Short-duration Heavy Rainfall Research Articles

The Response of Cloud Precipitation Efficiency to Warming in a Rainfall Corridor Simulated by WRF

Due to model errors caused by local variations in cloud precipitation processes, there are still significant uncertainties in current predictions and simulations of short-duration heavy rainfall. To tackle this problem, the effects of warming on cloud-precipitation efficiency was analyzed utilizing a weather research and forecasting (WRF) model. The analysis focused on a rainstorm corridor event that took place in July 2020. Rainstorm events from 4–6 July formed a narrow rain belt with precipitation exceeded 300 mm in the middle and lower reaches of the Yangtze River. Temperature sensitivity tests revealed that warming intensified the potential temperature gradient between north and south, leading to stronger upward motion on the front. It also strengthened the southwest wind, which resulted in more pronounced precipitation peaks. Warming led to a stronger accumulation and release of convective instability energy. Convective available potential energy (CAPE) and convective inhibition (CIN) both increased correspondingly with the temperature. The precipitation efficiency increased sequentially with 2 °C warming to 27.4%, 31.2%, and 33.1%. Warming can affect the cloud precipitation efficiency by both promoting and suppressing convective activity, which may be one of the reasons for the enhancement of extreme precipitation under global warming. The diagnostic relationship between upward moisture flux and lower atmospheric stability during precipitation evolution was also revealed.

The Short-Duration Heavy Rainfall in Different Quadrants of Northeast China Cold Vortices

The Short-Duration Heavy Rainfall in Different Quadrants of Northeast China Cold Vortices

Comparative study on the performance of ConvLSTM and ConvGRU in classification problems—taking early warning of short-duration heavy rainfall as an example

Convolutional long short-term memory (ConvLSTM) and convolutional gated recurrent unit (ConvGRU) are two widely adopted deep learning models that combine recurrent mechanisms with convolutional operations for spatiotemporal sequences forecasting. To clarify the convergence speed and classification ability of the above two models, using the same model architecture to predict the same classification problem is necessary. This research treats the district-level warning of short-duration heavy rainfall in Beijing as a binary classification problem in deep learning, and composite radar reflectivity data of the Beijing–Tianjin–Hebei radar network and rainfall data from automatic weather stations in Beijing are used for training and performance evaluation. The results show that the convergence speed of ConvGRU is approximately 25% faster than that of ConvLSTM. The early-warning performances of ConvLSTM and ConvGRU have similar trends with region, time, and rain intensity, but most of the scores of ConvLSTM are higher, and in a few cases, ConvGRU has higher scores.摘要卷积长短期记忆单元ConvLSTM和卷积门控循环单元ConvGRU是两种广泛应用的深度学习单元, 通过将循环机制与卷积运算相结合, 常常用于时空序列的预测. 为了明确上述两种模型的收敛速度和分类能力, 需要使用相同的模型架构对相同的分类问题进行预测. 本研究将北京短时强降水区级预警问题看作深度学习中的二分类问题, 使用京津冀雷达网的组合反射率数据和北京区域内的自动气象站降雨数据进行深度学习模型的训练和评估. 结果表明, ConvGRU的收敛速度比 ConvLSTM快约25%. ConvLSTM和ConvGRU的预警性能随地区, 时间, 降雨强度的变化趋势相似, 但大部分ConvLSTM的得分较高, 少数情况下ConvGRU的得分较高.

Exploring the Spatio-Temporal Trends of Geomorphological Incidents Induced by Precipitation on Chinese Highways

The spatiotemporal distribution of geomorphological incidents was examined in the present study, including the characteristics of obstruction distances and durations, by utilizing nationwide incident mitigation data and precipitation observation records from the period spanning 2019 to 2022. By comparing rainfall features over different temporal scales across various regions, the aim of the present study was to enhance the current comprehension of the patterns through which regional precipitation initiates incidents on highways by comparing rainfall characteristics over distinct temporal scales across diverse geographical areas. The findings indicate that: (1) The spatial distribution of highway incidents in China is significantly correlated with regional natural environments, predominantly concentrated in the southern parts of the country’s second and third topographical terraces. The temporal distribution closely aligns with annual and monthly precipitation patterns, with the majority of occurrences taking place from June to September. Further, notable disparities in the distribution of highway-related incidents were observed among counties across most provinces; (2) National highways experience a notably higher frequency of incidents than expressways and provincial roads, with most obstruction lengths concentrated within 1 km and durations predominantly under 3 days; (3) The probability of daily rainfall inducing highway incidents is distinctly higher than that of short-duration rainfall, with eastern and southern China experiencing significantly greater inducing precipitation volumes than other regions. The majority of areas are susceptible to incidents within a 3-day window following heavy rainfall or within 24 h after intense short-duration rainfall. Moreover, it is observed that incidents are more closely associated with extreme precipitation occurring within a single day; (4) There is a certain lag between the timing of incidents and the occurrence of extreme short-duration heavy rainfall, with the highest frequency of incidents coinciding with continuous rainfall periods of 3 to 6 days.

