple colocation (ETC) and FPAR‐based gross primary production (GPP) comparative evaluation at the site level, are integrated. The framework was applied to three widely used FPAR products, including GLASS (Global Land Surface Satellite), GEOV2 (version 2 of the COPERNICUS 1‐km product), and MODIS (Moderate Resolution Imaging Spectroradiometer), in China from 2001–2015. The root‐mean‐square error (RMSE) and correlation coefficient (R) based on the ETC method showed that at the national spatial scale, GEOV2‐FPAR had the highest precision (RMSE_FPAR = 0.0367, R_FPAR = 0.9012), followed by MODIS‐FPAR (RMSE_FPAR = 0.0482, R_FPAR = 0.8392) and GLASS‐FPAR (RMSE_FPAR = 0.0536, R_FPAR = 0.736). In particular, each FPAR data set was locally optimal over some regions. Using a light use efficiency model, GPP was calculated using these three FPAR data sets and other identical variables and parameters at 22 eddy flux sites. General coherent results were found in both GPP evaluation and site‐level ETC analysis of these three FPAR data sets. Therefore, we conclude that this framework is reliable and applicable in evaluating the potential uncertainties of FPAR.

Mesoscale convective vortices (MCVs) often cause rainstorms. To deepen our understanding of MCV formation mechanisms, reanalysis data from the National Centers for Environmental Prediction and the Weather Research and Forecasting model were used to simulate MCV activity in East China in August 2009. The simulations could reproduce the MCV and associated convective activities well. The vorticity budget and MCV formation mechanisms were then analyzed. The results show that the planetary vorticity advection is much smaller than other terms of the vorticity equation. The MCV initiates in the convective precipitation region and below 800 hPa. When the MCV initiates, there are vorticity-variation couplets within the vortex, and the MCV moves towards the positive vorticity-variation direction. In positive vorticity-variation areas, the divergence term and the tilting term are the vorticity source. The equilibrium response to diabatic heating is one of the forming mechanisms of this MCV. The latent-heating level is relatively low in this MCV case, and the MCV-forming level is also relatively low. Another forming mechanism of this MCV is the tilting of the horizontal vortex tube caused by the upward motion. At the MCV initiation, the perturbation scale of the vortex is found to be larger than the Rossby deformation radius, and thus the MCV could have a long duration.

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.

In this study, three typical and most extreme precipitation events in the history of North China are analyzed and compared in terms of accumulated precipitation and synoptical circulation using surface station observations of China and the ERA5 dataset. The three events happened in August 1963 (“63.8” event, hereafter), August 1975 (“75.8” event), and July 2021 (“21.7” event), respectively, mainly in Hebei and Henan Provinces of North China. The results show that the maximum daily and 4-day accumulated precipitation of all three events exceeded 500 mm and 800 mm, with many stations’ daily precipitation ranking Top 1. The “63.8” event persisted for the longest time, affected the largest area, and rained the most in 7 days (over 1000 mm). The “75.8” event was characterized by the most extreme daily precipitation and a concentrated area. All three events characterize a normal northward subtropical high that was located in North China and Northeast China. At 500 hPa, the area from South China to the South China Sea was dominated by a uniform pressure field. In the upper levels, there were troughs and divergence anomalies in all three events. In the low levels, there were anomalous low-level jets and the associated water vapor flux anomalies, which were located at different levels and came from different directions. Stable synoptical circulation and persistent jet and water vapor flux anomalies are the key factors in these extreme events.