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The annual average rainfall of summer monsoon rainstorms in Yangjiang is highest in the southeast, decreasing towards the wings. Rainfall most frequently occurs in the early morning and around noon in June, with the western region experiencing the peak slightly earlier than other areas. Short-duration intense rainfall in the south occurs most frequently between 02:00 and 08:00, while in the north, it is more common between 08:00 and 14:00; the 6-hour accumulated rainfall ≥50mm most frequently occurs between 02:00 and 08:00. The weather situation conducive to monsoon rainstorms involves the stability of the South Asian high pressure at 200hPa over the Indochinese Peninsula, with Yangjiang at 500hPa ahead of the southern trough. During the early morning, the southwest monsoon strengthens from 925hPa over the northern Bay of Bengal to the northern South China Sea, pushing northward to Yangjiang’s land, creating the atmospheric conditions for monsoon rainstorms. Moisture primarily enters from the Indochinese Peninsula through the South China Sea, gradually increasing at night and reaching its peak from late night to early morning. The moisture channel and convergence height are below 700hPa. Atmospheric upward motion extends from the mid-to-upper levels to near the surface in the early morning, with the strong center moving from south to north.

This study examined the rainfall characteristics and related synoptic processes of two extreme rainfall events that affected North China during 29 July–1 August 2023 (“23·7” rainstorm) and 3–5 August 1996 (“96·8” rainstorm), respectively. A stable dual-typhoon circulation pattern was observed in both rainstorm events. The surviving vortex of a landed typhoon, slowly approaching the rainstorm region, was blocked by a high-pressure system as it moved northwestward. Meanwhile, the second typhoon over the western Pacific Ocean facilitated remote northward transport of moisture. The low-level jet between the surviving vortex and the western Pacific subtropical high relayed moist warm air from the area of the South China Sea and western Pacific into the rainstorm region. Although the circulation patterns are similar, the stratification conditions, driving factors, and moisture budget of the two rainstorms differed during the main period of rainfall. The “23·7” rainstorm was categorized as warm-sector rainfall, as a result of the lifting of warm moist air over the eastern foothills of Taihang Mountains. In comparison with the situation of the “96·8” rainstorm, the surviving vortex of the “23·7” rainstorm traveled further northeastward and directly impacted the occurrence and progression of the rainfall, leading to relative northward displacement of the rainfall center, while the stronger net inward moisture flux caused greater regional average rainfall. The “96·8” rainstorm was broadly analogous to precipitation of a cold front, and the rainfall center was observed in the convergence area of warm and cold air masses before the mountains; the surviving vortex did not exert direct impact on the rainfall; and the more unstable stratification led to stronger hourly rainfall. The results derived through comparison of the two rainstorms could serve as valuable scientific reference for operational forecasting of heavy rainfall under similar environmental conditions over North China.

Effective management of rainstorm risk is essential for reducing regional rainstorm disaster risks and losses. In this paper, we discussed the influencing factors of urban rainstorm disaster (URSD) risk from four aspects and then constructed the index system of URSD risk assessment which includes 16 influencing factors. Furtherly, important indexes were extracted as the input of deep belief nets (DBN) model after analyzing the types and risk characteristics of URSD. As well as a coupling risk assessment model of URSD based on random forest and deep belief nets (RF–DBN) was established due to the capacity of high-dimensional data processing of RF and robustness of DBN. To test the validity of this risk assessment model, it was applied to evaluate the rainstorm disaster risk in 11 districts of Nanjing, China, from May to September during 2009 and 2017. Finally, the risk grade map of rainstorm disaster in Nanjing was drawn and the corresponding countermeasures for the regulation and control of URSD were put forward. The results show that the rainstorm risk in Nanjing is generally high during the period of rainy season and the risk of rainstorm disaster has egional features during the flood season.