Spatial and Temporal Variations of the Precipitation Structure in Jiangsu Province from 1960 to 2020 and Its Potential Climate-Driving Factors

This study investigated the temporal and spatial variations of precipitation duration and intensity in Jiangsu Province from 1960 to 2020 using the IDW spatial interpolation method and Kendall’s tau trend test, based on daily precipitation data collected from 22 meteorological stations. Additionally, a Pearson correlation analysis was conducted to examine the correlations between the occurrence rate and contribution rate of precipitation with different durations and grades, as well as five large-scale climate indices. The results indicated the following trends: (1) An increase in the precipitation duration corresponded to a decrease in the occurrence rates, while the contribution rates initially increased and then decreased. The province was predominantly characterized by 1–3 days of light rainfall, with a higher probability of short-duration heavy rainfall in northern Jiangsu. (2) From 1960 to 2020, most stations experienced decreasing trends in the precipitation duration occurrence and contribution rates, but heavy rainfall increased, suggesting a shift to short-duration heavy precipitation. (3) The Arctic Oscillation (AO) notably negatively correlates with the 9-day occurrence rate of precipitation (9dOR), while it positively correlates significantly with the occurrence rate of moderate rainfall (MROR). The North Atlantic Oscillation (NAO) exhibits a significant positive correlation with the 2-day occurrence rate of precipitation (2dOR) and a notable negative correlation with the 9-day occurrence rate of precipitation (9dOR). The PDO (Pacific Decadal Oscillation) has shown significant positive correlations with the 2-day precipitation occurrence rate (2dOR) and contribution rate (2dCR), a negative correlation with the light rainfall occurrence rate (LROR), and significant positive correlations with both the moderate and heavy rainfall occurrence rates (MROR and HROR, respectively). The AO, NAO, and PDO are potential climate factors that influence changes in the precipitation structure in Jiangsu Province. These research findings offer valuable insights for regional water resource management, flood risk assessment, and predicting future precipitation trends under climate change scenarios.

Characteristics of water vapor isotopes and moisture sources for short-duration heavy rainfall events in Nanjing, eastern China

Short-duration heavy rainfall causes severe urban flooding, threatening urban security and socio-economic development. The lower reaches of the Yangtze River are one of the regions with the highest frequency of short-duration heavy rainfalls in China. In this study, hourly stable isotope compositions in water vapor (δ18Ov and d-excessv) are analyzed for nine short-duration heavy rainfall events during the summer monsoon season (June to September) from 2013 to 2021 in Nanjing, eastern China. The circulation patterns that lead to these events can be divided into four types: tropical cyclone, low-pressure vortex, cold front, and western North Pacific subtropical high. During these events, δ18Ov is enriched, ranging from −18.8 ‰ to −13.7 ‰ with a pre-storm increasing trend. This is largely caused by strongly isolated meso- and small-scale convections and the close proximity of oceanic moisture sources. The d-excessv shows three different variation patterns during rainfall events: increasing, decreasing, and irregular fluctuations. They each correspond to the increasing contribution of terrestrial moisture from eastern China, proximal oceanic moisture from China’s offshore waters (including the South China Sea, East China Sea, and Yellow Sea), and the mixing influence of these two moisture sources. Multiple patterns of the d-excessv variations reflect both importance of terrestrial moisture from eastern China and oceanic moisture from China’s offshore waters for summer short-duration heavy rainfall events in eastern China.

