Volume 53,Issue 3,2025 Table of Contents
2025, 53(3):301-313.
DOI: 10.19517/j.1671-6345.20240237
Abstract:
Radar malfunctions and other factors often lead to abnormal echoes, directly affecting data quality. The abnormal data entering the data sharing system have a very serious impact on the quality of observation data in the network of China’s new generation weather radar (CINRAD), as well as quantitative applications such as radar data assimilation and precipitation estimation, reducing the accuracy of short-term forecasting systems and numerical forecasting models. At present, the meteorological department carries out stream transmission, data sharing, and business monitoring based on radar radial data. However, data quality control mainly relies on the analysis and processing of volume scan data, using the whole or regional image features for analysis and processing. The data analysis is not precise enough, the identification of erroneous data is not accurate enough, and the timeliness is low, which cannot provide fast and refined real-time radar data quality control. At the same time, abnormal data have randomness and diversity, but existing data quality control methods mainly target a certain factor that affects the quality of radar data, such as sea waves, bird flocks, electromagnetic interference, radar fault echo data, etc. Therefore, it is urgent to study a universal method for rapid identification of abnormal echo data, improve the timeliness and quality of radar data quality control, and meet the business needs of refined forecasting services. This article proposes a method for identifying abnormal data based on radar radial data feature analysis. By analysing the number of radial echoes, the maximum distance of radial echoes, the average intensity of radial echoes, and the correlation of radial reflectivity factors, a membership function and an identification equation for abnormal echo data are established to determine the threshold for identifying abnormal echo data. This method more accurately and finely identifies multiple types of radar abnormal echoes. Under clear weather conditions, the position and intensity of ground clutter are relatively fixed. By statistically analysing the dynamic range of the number of normal radial echoes, the maximum distance of radial echoes, and the average intensity of radial echoes, the membership functions and thresholds of each parameter of abnormal radial data are determined, and a comprehensive identification equation is established. Under non-clear weather conditions, there are meteorological echoes, and the evolution of normal meteorological echoes has reasonable limits, with a certain degree of continuity in time and space. The radial reflectivity of adjacent volume scans has good correlation in normal echo data, while radar abnormal echoes often have suddenness, manifested as abnormal distributions of the radial echo numbers, the maximum radial echo distances, and the average radial echo intensity, and reduce the correlation between radial reflectivity of adjacent volume scans. Therefore, normal radar echo data are taken as a sample, and a certain time interval is selected. Through dynamic range statistical analysis of four parameters: the ratio of the number of radial echoes, the ratio of the maximum distance of radial echoes, the ratio of the average intensity of radial echoes, and the correlation of radial reflectivity factors in the same time interval and elevation angle adjacent azimuth radial data of normal echoes, the membership function, identification equation, and judgment threshold of abnormal echo data are determined to identify abnormal radial data. Using the above identification methods, the hardware faults, as well as abnormal echo data caused by calibration errors, super refraction, and electromagnetic interference of Shijiazhuang CINRAD/SA new generation weather radar, are identified. The overall recognition rate of abnormal data is over 90%. The abnormal data recognition method based on radial data using fuzzy logic can be applied to identify various abnormal echo data caused by hardware failures, as well as non-meteorological echoes such as super-refraction and electromagnetic interference, and has wide applicability. It quickly and finely identifies abnormal radar echo data, supplements and improves existing radar data quality control methods, and provides technical support for providing high-quality radar detection data to meet the precise forecasting and fine service meteorological business needs.
Radar malfunctions and other factors often lead to abnormal echoes, directly affecting data quality. The abnormal data entering the data sharing system have a very serious impact on the quality of observation data in the network of China’s new generation weather radar (CINRAD), as well as quantitative applications such as radar data assimilation and precipitation estimation, reducing the accuracy of short-term forecasting systems and numerical forecasting models. At present, the meteorological department carries out stream transmission, data sharing, and business monitoring based on radar radial data. However, data quality control mainly relies on the analysis and processing of volume scan data, using the whole or regional image features for analysis and processing. The data analysis is not precise enough, the identification of erroneous data is not accurate enough, and the timeliness is low, which cannot provide fast and refined real-time radar data quality control. At the same time, abnormal data have randomness and diversity, but existing data quality control methods mainly target a certain factor that affects the quality of radar data, such as sea waves, bird flocks, electromagnetic interference, radar fault echo data, etc. Therefore, it is urgent to study a universal method for rapid identification of abnormal echo data, improve the timeliness and quality of radar data quality control, and meet the business needs of refined forecasting services. This article proposes a method for identifying abnormal data based on radar radial data feature analysis. By analysing the number of radial echoes, the maximum distance of radial echoes, the average intensity of radial echoes, and the correlation of radial reflectivity factors, a membership function and an identification equation for abnormal echo data are established to determine the threshold for identifying abnormal echo data. This method more accurately and finely identifies multiple types of radar abnormal echoes. Under clear weather conditions, the position and intensity of ground clutter are relatively fixed. By statistically analysing the dynamic range of the number of normal radial echoes, the maximum distance of radial echoes, and the average intensity of radial echoes, the membership functions and thresholds of each parameter of abnormal radial data are determined, and a comprehensive identification equation is established. Under non-clear weather conditions, there are meteorological echoes, and the evolution of normal meteorological echoes has reasonable limits, with a certain degree of continuity in time and space. The radial reflectivity of adjacent volume scans has good correlation in normal echo data, while radar abnormal echoes often have suddenness, manifested as abnormal distributions of the radial echo numbers, the maximum radial echo distances, and the average radial echo intensity, and reduce the correlation between radial reflectivity of adjacent volume scans. Therefore, normal radar echo data are taken as a sample, and a certain time interval is selected. Through dynamic range statistical analysis of four parameters: the ratio of the number of radial echoes, the ratio of the maximum distance of radial echoes, the ratio of the average intensity of radial echoes, and the correlation of radial reflectivity factors in the same time interval and elevation angle adjacent azimuth radial data of normal echoes, the membership function, identification equation, and judgment threshold of abnormal echo data are determined to identify abnormal radial data. Using the above identification methods, the hardware faults, as well as abnormal echo data caused by calibration errors, super refraction, and electromagnetic interference of Shijiazhuang CINRAD/SA new generation weather radar, are identified. The overall recognition rate of abnormal data is over 90%. The abnormal data recognition method based on radial data using fuzzy logic can be applied to identify various abnormal echo data caused by hardware failures, as well as non-meteorological echoes such as super-refraction and electromagnetic interference, and has wide applicability. It quickly and finely identifies abnormal radar echo data, supplements and improves existing radar data quality control methods, and provides technical support for providing high-quality radar detection data to meet the precise forecasting and fine service meteorological business needs.