Taking CMPA (CMA Multi-source Merged Precipitation Analysis System) analysis data as a reference, the research analyzes the forecast performance of ECMWF, CMA-Meso, and SCMOC (National Meteorological Center grid precipitation forecast guidance product) in 74 rainstorm cases in 2020 and 2021 in Qinling Mountains and their surrounding areas by using the dichotomy classical verification score comprehensive diagram and the object-oriented MODE spatial verification method, based on the circulation classification in rainstorm weather. The research conclusions are as follows: (1) based on the high- and low-altitude circulation situation and focused on the direct impact system, rainstorms in the Qinling Mountains and their surrounding areas can be divided into five patterns. (2) Point-to-point verification shows that SCMOC has obvious advantages in rainstorm forecast, but the disadvantage is that the Bias is relatively high. CMA-Meso has advantages in RST (weak weather system) decentralized rainstorm forecast. (3) MODE verification shows that the number of ECMWF and SCMOC independent objects is significantly lower than that of observation, the forecast area of regional rainstorm objects of SCMOC is significantly larger, the SCMOC scattered rainstorm objects are missed, and the number of independent precipitation objects of CMA-Meso is higher than that of the other two precipitation products. (4) The forecast object area and intensity of SCMOC and observation match best in the XFC (westerly trough) circulation situation, while ECMWF has the best results for the forecast of FGXFC (subtropical high westerly trough) rainstorms.

Rainstorm disaster brings serious threat to people's life and property safety. Constructing reasonable rainstorm disaster risk index and drawing rainstorm disaster risk map can help decision-makers to deal with rainstorm disaster effectively and reduce disaster loss. It has important practical significance. This paper, for the first time, proposes a comprehensive risk index for death caused by rainstorm disasters. According to this index, the regional hazard map of Beijing is drawn, so as to directly reflect the damage degree of rainstorm disaster in Beijing. In the process of index construction, the weight is determined by regression coefficient innovatively, and the disadvantage of subjective setting weight is avoided, and the spatial distribution of risk can be more accurately reflected by constructing disaster risk index by using fused grid data. Research shows that the rainstorm death risk index proposed in this paper can well reflect the risk of death caused by rainstorms in various areas of Beijing. Combined with the ArcGIS software, a risk map of death due to rainstorm disasters is drawn. It is found that Fangshan District of Beijing is a major disaster area with the highest risk of death. Finally, the managerial implication included that government administrators should evaluate the risk of rainstorm disasters in a certain area according to the established rainstorm death risk indexes and draw a risk map accordingly.

Extremely heavy rainfall has posed a significant hazard to urban growth as the most common and disaster-prone natural calamity. Due to its unique geographical location, the metro system is more vulnerable to waterlogging caused by rainstorm disaster. Research on resilience to natural disasters has attracted extensive attention in recent years. However, few studies have focused on the resilience of the metro system against rainstorms. Therefore, this paper aims to develop an assessment model for evaluating metro stations’ resilience levels. Twenty factors are carried out from dimensions of resistance, recovery and adaptation. The methods of ordered binary comparison, entropy weight and cloud model are proposed to build the assessment model. Then, taking Chongqing metro system in china as a case study, the resilience level of 13 metro stations is calculated. Radar charts from dimensions of resistance, recovery, and adaptation are created to propose recommendations for improving metro stations’ resilience against rainstorms, providing a reference for the sustainable development of the metro system. The case study of the Chongqing metro system in china demonstrates that the assessment model can effectively evaluate the resilience level of metro stations and can be used in other infrastructures under natural disasters for resilience assessment.