Brightness Temperature Characteristics of Short-Duration Heavy Rainfall in the Chengdu–Chongqing Railway Region in China

In this study, we analyzed the brightness temperature characteristics of short-duration heavy rainfall (SDHR) along the Chengdu–Chongqing Railway (CCR), an important corridor of economic and transportation activity in southwest China. Our findings could prove useful in the monitoring and advance warning of SDHR events: (1) SDHR predominantly occurred from July to August, with a peak frequency in July in the CCR area. In terms of diurnal variation, SDHR was mainly observed at night, particularly between 22:00–05:00 and 06:00–09:00 (local time), with a peak at 01:00; (2) The relationship between SDHR and equivalent blackbody temperature (TBB) further showed that the occurrence of SDHR was accompanied by TBB decreasing to its minimum value, after which it increased, and SDHR ceased. In cases where TBB approached its minimum value after 1 h but continued to decrease slightly, SDHR continued. When SDHR occurred, the majority of the TBB values were recorded in the range 190–230 K; within this range, values between 190 and 200 K were most frequently recorded. In general, lower TBB values are associated with more intense SDHR. Based on this finding, we used linear regression to establish an estimating equation for SDHR.

Real-Time Flood Forecasting via Parameter Regionalization and Blending Nowcasts with NWP Forecasts over the Jiao River, China

Abstract Supertyphoon rainstorms are apposite examples to evaluate the utility of multisource precipitation products in monitoring and forecasting short-duration heavy rainfall and the resulting intense floods. In this study, the record-breaking floods induced by Typhoon Lekima in Jiao River, China, were retrospectively forecasted. The Xinanjiang (XAJ) model was calibrated based on parameter regionalization derived from SOM+k-means clustering. Via XAJ, the performance of the currently prevailing atmosphere reanalysis (CLDASv2 and CMA-CMORP), quantitative precipitation estimation (QPE) (IMERG-ER and PERSIANN-CCS), and quantitative precipitation forecasts (QPFs) (GRAPES_MESO, ECMWF, and GFS) in monitoring and forecasting Lekima rainfall and flood was comprehensively evaluated. A three-component blended ensemble was proposed, by blending QPE nowcasts with the weighted ensemble of QPFs through a transition of the regional GRAPES_MESO, and compared with two conventional two-component blending methods. The results indicated that the parameter regionalization enabled an explicit consideration of the spatial heterogeneity of basin attributes as well as meteorology, resulting in a minimum NSE of 0.81. CLDASv2 and CMA-CMORPH provided superior spatiotemporal accuracy with a structural similarity index up to 0.75 and NSE > 0.9 for the flood simulation. PERSIANN-CCS rainfall and the driven flood were seriously underestimated by 70% and 80%, respectively. The real-time application of QPFs during the Lekima flood provided encouraging results with a lead time of 40 h. The three-component blended ensemble method resulted in more stable and accurate flood forecasts, especially for the flood peak on 9 August, which was improved by 80%. Our results are expected to present support for real-time flood preparation and mitigation with practical significance.

Effects of joint assimilation of FY-4A AGRI and ground-based microwave radiometer on heavy rainfall prediction

As the latest generation of Chinese Geostationary Weather Satellites, Fengyun-4 carries the Advanced Geosynchronous Radiation Imager (AGRI), which has more spectral bands and higher temporal and spatial resolution than the Visible Infrared Spin-Scan Radiometer (VISSR) onboard geostationary satellite FY-2. Direct assimilation of the FY-4A AGRI datasets has been proved to be an efficient way to improve heavy rainfall simulation. We aim to assess the joint assimilation of AGRI infrared radiance and ground-based MWR (Microwave Radiometer) data on short-duration heavy rainfall prediction. RTTOV (Radiative Transfer for the TIROS Operational Vertical Sounder) is used as the observational operator for FY-4A AGRI data assimilation. The data assimilation interface is built in WRFDA 4.3 to achieve direct assimilation of FY4A AGRI radiance. The forecasting effectiveness of the joint assimilation for a typical heavy rainfall event over northern China is analyzed with four simulation experiments. The main conclusions are: 1) Assimilating MWR data can improve the initial humidity condition in the middle-lower layers, while AGRI radiance assimilation favors the initial humidity correction in the middle-upper layers. The joint assimilation of two datasets can remarkably improve the initial humidity condition in the entire column. 2) Data assimilation effectively improves the 6-h accumulated rainfall simulation. The joint assimilation of AGRI radiance and MWR data is superior to assimilating either of them. The joint assimilation significantly improves the rainfall forecast over the Beijing area, where the seven MWRs are distributed. 3) Data assimilation experiments present similar effects on predicted and initial humidity conditions. The MWR_DA experiment (only assimilate MWR data) markedly improves the humidity forecast in the middle-lower layers, while AGRI_DA (only assimilate AGRI data) is effective in the middle-upper layers. The joint assimilation of AGRI radiance and MWR data could skillfully correct the humidity distribution in the entire layers, allowing for more accurate heavy rainfall prediction. This paper provides a valuable basis for further improving the application of FY-4A AGRI radiance in numerical weather models.