2025, 53(3):314-326.
DOI: 10.19517/j.1671-6345.20240253
Abstract:
Because of its small size, low cost, perfect function, and stable performance, X-band weather radar provides fine observation data as a supplement for the new generation of weather radar in the low-level blind area, mountainous area, and key monitoring area. In recent years, Yunnan Province builds a number of X-band dual-polarisation weather radars to supplement the detection blind spots of the new generation of weather radar observation network and improve the coverage of radar observation in the province. In order to effectively improve the accuracy of multi-system radar network observation, the heavy rainfall weather process occurring in Kunming and Dehong Prefecture and their surrounding areas on 28 July 2023, is selected, and the data of synchronous observation bodies in Kunming, Chenggong, Dehong, and Yingjiang are taken as an example to compare the radar echo intensity of different time and elevation combinations. The consistency of echo intensity between adjacent C-band weather radar and X-band weather radar in Yunnan is analysed. The results show that both X-band weather radar and C-band weather radar can accurately reflect the intensity change of precipitation, but there is a certain deviation in the measured echo intensity; the former is larger than the latter. In the same observation area, the echo shapes of the two radars at different times and elevation angles are basically the same, and the echo generation, extinction, and change trend are consistent, correctly reflecting the intensity change of precipitation. The strong centre of the echo appears in the same position, but the strong centre of the X-band weather radar is more prominent. At the same time, the echo intensity of X-band weather radar is generally higher than that of C-band weather radar. The average echo value of Chenggong radar is 3.5 dBz higher than that of Kunming radar, and the maximum echo value is 15.5 dBz higher, and the average echo value of Yingjiang radar is about 5 dBz higher than that of Dehong radar, and the maximum echo value is 19.5 dBz higher. In the same observation area, C-band weather radar has more weak echoes, X-band weather radar has more strong echoes, and the peak echo intensity of X-band weather radar is greater than that of C-band weather radar. Comprehensive analysis shows that radar hardware difference, calibration inconsistency, beam blocking, altitude inconsistency, atmospheric attenuation, atmospheric environment difference, and so on are the factors that cause the echo intensity inconsistency between adjacent radars. Therefore, it is necessary to carry out unified system calibration and radar echo intensity attenuation correction to improve the accuracy and consistency of radar network observation.
Because of its small size, low cost, perfect function, and stable performance, X-band weather radar provides fine observation data as a supplement for the new generation of weather radar in the low-level blind area, mountainous area, and key monitoring area. In recent years, Yunnan Province builds a number of X-band dual-polarisation weather radars to supplement the detection blind spots of the new generation of weather radar observation network and improve the coverage of radar observation in the province. In order to effectively improve the accuracy of multi-system radar network observation, the heavy rainfall weather process occurring in Kunming and Dehong Prefecture and their surrounding areas on 28 July 2023, is selected, and the data of synchronous observation bodies in Kunming, Chenggong, Dehong, and Yingjiang are taken as an example to compare the radar echo intensity of different time and elevation combinations. The consistency of echo intensity between adjacent C-band weather radar and X-band weather radar in Yunnan is analysed. The results show that both X-band weather radar and C-band weather radar can accurately reflect the intensity change of precipitation, but there is a certain deviation in the measured echo intensity; the former is larger than the latter. In the same observation area, the echo shapes of the two radars at different times and elevation angles are basically the same, and the echo generation, extinction, and change trend are consistent, correctly reflecting the intensity change of precipitation. The strong centre of the echo appears in the same position, but the strong centre of the X-band weather radar is more prominent. At the same time, the echo intensity of X-band weather radar is generally higher than that of C-band weather radar. The average echo value of Chenggong radar is 3.5 dBz higher than that of Kunming radar, and the maximum echo value is 15.5 dBz higher, and the average echo value of Yingjiang radar is about 5 dBz higher than that of Dehong radar, and the maximum echo value is 19.5 dBz higher. In the same observation area, C-band weather radar has more weak echoes, X-band weather radar has more strong echoes, and the peak echo intensity of X-band weather radar is greater than that of C-band weather radar. Comprehensive analysis shows that radar hardware difference, calibration inconsistency, beam blocking, altitude inconsistency, atmospheric attenuation, atmospheric environment difference, and so on are the factors that cause the echo intensity inconsistency between adjacent radars. Therefore, it is necessary to carry out unified system calibration and radar echo intensity attenuation correction to improve the accuracy and consistency of radar network observation.
2025, 53(3):327-334.