The warming climate-induced intensification of hydrological cycle is amplifying extreme precipitation and increasing flood risk at regional and global scales. The evaluation of flood risk, which depends on assessment indicators, weights, as well as data quality, is the first step toward mitigation flood disasters. In this study, we accepted ten risk assessment indicators concerning hazard of disaster-causing factors, sensitivity of hazard-forming environments, and vulnerability of disaster-bearing bodies. We used a combined weighting method based on the analytic hierarchy process and entropy weight (AHP-EW) technique to evaluate rainstorm-induced flood risks across the Yellow River Basin (YRB) from 2000 to 2018. We observed flood hazards are intensifying across the YRB. Specifically, areas with medium flood hazards expanded from the lower to the middle and upper YRB. The sensitivity to floods exhibited a spatial pattern of increasing from southeast to northwest (lower to upper YRB). The increase in vegetation coverage in the middle and upper reaches of the YRB reduces the sensitivity to flood disasters. Flood vulnerability shows an increasing trend, with higher vulnerability mainly observed in the middle and lower YRB. The overall flood risk in the YRB shows an increasing trend, with a 9-fold increase in flood risk from 2000 to 2018. Medium to high flood risk and vulnerability can mainly be identified in the middle and lower YRB, where population and gross domestic product are concentrated. The intensifying rainstorm-induced flood risks over urban areas in these regions should arouse public concern.

This study developed an objective identification algorithm for the Southwest Vortex (SWV), the dominant rainstorm system prevalent in Southwest China. Based on the TempestExt package, the newly developed SWV identification algorithm employed a 12 h minimum duration threshold, utilizing the high-resolution ERA5 dataset with 1 h intervals. The results reveal that the algorithm precisely identifies the SWV records documented in the SWV Yearbooks, achieving an optimal balance of high probability of detection and low false alarm rate. In addition, the algorithm can detect the SWVs in advance, offering a significant enhancement to SWV monitoring. Notably, the algorithm-detected SWVs exhibit a strong correlation with rainstorms, with a correlation coefficient of 0.70. From an on-site precipitation perspective, the algorithm-detected SWVs account for 87.6% of the observed rainstorm days. Collectively, this study introduces an updated tool for the SWV identification and underscores the algorithm’s promising potential in improving rainstorm forecasts in Southwest China.

With the rapid urbanization, waterlogging losses caused by rainstorm are becoming increasingly severe. In order to reveal the correlations between rainstorm characteristic elements, and make the calculation of rainstorm return period more reasonable and objective, this study established the joint distribution models of rainstorm elements by using copula theory based on the rainfall data in a Chinese megacity, Zhengzhou. Then their combined design values of primary return period (PRP) and secondary return period (SRP) are derived by the maximum probability method and the same frequency method. Finally, the rainstorm pattern was acquired associated with Pilgrim & Cordery method (PC). The results indicate that the calculation of rainstorm return period (RRP) with SRP is more reasonable than PRP. For same RRP, the rainstorm volume (RV) of “Or” return period type is largest, while the “And” return period’s is smallest, and the RVs of Kendall return period and survival Kendall return period are between them. Concerning Kendall return period, the RVs calculated by the maximum probability method and the same frequency method are pretty close, and their relative deviations are from -5.84% to 4.69%. Compared to “Or” return period, the rainstorm patterns of Kendall return period can reduce the magnitude and investment of the stormwater infrastructure. Moreover, the rainfall with designed rainstorm pattern of survival Kendall return period mainly concentrated before the rain peak in contrast with Kendall return period.

Practical application has shown that the blown-up theory has great predictive ability for predicting transitional weather systems, especially catastrophic weather systems. This study applies the blown-up theory to analyze and predict a rainstorm case in Jiangsu Province of East China to explore the applicability of the blown-up theory. At the same time, a numerical simulation experiment is conducted using the Weather Research and Forecasting Model (WRF) v4.2. The numerical results are compared with the European Center for Medium Weather Forecasting (ECMWF) Reanalysis v5 (ERA5) data and the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) products. It is found that there is a deviation in the simulation for the precipitation center, and further analysis indicates that it is likely related to the position of the simulated low-level shear line. On the other hand, the blown-up analyses are consistent with the actual situation and provide additional information besides the numerical simulation results. These results indicate that the blown-up charts and V-3θ diagrams are able to predict the weather system transformation, the rainfall area, and the evolution of the rainstorm, which confirms the applicability of the blown-up theory to rainstorm forecasts. This provides an auxiliary analysis method in addition to numerical simulations for rainstorm forecasts.