Performance evaluation of IMERG products based on the extremely heavy rainstorm event (2021) once in a thousand years in Henan, China

Henan, a province of central China, experienced rainfall at the level of rare extremely heavy rainstorms once in a millennium during the period from July 17th to July 23rd, 2021. Based on ground-based rainfall data from 116 gauges, the performance of Global Rainfall Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) products (IMERG-Early run (IMERG-E), IMERG-Late run (IMERG-L), and IMERG-Final run (IMERG-F)) were evaluated from the seven-day rainfall change process, the hourly rainfall change process on July 20th and the six traditional indexes. Results indicate that the overall performance of IMERG-F is the best, relative bias (RB) is −0.03 and correlation coefficient (CC) is 0.51. IMERG-L (RB, −0.09; CC, 0.49) is very close to IMERG-F More outstandingly, in the three days of 19th, 20th and 21st, RB of IMERG-L per day is −0.01, 0.02, and − 0.13, respectively. IMERG-L shows a greater ability to capture extreme short-duration heavy rainfall in the peak period compared to the other two products. Since weak rainfall overestimation coefficient (WROC) is >0.5, it can be concluded that RB of excessively overestimated gauges are >100% mainly determined by the overestimation during weak rainfall; Because of overestimation coefficient (OC) and weak rainfall coefficient (WRC), there is an obvious error trend that gauges with weak rainfall (≤ 1 mm/h) are easily overestimated and gauges with non-weak rainfall (> 1 mm/h) are easily underestimated; IMERG-F has higher entire accuracy and reduces the error trend because of the large number of PMW estimates.

The features and probability forecasting of short–duration heavy rainfall in the Beijing-Tianjin-Hebei region caused by North China cold vortices

Based on hourly station precipitation data and ECMWF ERA5 reanalysis data from 2009 to 2019, this paper explores the temporal variations and spatial distribution of short–duration heavy rainfall (SDHR) induced by North China cold vortices (NCCV) over the Beijing-Tianjin-Hebei (BTH) region, and comparatively analyzes the characteristic of environmental parameters and then choose some predictors to make probability forecasting for short–duration heavy rainfall induced by North China cold vortices. Results show that short–duration heavy rainfall has obviously interannual, monthly and diurnal variations. Areas of high short–duration heavy rainfall frequency caused by North China cold vortices exhibit eastward movement, which generally locate along the mountain areas of the Beijing-Tianjin-Hebei region in the afternoon, and moves to the coastal areas of the Beijing-Tianjin-Hebei region after midnight. In general, short–duration heavy rainfall induced by North China cold vortices mainly occurs in 16:00–21:00 and around 02:00–05:00, showing a delayed peak time and a secondary peak time in recent years. Besides, short–duration heavy rainfall caused by North China cold vortices occurs fewer but more extremely over the northwestern and southern parts of the Beijing-Tianjin-Hebei region, more frequently and extremely over the border area of the Beijing-Tianjin-Hebei region, and more frequently but with moderate intensity over the coastal area of the Beijing-Tianjin-Hebei region. By comparing the distribution characteristics of some physical parameters for three categories of no precipitation, ordinary precipitation, and short–duration heavy rainfall weather induced by North China cold vortices, it is found that moisture and atmospheric instability conditions have great significance for the occurrence of short–duration heavy rainfall caused by North China cold vortices. Probability forecast for short–duration heavy rainfall caused by North China cold vortices is made based on ingredient method and fuzzy logic algorithms. The result shows the products have good performance, further implying the significance of the environmental parameters for forecasting short–duration heavy rainfall caused by North China cold vortices.