DOI: 10.19517/j.1671-6345.20240110
Abstract:
The drift phenomenon exists in the process of radisonde meteorological observation, and the characteristics of drifting data are of great significance for evaluating the accuracy of ground-based microwave radiometer retrieval products. By researching the drift characteristics of radisonde data at the 0 to 10 km height range of Jinghe National Basic Station in Xi’an from 31 October 2017, to 31 December 2023, on the basis of dividing the station area and the drifting area, this study discusses the influence of drift on temperature evaluation of ground-based microwave radiometers under different weather conditions. The results show that both the Root Mean Squared Error (RMSE) and Correlation Coefficient (Corr) of the drift area are larger than those of the station area, and the Corr is smaller than that of the station area, exhibiting distinct interval characteristics. For clear-sky conditions, the RMSE decreases while the Corr increases in the middle and lower troposphere, and the maximum regional difference occurs at 4.25 km. For cloudy conditions, both the RMSE and Corr increase, and the maximum regional difference in the correlation coefficient occurs at 5.25 km. As altitude increases, for clear-sky conditions, the RMSE and Corr tend to approach those of the station area, while for cloudy conditions, only the Corr approaches and overlaps around 8 km. Due to the combined influence of sounding drift and weather conditions, there are differences in the evaluation indexes of different weather in the same region. The RMSE of clear-sky weather is larger than that of cloudy weather, and the Corr is smaller. The RMSE of the drifting region is close, and the Corr of clear sky is small. Under long-distance sounding drift conditions, wind effects lead to changes in kinetic and thermal energy, particularly within the 7 km altitude range in the troposphere, where wind speed differences under different weather conditions are significant. These factors are the main reasons for the large deviations in temperature evaluation metrics of ground-based microwave radiometers. The study provides a reference for using sounding data to evaluate the data accuracy and product application of new atmospheric detection equipment.
The drift phenomenon exists in the process of radisonde meteorological observation, and the characteristics of drifting data are of great significance for evaluating the accuracy of ground-based microwave radiometer retrieval products. By researching the drift characteristics of radisonde data at the 0 to 10 km height range of Jinghe National Basic Station in Xi’an from 31 October 2017, to 31 December 2023, on the basis of dividing the station area and the drifting area, this study discusses the influence of drift on temperature evaluation of ground-based microwave radiometers under different weather conditions. The results show that both the Root Mean Squared Error (RMSE) and Correlation Coefficient (Corr) of the drift area are larger than those of the station area, and the Corr is smaller than that of the station area, exhibiting distinct interval characteristics. For clear-sky conditions, the RMSE decreases while the Corr increases in the middle and lower troposphere, and the maximum regional difference occurs at 4.25 km. For cloudy conditions, both the RMSE and Corr increase, and the maximum regional difference in the correlation coefficient occurs at 5.25 km. As altitude increases, for clear-sky conditions, the RMSE and Corr tend to approach those of the station area, while for cloudy conditions, only the Corr approaches and overlaps around 8 km. Due to the combined influence of sounding drift and weather conditions, there are differences in the evaluation indexes of different weather in the same region. The RMSE of clear-sky weather is larger than that of cloudy weather, and the Corr is smaller. The RMSE of the drifting region is close, and the Corr of clear sky is small. Under long-distance sounding drift conditions, wind effects lead to changes in kinetic and thermal energy, particularly within the 7 km altitude range in the troposphere, where wind speed differences under different weather conditions are significant. These factors are the main reasons for the large deviations in temperature evaluation metrics of ground-based microwave radiometers. The study provides a reference for using sounding data to evaluate the data accuracy and product application of new atmospheric detection equipment.
2025, 53(3):335-346.
DOI: 10.19517/j.1671-6345.20240181
Abstract:
The analysis of the winter snowdrop spectrum on the north of the Guizhou Plateau from 2018 to 2023 shows that the distribution of snow droplet patterns is closely related to the number, size, shape, and density of particles. The snowfall amount and snow depth are related to the accumulation of snow particles. The starting and ending time and the number of snow particles directly reflect the evolution characteristics of the whole snowfall process. The specific conclusions are as follows: (1) From the perspective of particle number and size spectrum distribution, the diameter spectrum width of the raindrops and snowdrops is mainly distributed between 1-5 mm and 5-15 mm. In winter, the northern side of the Guizhou Plateau often experiences weak rainfall events, with the number of drizzle particles being about 5% higher than that of rain particles. The average diameter of the raindrop spectrum is less than 3 mm, which belongs to the narrow-spectrum precipitation type. During winter snowfall, the proportion of snow particles exceeds 75%, and the snow particle size distribution is higher than that of raindrops. The diameter of the snowfall spectrum is greater than 8 mm, which belongs to the wide-spectrum precipitation type. This provides a good indication for identifying snow weather. (2) From the particle number velocity spectrum distribution, the velocity spectrum width of raindrops and snowflakes mainly ranges from 5-10 m·s-1 to 3-5 m·s-1. The mode of particle speed is 2.2 m·s-1 and 1.1 mm·s-1. In comparison, the raindrop spectrum and snowdrop velocity spectrum are distributed in two intervals above and below 5 m·s-1, and the values of the particle grading velocity differ by a factor of 2. The shape of snow particles is flat, the density is small, and the size is large, which leads to a lower falling speed. Using the particle falling speed as a method to identify rain and snow precipitation types is highly representative. (3) In a single snowfall event, the number of all particles can be used as the quantity for calculating snow depth accumulation. There is a significant positive correlation between the measured snowfall and the inverted snowfall, and they show good consistency in the changing trend. However, the correlation and trend consistency between the measured snow depth and the inversion result are weaker than those of the snowfall inversion, which is related to ambient temperature conditions, precipitation phase transformation, and snow melting rate. (4) The measurement and inversion of snow depth are only meaningful when snow particles persist, so the identification of precipitation phase types is particularly critical, as it serves as an important basis for judging the accumulation time of snow particles. The snowfall amount and snow depth inverted using the particle number and particle diameter (particle volume) show good estimation results. The evolution characteristics of the snow weather process or the period of ground snow accumulation can be reproduced using characteristic quantities such as particle phase, particle number, snowfall, snow depth, and snow accumulation rate. This has a good guiding effect on the monitoring and evaluation of snowfall and snow accumulation.