Simulation-based assessment of inundation risk potential considering the nonstationarity of extreme flood events under climate change

The projected increase in the frequency of extreme rainfall events with climate change has serious implications for flood risk management. This study developed a novel method to evaluate future flood inundation risk in the Kakehashi River basin, Japan. First, a pseudo global warming (PGW) method and ensemble simulation techniques were combined to develop rainfall projections with different return periods, based on the Weather Research and Forecasting (WRF) model. Second, runoff analyses were performed for the target river basin, and inundation simulations, including levee breaches, were conducted at high spatial resolution (40 × 40 m). Finally, the potential inundation risk for the river basin was estimated. Rainfall simulation results indicated intensification of short-duration heavy rainfall events. The PGW ensemble simulations indicated that extreme rainfall scenarios with long return periods (>1000 years, based on current conditions) are likely to occur more frequently in the future, highlighting the possibility of flood intensification. Regardless of the length of return period, areas with infrequent flooding but large inundation depth and those with more frequent flooding but small inundation depth were classified as high risk. The proposed method provides a baseline framework for future flood risk assessments and the results highlight the importance of incorporating (currently) rare heavy rainfall events in future flood management evaluation and planning.

Subdaily Rain-Rate Properties in Western Java Analyzed Using C-Band Doppler Radar

Abstract Jakarta, a megacity in Indonesia, experiences recurrent floods associated with heavy rainfall. Characteristics of subdaily rainfall and the local factors influencing rainfall around Jakarta have not been thoroughly investigated, primarily because of data limitations. In this study, we examine the frequency and intensity of hourly and daily rain rate, including spatial characteristics and variations across time scales. We use 6-min C-band Doppler radar and 1-min in situ data during 2009–12 to resolve spatial rain-rate characteristics at higher resolution than previous studies. A reflectivity–rain rate (Z–R) relationship is derived (Z = 102.7R1.75) and applied to estimate hourly rain rate. Our results show that rain rate around Jakarta is spatially inhomogeneous. In the rainy season [December–February (DJF)], rain rate exhibits statistical properties markedly different from other seasons, with much higher frequency of rain, but, on average, less intense rain rate. In all seasons, there is a persistent higher hourly and daily mean rain rate found over mountainous areas, indicating the importance of local orographic effects. In contrast, for hourly rain-rate extremes, peaks are observed mostly over the coastal land and lowland areas. For the diurnal cycle of mean rain rate, a distinct afternoon peak is found developing earlier in DJF and later in the dry season. This study has implications for other analyses of mesoscale rain-rate extremes in areas of complex topography and suggests that coarse-grain products may miss major features of the rain-rate variability identified in our study. Significance Statement For many years, Jakarta and its surrounding regions have been repeatedly inundated by flooding triggered by short-duration heavy rainfall or rainfall accumulated over multiple days. Little is known about the distribution of local rainfall and how it differs between seasons. In this study, we used high-resolution C-band Doppler radar during 2009–12 to understand the characteristics of rainfall over this complex topography. The results demonstrate that the rainfall features vary spatially and seasonally. In the wet season, rainfall is more frequent but, on average, lighter relative to other seasons. In all seasons, the highest hourly and daily mean rain rate persistently occurs over the mountains, indicating the vital role of topography in generating rainfall in the region.

Attributing heavy rainfall event in Berchtesgadener Land to recent climate change – Further rainfall intensification projected for the future

On 17 July 2021, storm “Bernd” hit the alpine region of Berchtesgadener Land inducing short-duration heavy rainfall, which triggered flash floods, debris flows, landslides, and flooding. Based on the observed precipitation data and an analysis of the runoff measurements, the driver of the event is defined as a 3-h rainfall. The 50-member single model initial-condition large ensemble of the Canadian Regional Climate Model version 5 under the emission scenario RCP 8.5 is employed to explore the occurrence probability of the event under historic, current, and future climate conditions. For the rainfall event, a return period of 21 years (17–25 years) is found for the current climate (2006-2035). Under historic climate (1970-1999) the event is estimated to be 3.1 (1.9–5.2) times less likely equalling a return period of 64 years (48–90 years). This is particularly critical as experience and observational data from the recent past have been crucial to the design of infrastructure and still influence current planning. For future climate conditions, the event probability is projected to increase resulting in return periods of 7.8 years (7.1–8.8 years; 2040-2069) and 4.9 years (4.6–5.4 years; 2070-2099), respectively. The future shifts in extreme precipitation must be urgently taken into account for appropriate adaptation measures.