The analysis of the winter snowdrop spectrum on the north of the Guizhou Plateau from 2018 to 2023 shows that the distribution of snow droplet patterns is closely related to the number, size, shape, and density of particles. The snowfall amount and snow depth are related to the accumulation of snow particles. The starting and ending time and the number of snow particles directly reflect the evolution characteristics of the whole snowfall process. The specific conclusions are as follows: (1) From the perspective of particle number and size spectrum distribution, the diameter spectrum width of the raindrops and snowdrops is mainly distributed between 1-5 mm and 5-15 mm. In winter, the northern side of the Guizhou Plateau often experiences weak rainfall events, with the number of drizzle particles being about 5% higher than that of rain particles. The average diameter of the raindrop spectrum is less than 3 mm, which belongs to the narrow-spectrum precipitation type. During winter snowfall, the proportion of snow particles exceeds 75%, and the snow particle size distribution is higher than that of raindrops. The diameter of the snowfall spectrum is greater than 8 mm, which belongs to the wide-spectrum precipitation type. This provides a good indication for identifying snow weather. (2) From the particle number velocity spectrum distribution, the velocity spectrum width of raindrops and snowflakes mainly ranges from 5-10 m·s-1 to 3-5 m·s-1. The mode of particle speed is 2.2 m·s-1 and 1.1 mm·s-1. In comparison, the raindrop spectrum and snowdrop velocity spectrum are distributed in two intervals above and below 5 m·s-1, and the values of the particle grading velocity differ by a factor of 2. The shape of snow particles is flat, the density is small, and the size is large, which leads to a lower falling speed. Using the particle falling speed as a method to identify rain and snow precipitation types is highly representative. (3) In a single snowfall event, the number of all particles can be used as the quantity for calculating snow depth accumulation. There is a significant positive correlation between the measured snowfall and the inverted snowfall, and they show good consistency in the changing trend. However, the correlation and trend consistency between the measured snow depth and the inversion result are weaker than those of the snowfall inversion, which is related to ambient temperature conditions, precipitation phase transformation, and snow melting rate. (4) The measurement and inversion of snow depth are only meaningful when snow particles persist, so the identification of precipitation phase types is particularly critical, as it serves as an important basis for judging the accumulation time of snow particles. The snowfall amount and snow depth inverted using the particle number and particle diameter (particle volume) show good estimation results. The evolution characteristics of the snow weather process or the period of ground snow accumulation can be reproduced using characteristic quantities such as particle phase, particle number, snowfall, snow depth, and snow accumulation rate. This has a good guiding effect on the monitoring and evaluation of snowfall and snow accumulation.
2025, 53(3):347-361.
DOI: 10.19517/j.1671-6345.20240115
Abstract:
The GRAPES_MESO and WRF models are used to analyse the computational characteristics of numerical models on the KUNPENG platform, and are compared with the Intel (X86) platform to explore the improvement space of numerical models in resource utilisation, computational bottlenecks, hotspot functions, and other aspects on the KUNPENG platform. The results indicate that: (1) After adaptation, both models obtain consistent results on the domestic KUNPENG platform as on the X86 platform. (2) Both models exhibit good parallel scalability on both X86 and KUNPENG platforms. When using the same number of processes, the computing efficiency of the KUNPENG platform is 65% to 90% of that of the X86 platform. However, when using the same number of nodes, the computing efficiency of the KUNPENG platform exceeds that of the X86 platform by 22% to 45%. (3) In terms of hardware resource utilisation, the two models consume the most time in computing, followed by communication, and finally IO. The models have a higher CPU usage rate, appropriate memory usage of nodes, and the subsequent optimisation mainly focuses on code efficiency, algorithm, memory access, etc. (4) In terms of MPI communication, the communication efficiency of MPI in the GRAPES model improves by optimising the Collective Sync, Allreduce, and Wait algorithms of collective communication on the KUNPENG platform. (5) Through top-down analysis, it is found that the computing bottlenecks of the two models on the two platforms are mainly concentrated in the back-end CPU bottleneck and the back-end memory subsystem bottleneck. Thanks to the optimisation of multi-memory channels and the Bisheng compiler, the memory access efficiency, branch prediction rate, and cache hit rate of the GRAPES model on the KUNPENG platform are higher than those on the X86 platform. In addition, from the perspective of memory subsystem bottleneck information, TLB Miss and L1/L2 Miss are generally low, the memory access efficiency is high, and the memory access optimisation space is limited. From the perspective of instruction distribution information, the proportion of memory read and shaping instructions is relatively high, and there are certain floating-point instructions, which reflect the high memory bandwidth advantage of the KUNPENG architecture. In addition, the vectorisation instruction is not high, so vectorisation optimisation is considered. (6) From the analysis of hotspots, the GRAPES model is optimised by the GCR algorithm, the collective communication hotspots represented by uct and ucg, the mathematical functions represented by expf and powf, and the hot functions such as malloc memory operations are also optimised on the KUNPENG platform.
The GRAPES_MESO and WRF models are used to analyse the computational characteristics of numerical models on the KUNPENG platform, and are compared with the Intel (X86) platform to explore the improvement space of numerical models in resource utilisation, computational bottlenecks, hotspot functions, and other aspects on the KUNPENG platform. The results indicate that: (1) After adaptation, both models obtain consistent results on the domestic KUNPENG platform as on the X86 platform. (2) Both models exhibit good parallel scalability on both X86 and KUNPENG platforms. When using the same number of processes, the computing efficiency of the KUNPENG platform is 65% to 90% of that of the X86 platform. However, when using the same number of nodes, the computing efficiency of the KUNPENG platform exceeds that of the X86 platform by 22% to 45%. (3) In terms of hardware resource utilisation, the two models consume the most time in computing, followed by communication, and finally IO. The models have a higher CPU usage rate, appropriate memory usage of nodes, and the subsequent optimisation mainly focuses on code efficiency, algorithm, memory access, etc. (4) In terms of MPI communication, the communication efficiency of MPI in the GRAPES model improves by optimising the Collective Sync, Allreduce, and Wait algorithms of collective communication on the KUNPENG platform. (5) Through top-down analysis, it is found that the computing bottlenecks of the two models on the two platforms are mainly concentrated in the back-end CPU bottleneck and the back-end memory subsystem bottleneck. Thanks to the optimisation of multi-memory channels and the Bisheng compiler, the memory access efficiency, branch prediction rate, and cache hit rate of the GRAPES model on the KUNPENG platform are higher than those on the X86 platform. In addition, from the perspective of memory subsystem bottleneck information, TLB Miss and L1/L2 Miss are generally low, the memory access efficiency is high, and the memory access optimisation space is limited. From the perspective of instruction distribution information, the proportion of memory read and shaping instructions is relatively high, and there are certain floating-point instructions, which reflect the high memory bandwidth advantage of the KUNPENG architecture. In addition, the vectorisation instruction is not high, so vectorisation optimisation is considered. (6) From the analysis of hotspots, the GRAPES model is optimised by the GCR algorithm, the collective communication hotspots represented by uct and ucg, the mathematical functions represented by expf and powf, and the hot functions such as malloc memory operations are also optimised on the KUNPENG platform.
2025, 53(3):362-377.
DOI: 10.19517/j.1671-6345.20240153
Abstract:
Revealing the features and disaster risks of typhoons impacting Xiamen holds significant scientific and practical value for understanding typhoon hazards and improving disaster risk prevention and mitigation. This study utilises the Northwestern Pacific Tropical Cyclone Best Track dataset produced by the China Meteorological Administration (CMA), daily ground observation data from the Xiamen Observatory (1953-2023), hourly precipitation data from the Xiamen Observatory (1980-2023), and hourly data from automatic weather stations across Xiamen (2016-2023). The analysis focuses on the characteristics of typhoon frequency, impact duration, intensity, genesis location, interannual variation, wind and precipitation patterns, and the hazard risks associated with typhoons that make landfall in or affect Xiamen over the past 71 years. The results indicate that Xiamen experiences a total of 259 typhoons over 71 years. The greafest annual occrurence freguency of 9 typhoons occurs in 1961 and 1978, with active typhoon activity during the 1970s to 1990s. Typhoons affect Xiamen from April to December, with nearly 80% occurring between July and September, peaking in August. The frequency of typhoons impacting Xiamen is influenced by multiple factors, including the spatial configuration of sea surface temperature anomalies, variations in the phases of the Pacific Decadal Oscillation (PDO) and El Nio-Southern Oscillation (ENSO), and the patterns of the Western Pacific Subtropical High. Typhoons are less frequent during ENSO developing years and more frequent during ENSO decay years and weak in La Nia years. Nearly 30% of typhoons impacting Xiamen reach super typhoon intensity, showing significant increasing variability since the 1990s. The genesis of typhoons affecting Xiamen is concentrated in the Philippine Sea and the northeastern South China Sea. Notably, the annual average genesis location of typhoons since the 1990s exhibits a significant westward and northward migration. Among 44 typhoons that cause over 100 mm of rainfall in 24 hours, 31 are typhoons that make landfall in Xiamen or follow a southern trajectory, with the extreme precipitation of 509.5 mm caused by Typhoon Tasha (No. 9009). The four direct landfall typhoons bring wind speeds exceeding 41.5 m·s-1, whereas typhoons passing through Taiwan before affecting Xiamen result in weaker wind speeds below 32.7 m·s-1 in contrast. The maximum wind speed reaching 60.0 m·s-1 is recorded during Typhoon Iris (No. 5908). Different typhoons exhibit significant variations in wind, rain, and comprehensive hazard indices. Super Typhoon Meranti (No. 1614) ranks the highest in comprehensive risk. Typhoon Doksuri (No. 2305) and Typhoon Haikui (No. 2311) also cause severe disasters. Doksuri poses high wind and rain risks, while Haikui primarily presents a high rain risk, characterised by a typical non-uniform spatial distribution. These findings provide a scientific basis for enhancing Xiamen’s resilience to extreme weather and climate-related disasters, as well as for informing urban planning, production activities, and ensuring public safety.