Probability Forecasting of Short-Term Short-Duration Heavy Rainfall Combining Ingredients-Based Methodology and Fuzzy Logic Approach

Highly convection-related short-duration heavy rainfall (SDHR), defined as rainfall greater than 20 mm h−1 of a whole hour, causes severe damage every year in China. An objective forecasting method is developed to provide guidance products for the short-term probability of SDHR. Representative parameters of environmental moisture content, instability, and dynamical forcing are selected as predictors based on the ingredients-based methodology. The predictors are selected by comparing their ability to discriminate between SDHR and both no rainfall and ordinary rainfall with hourly rainfall records and the NCEP reanalysis dataset during the warm seasons of 2002 and 2009. A fuzzy logic approach is obtained for the calculation of SDHR probability. Intervals of intensities are obtained based on specific percentiles and various weight settings examined. The probabilistic SDHR forecasts during the 2015 warm seasons with the NCEP GFS dataset are obtained, and forecasts are evaluated by using an operational used spatial verification method. Results show that the reference operational SDHR forecasts are surpassed by the 00–12 h period objective SDHR forecasts measured with the maximum critical success index (CSI), and even the average CSI (CSIave) for the top groups is better than the reference. The guidance SDHR products are skillful within 60 h. Although the weights vary significantly, the short-term patterns of the SDHR probability are mainly determined by the environmental conditions. The objective forecasting method is ingredients-based but is combined with fuzzy logic algorithms. The new approach provides a feasible exploration of the convective weather phenomenon.

Efficacy Analysis of Urban Planning Scenarios for Flood Mitigation with Low Impact Development Technologies Using SWMM: A Case Study in Saitama City, Japan

LID (Low impact Development) has been widely promoted as a measure against urban flooding which has been recently increasing due to urbanization and climate change. However, studies that consider the combined effects of spatially distributing multiple LIDs simultaneously in an urban area of specific size as urban planning scenarios are few. In this study, two cases of past rainfall data (short duration and long duration heavy rainfall), are used to simulate the effects of 3 different urban planning scenarios of distributed LID (i.e. combined LIDs implementable at the 1) building-level, 2) in open spaces, and 3) combined implementation of both 1&2), in addition to simulating for separate implementation of each LID type using the Storm Water Management Model (SWMM). The results show that in the case of short duration heavy rainfall, all 3 LID scenarios provide a greater decrease in the rate of flood volume with comparison to the case of long duration heavy rainfall. This points to the fact that LIDs have a high potential to mitigate flood volumes resulting from short duration heavy rainfall - the type of rainfall which has become more frequent recently. Furthermore, the paper also organizes the LID types according to their implementability under different urban planning scenarios, and shows that such combined use of LIDs results in higher flood mitigation efficacy.

Mechanisms of Short-Duration Heavy Rainfall in the Western Pacific Subtropical High Area: An Analysis of Two Rainstorms of 2018 in Hunan Province, China

ABSTRACT This study examines two short-duration heavy rainfall cases of 2018 in Hunan province, China, using observations and the NCEP FNL analyses. Short-duration heavy rainfall occurring in the western Pacific subtropical high (WPSH) area is one of the major natural hazards during spring and summer over the middle reaches of the Yangtze River basin. Rainstorms in the two cases selected showed high echo-top height but low storm centroid elevation, resembling the “low-echo centroid” structure. Weak vertical shear was observed in the mid-lower troposphere, thereby leading to a short life cycle of storms. Before the heavy rainfall events, in addition to substantial changes in convective available potential energy (CAPE) and convective inhibition (CIN), both cases were characterized by a lack of troughs and jet streams in the middle and upper troposphere over the middle reaches of the Yangtze River basin. A proper configuration of the WPSH extending to the middle reaches of the Yangtze River basin along with low-level synoptic systems (e.g. a surface convergence line or the cold air invading) favoured moisture supply and lifting mechanisms for convection and the rainstorms. During the hot afternoon hours, the thermals forming at the surface further enhanced convection and the rainstorms.

Diurnal Variation and Distribution of Short-Duration Heavy Rainfall in Beijing–Tianjin–Hebei Region in Summer Based on High-Density Automatic Weather Station Data

The distribution and diurnal variation of short-duration heavy rainfall (SDHR) and the influence of a complex underlying surface were studied by using fine-scale hourly precipitation data in the Beijing–Tianjin–Hebei (BTH) region during the summers of 2014–2020. Areas prone to SDHR are located mainly in the southern foothills of the Yanshan Mountains, the foothills area, and the trumpet-shaped topographic entrance area north of Beijing, areas inland of the west coast of Bohai Bay, and the northern Beijing urban area. Owing to the influence of topography and the geographical location, the distribution and diurnal variation SDHR is significantly different in the western and northern mountainous areas, the foothills, and the plains. Compared to the underlying urban surface, the topography and the land–sea interface have considerable effects on the distribution of SDHR. A key finding is that the foothills of northern of Beijing, eastern slope and piedmont area of the Taihang Mountains, and the land–sea interface of Bohai Bay play important roles in the formation and propagation of SDHR.

A seven-year climatology of the initiation, decay and morphology of severe convective storms during the warm season over North China

AbstractThe present work established a 7-year climatology of the initiation, decay, and morphology of severe convective storms (SCSs) during the warm seasons (May–September) of 2011–2018 (except 2014) over North China. This was achieved by using severe weather reports, precipitation observations, and composite Doppler radar reflectivity data. A total of 371 SCSs were identified. SCSs primarily initiated around noon with the highest frequency over the high terrain of Mount Taihang, and they mostly decayed over the plains at night. The storm morphologies were classified into three types of cellular storms (individual cells, clusters of cells, and broken lines), six types of linear systems (convective lines with no stratiform, with trailing stratiform, leading stratiform, parallel stratiform, embedded lines, and bow echoes), and nonlinear systems. Three types of severe convective weather, namely, short-duration heavy rainfall, hail, and thunderstorm high winds associated with these morphologies were investigated. Nonlinear systems were the most frequent morphology, followed by clusters of cells. Convective lines with trailing stratiform were the most frequent linear morphology. A total of 1,429 morphology samples from the 371 SCSs were found to be responsible for 15,966 severe convective weather reports. Linear (nonlinear) systems produced the most short-duration heavy rainfall (hail and thunderstorm high wind) reports. Bow echos were most efficient in producing both short-duration heavy rainfall and thunderstorm high wind reports whereas broken lines had the highest efficiency for hail production. The results in the present study are helpful for local forecasters to better anticipate the storm types and associated hazardous weather.

Statistical characteristics and risk zoning of different duration heavy rainfall in Shanxi

Based on different duration heavy rainfall data and the associated disaster situation, geographic information, socio-economic characteristics, river network density, and geological hazard-prone zoning of 109 stations in Shanxi Province in the past 38 years, a statistical analysis of different duration heavy rainfall events in Shanxi Province was carried out. In addition, a comprehensive risk zoning was performed using hierarchy analysis and weighted comprehensive evaluation methods. The results show that: (1) the spatial distribution of the extreme value indicates the following: the mountain area is larger than that of the basin, and the south is greater than the north and has a shorter time-effect and a stronger local distribution of the extreme value. Yuanqu County (YuanQ) has the highest concentration area of all different duration heavy rainfall events within 12 h. (2) Within 12 h., the occurrence frequency of different duration heavy rainfall has the spatial distribution characteristics of being higher in the south and lower in the north, higher in the mountain area than in the basin area, higher in the eastern mountain area than in the western mountain area, and obviously concentrated in the southeast. YuanQ is a high incidence area of short-duration heavy rainfall over 1 h. and 3 h., and Jincheng City (JinC) is a high incidence area of heavy rainfall over 6 h and 12 h.. (3) Severe precipitation with different durations occurs in July–August every year, and the frequency of hourly heavy rainfall is the highest. (4) The intra-day distributions of heavy rainfall over a period of 1 h., 3 h., and 12 h. are single-peak curves, with peaks at 18:00, 19:00 and 09:00, respectively; the intra-day distribution of heavy rainfall over 6 h. is a double peak curve, with peaks at 06:00 and 20:00. (5) The variation trend of the annual occurrence times of short-duration heavy precipitation is similar for 1 h, 3 h, and 6 h, and the growth rate is the highest in southeastern Shanxi Province. The variation trend of the occurrence times of heavy rainfall over 12-h. is different from that of 1-h., 3-h., and 6-h. short-duration heavy rainfall. The rate of growth is the largest in the eastern and western mountain areas of Shanxi Province. (6) The whole area of JinC, the east of Yuncheng City (YunC), and the southeast of Changzhi City (CZ) are the high-risk areas for all different duration heavy precipitation disaster-causing factors within 12 h. As the duration of heavy rainfall increases, the high-risk areas with respect to disaster factors in Linfen City (LF) and CZ increase. (7) JinC, YunC, and Liulin County (LL) are high-risk areas for the comprehensive risk of different duration heavy rainfall within 12 h, and LF and CZ districts increase the extent of high-risk areas with the increase in the duration of heavy precipitation.