Revealing the features and disaster risks of typhoons impacting Xiamen holds significant scientific and practical value for understanding typhoon hazards and improving disaster risk prevention and mitigation. This study utilises the Northwestern Pacific Tropical Cyclone Best Track dataset produced by the China Meteorological Administration (CMA), daily ground observation data from the Xiamen Observatory (1953-2023), hourly precipitation data from the Xiamen Observatory (1980-2023), and hourly data from automatic weather stations across Xiamen (2016-2023). The analysis focuses on the characteristics of typhoon frequency, impact duration, intensity, genesis location, interannual variation, wind and precipitation patterns, and the hazard risks associated with typhoons that make landfall in or affect Xiamen over the past 71 years. The results indicate that Xiamen experiences a total of 259 typhoons over 71 years. The greafest annual occrurence freguency of 9 typhoons occurs in 1961 and 1978, with active typhoon activity during the 1970s to 1990s. Typhoons affect Xiamen from April to December, with nearly 80% occurring between July and September, peaking in August. The frequency of typhoons impacting Xiamen is influenced by multiple factors, including the spatial configuration of sea surface temperature anomalies, variations in the phases of the Pacific Decadal Oscillation (PDO) and El Nio-Southern Oscillation (ENSO), and the patterns of the Western Pacific Subtropical High. Typhoons are less frequent during ENSO developing years and more frequent during ENSO decay years and weak in La Nia years. Nearly 30% of typhoons impacting Xiamen reach super typhoon intensity, showing significant increasing variability since the 1990s. The genesis of typhoons affecting Xiamen is concentrated in the Philippine Sea and the northeastern South China Sea. Notably, the annual average genesis location of typhoons since the 1990s exhibits a significant westward and northward migration. Among 44 typhoons that cause over 100 mm of rainfall in 24 hours, 31 are typhoons that make landfall in Xiamen or follow a southern trajectory, with the extreme precipitation of 509.5 mm caused by Typhoon Tasha (No. 9009). The four direct landfall typhoons bring wind speeds exceeding 41.5 m·s-1, whereas typhoons passing through Taiwan before affecting Xiamen result in weaker wind speeds below 32.7 m·s-1 in contrast. The maximum wind speed reaching 60.0 m·s-1 is recorded during Typhoon Iris (No. 5908). Different typhoons exhibit significant variations in wind, rain, and comprehensive hazard indices. Super Typhoon Meranti (No. 1614) ranks the highest in comprehensive risk. Typhoon Doksuri (No. 2305) and Typhoon Haikui (No. 2311) also cause severe disasters. Doksuri poses high wind and rain risks, while Haikui primarily presents a high rain risk, characterised by a typical non-uniform spatial distribution. These findings provide a scientific basis for enhancing Xiamen’s resilience to extreme weather and climate-related disasters, as well as for informing urban planning, production activities, and ensuring public safety.
2025, 53(3):378-390.
DOI: 10.19517/j.1671-6345.20240207
Abstract:
From 26 to 28 July 2023, the Sichuan Basin experienced a prolonged and widespread heavy rainfall event. This process, characterised as the most intense rainfall since the onset of the flood season 2023 in the basin, led to significant localised flooding disasters. To analyse the characteristics and evolution of the southwest vortex responsible for the heavy rainfall in the Sichuan Basin, the study utilises ERA5 reanalysis data, GPM surface precipitation data, and FY-2G cloud-top equivalent blackbody temperature data, applying synoptic diagnostic methods and the vorticity budget equation. The conclusions are as follows: (1) The southwest vortex belonged to the non-moving-out type, and in addition to being induced and coupled with the plateau vortex, the typhoon also promoted the development of the southwest vortex by transporting vapour over a long distance and changing the wind pressure field structure. (2) The mesoscale system activity experienced five stages: mesoscale convergence disturbance, southwest vortex generation and development, intensity weakening, redevelopment and intensification, and weakening filling. The scope and intensity of precipitation during the redevelopment stage were greater than those during the initial development stage. (3) In the redevelopment stage, the southwest vortex system became deeper, the height of the positive vorticity column increased to 400 hPa, and the range expanded along the height to the northwest, with the feature of “convergence at low level and divergence at high level” significantly enhanced. (4) The water vapour during the initial development period was mainly contributed by the humid airflow from the Bay of Bengal. During the redevelopment period, it was transported westward from the South China Sea to the Sichuan Basin by the typhoon, and the southwest vortex region maintained a high humidity state. The asymmetry of the warm wet structure was strengthened, and the baroclinicity was strong. The degree of convergence and divergence of water vapour corresponded to the location of the southwest vortex and precipitation intensity. (5) The lower-level positive vorticity budget of the two development stages was mainly contributed by the stretching term, the vertical transport term, and the twisting term.
From 26 to 28 July 2023, the Sichuan Basin experienced a prolonged and widespread heavy rainfall event. This process, characterised as the most intense rainfall since the onset of the flood season 2023 in the basin, led to significant localised flooding disasters. To analyse the characteristics and evolution of the southwest vortex responsible for the heavy rainfall in the Sichuan Basin, the study utilises ERA5 reanalysis data, GPM surface precipitation data, and FY-2G cloud-top equivalent blackbody temperature data, applying synoptic diagnostic methods and the vorticity budget equation. The conclusions are as follows: (1) The southwest vortex belonged to the non-moving-out type, and in addition to being induced and coupled with the plateau vortex, the typhoon also promoted the development of the southwest vortex by transporting vapour over a long distance and changing the wind pressure field structure. (2) The mesoscale system activity experienced five stages: mesoscale convergence disturbance, southwest vortex generation and development, intensity weakening, redevelopment and intensification, and weakening filling. The scope and intensity of precipitation during the redevelopment stage were greater than those during the initial development stage. (3) In the redevelopment stage, the southwest vortex system became deeper, the height of the positive vorticity column increased to 400 hPa, and the range expanded along the height to the northwest, with the feature of “convergence at low level and divergence at high level” significantly enhanced. (4) The water vapour during the initial development period was mainly contributed by the humid airflow from the Bay of Bengal. During the redevelopment period, it was transported westward from the South China Sea to the Sichuan Basin by the typhoon, and the southwest vortex region maintained a high humidity state. The asymmetry of the warm wet structure was strengthened, and the baroclinicity was strong. The degree of convergence and divergence of water vapour corresponded to the location of the southwest vortex and precipitation intensity. (5) The lower-level positive vorticity budget of the two development stages was mainly contributed by the stretching term, the vertical transport term, and the twisting term.
2025, 53(3):391-404.
DOI: 10.19517/j.1671-6345.20240122
Abstract:
Using multi-source observation data and ERA5 reanalysis data, a rainstorm that triggers a record-breaking flood in Qijiang Basin (QB) from June 19 to 22, 2020, is analysed. The nocturnal enhancement mechanism of precipitation brought by Southwest Vortex is hereafter studied. The results show that: (1) The rainstorm, exhibiting significant daily variation, intensified during the night and early morning. The whole process was divided into three stages. At the third stage, the MCSs showed lower Blackbody Brightness Temperature (TBB), moved and propagated more slowly, and resulted in stronger precipitation and convection with longer duration. (2) Under the background of a weak trough in the westerly to the north of the Western Pacific Subtropical High, the rainstorm was caused by a strong Southwest Vortex, a stable low-level jet, and a convergence line on the surface. At the stage of convection initiation, an unstable environment with high temperature and humidity was formed near the convergence line. Meanwhile, the northerly wind on the surface was forced to lift by terrain, then joined the updraft of basin-plateau secondary vertical circulation, and later triggered convection. (3) The low-level ageostrophic wind above Sichuan Basin (SB) and northern Yunnan-Guizhou Plateau (YGP) rotated clockwise every day, both turned southerly and strengthened at night, and was stronger above YGP than above SB. The nocturnal low-level wind, being sub-geostrophic above SB and super-geostrophic above YGP, caused warm shear and flow convergence. Additionally, the water vapour flux transported by ageostrophic wind was negative during the day and positive at night, while the water vapour flux transported by geostrophic wind remained positive all day, resulting in a significant positive increase in the water vapour flux transported by actual wind at night. The above daily variations were conducive to water vapour accumulation and flow convergence, which eventually led to the intensification of precipitation. (4) The advection and ageostrophic terms in the momentum balance equation became positive or increased at night, and were greater above YGP than above SB. The horizontal wind on YGP therefore intensified, wind speed gradient and convergence were formed as a result. The ageostrophic effect played an important role in the nocturnal enhancement mechanism of precipitation.
Using multi-source observation data and ERA5 reanalysis data, a rainstorm that triggers a record-breaking flood in Qijiang Basin (QB) from June 19 to 22, 2020, is analysed. The nocturnal enhancement mechanism of precipitation brought by Southwest Vortex is hereafter studied. The results show that: (1) The rainstorm, exhibiting significant daily variation, intensified during the night and early morning. The whole process was divided into three stages. At the third stage, the MCSs showed lower Blackbody Brightness Temperature (TBB), moved and propagated more slowly, and resulted in stronger precipitation and convection with longer duration. (2) Under the background of a weak trough in the westerly to the north of the Western Pacific Subtropical High, the rainstorm was caused by a strong Southwest Vortex, a stable low-level jet, and a convergence line on the surface. At the stage of convection initiation, an unstable environment with high temperature and humidity was formed near the convergence line. Meanwhile, the northerly wind on the surface was forced to lift by terrain, then joined the updraft of basin-plateau secondary vertical circulation, and later triggered convection. (3) The low-level ageostrophic wind above Sichuan Basin (SB) and northern Yunnan-Guizhou Plateau (YGP) rotated clockwise every day, both turned southerly and strengthened at night, and was stronger above YGP than above SB. The nocturnal low-level wind, being sub-geostrophic above SB and super-geostrophic above YGP, caused warm shear and flow convergence. Additionally, the water vapour flux transported by ageostrophic wind was negative during the day and positive at night, while the water vapour flux transported by geostrophic wind remained positive all day, resulting in a significant positive increase in the water vapour flux transported by actual wind at night. The above daily variations were conducive to water vapour accumulation and flow convergence, which eventually led to the intensification of precipitation. (4) The advection and ageostrophic terms in the momentum balance equation became positive or increased at night, and were greater above YGP than above SB. The horizontal wind on YGP therefore intensified, wind speed gradient and convergence were formed as a result. The ageostrophic effect played an important role in the nocturnal enhancement mechanism of precipitation.
2025, 53(3):405-416.
DOI: 10.19517/j.1671-6345.20240150
Abstract:
Using multi-source observation and reanalysis data, the rare ice pellet weather in southern Jiangsu from February 22 to 24, 2024 is analysed, and ice grains, freezing rain, and snow are also compared. The results show that the strong southwest warm wet jet, stably maintained at 700 hPa, provided favourable power, water vapour, and temperature stratification conditions for the formation of ice pellet weather. The development of middle warm wet airflow exhibited significant extremes. The 700 hPa height field in southern Jiangsu was 10-30 gpm higher than the annual average climate (standard deviation multiple of 0.5σ-1σ), and the southwest wind was stronger than the annual average climate by 10 m·s-1, with a 4-5 ℃ higher temperature (standard deviation multiple of 1.5σ). The middle abnormal warming was one of the important conditions for the rare long-term ice pellet weather in southern Jiangsu. The inversion layer was stable, located between 939.8 hPa and 729.9 hPa, with an average thickness of 1540 metres and an average intensity of 10.2 ℃. The stably maintained middle warm layer and low cold layer provided favourable temperature conditions for the occurrence of ice grain weather: the average thickness of the warm layer was 709 metres, the height was between 779.3 hPa and 683 hPa, and the temperature of the warm layer was less than or equal to 2.9 ℃. The cold layer was basically located below 779.3 hPa, and the lowest temperature was between -8.7 ℃ and -7.6 ℃, which was conducive to the ice particles partially melting in the warm layer and being frozen again during the descent process, ultimately falling to the ground as ice particles. The radar characteristics of the three phases (ice particles, freezing rain, and snow) were different, which had certain indicator significance for the identification of precipitation phases and the forecast of phase approaches: the reflectivity factor of snow was below 30 dBz, while the reflectivity factors of ice particles and freezing rain were greater, generally below 45 dBz; the differential reflectance factor (ZDR) was ice particles > freezing rain > snow, and the maximum ZDR of ice particle was 4 dB. From the correlation coefficient (CC), ice particles had the smallest values, while freezing rain and snow were close to 1.
Using multi-source observation and reanalysis data, the rare ice pellet weather in southern Jiangsu from February 22 to 24, 2024 is analysed, and ice grains, freezing rain, and snow are also compared. The results show that the strong southwest warm wet jet, stably maintained at 700 hPa, provided favourable power, water vapour, and temperature stratification conditions for the formation of ice pellet weather. The development of middle warm wet airflow exhibited significant extremes. The 700 hPa height field in southern Jiangsu was 10-30 gpm higher than the annual average climate (standard deviation multiple of 0.5σ-1σ), and the southwest wind was stronger than the annual average climate by 10 m·s-1, with a 4-5 ℃ higher temperature (standard deviation multiple of 1.5σ). The middle abnormal warming was one of the important conditions for the rare long-term ice pellet weather in southern Jiangsu. The inversion layer was stable, located between 939.8 hPa and 729.9 hPa, with an average thickness of 1540 metres and an average intensity of 10.2 ℃. The stably maintained middle warm layer and low cold layer provided favourable temperature conditions for the occurrence of ice grain weather: the average thickness of the warm layer was 709 metres, the height was between 779.3 hPa and 683 hPa, and the temperature of the warm layer was less than or equal to 2.9 ℃. The cold layer was basically located below 779.3 hPa, and the lowest temperature was between -8.7 ℃ and -7.6 ℃, which was conducive to the ice particles partially melting in the warm layer and being frozen again during the descent process, ultimately falling to the ground as ice particles. The radar characteristics of the three phases (ice particles, freezing rain, and snow) were different, which had certain indicator significance for the identification of precipitation phases and the forecast of phase approaches: the reflectivity factor of snow was below 30 dBz, while the reflectivity factors of ice particles and freezing rain were greater, generally below 45 dBz; the differential reflectance factor (ZDR) was ice particles > freezing rain > snow, and the maximum ZDR of ice particle was 4 dB. From the correlation coefficient (CC), ice particles had the smallest values, while freezing rain and snow were close to 1.
2025, 53(3):417-426.
DOI: 10.19517/j.1671-6345.20240218
Abstract:
Near-surface air temperature (Ta) at high spatiotemporal resolution is of great significance for meteorology, hydrology, agroecology, production and life, and disaster prevention and reduction. The heterogeneity of Ta in mountainous areas is strong, and there are few stations. How to obtain high spatial resolution forecast Ta under complex mountainous terrain remains a challenge in operational applications and scientific fields. The Global Forecast System (GFS) provides forecast Ta products with global coverage, but its low spatial resolution is not applicable to small-scale areas, especially mountainous areas with complex terrain. Currently, downscaling methods are widely used, which transform large-scale Ta into small-scale Ta. Taking Chongqing with complex terrain as a test area, this study uses elevation data with two spatial resolutions (0.25° and 200 m), latitude and longitude, temporal information, and GFS forecast Ta (0.25°) to construct a downscaling model of GFS forecast Ta for Chongqing based on the statistical downscaling method of neural networks. Validated using Chongqing station data in 2020, the root-mean-square error (RMSE) between the downscaled Ta and station Ta reduces from 2.55 ℃ to 1.65 ℃, the correlation coefficient (R) improves from 0.959 to 0.98, and the absolute value of the mean bias (Bias) reduces from 1 ℃ to 0.02 ℃. To assess the spatiotemporal stability of the model, this paper analyses the model errors by four aspects: month, day, different moments, and different forecast timescales. The results show that the downscaled Ta performance is more stable, with the 12-month RMSE decreasing from 2.22-3.15 ℃ to 1.37-1.86 ℃, and the absolute value of Bias decreasing from 0.10-2.24 ℃ to 0.01-0.29 ℃. The improvement is more obvious in the hot season (July to October). Comparing the time series of modelled Ta, GFS Ta, and station Ta at the three sites, the downscaled Ta aligns better with the station Ta, and the RMSE reduces from 1.63-2.54 ℃ to 1.52-1.87 ℃. Comparing the model performance at different moments, the downscaled Ta has smaller RMSE and Bias, and the model significantly improves accuracy even at moments when the GFS Ta errors are larger (03:00 and 09:00). Comparing the two forecast time scales, there is no significant difference in model performance after downscaling. In addition, the error spatial analysis results show that the station locations throughout Chongqing perform better after downscaling, and the effect is obvious at some stations, with the RMSE decreasing from 3.61 ℃ to 1.70 ℃, the R improving from 0.965 to 0.978, and the Bias reducing from -2.95 ℃ to -0.25 ℃. Finally, the model applies to GFS 3 h forecast Ta (0.25°×0.25°) to obtain small-scale Ta (200 m×200 m). The effect of Ta spatial distribution before and after downscaling is demonstrated for four moments (January 1, 03:00; April 1, 03:00; July 1, 03:00; and October 1, 03:00, 2022) in Chongqing. In contrast, the spatial resolution of GFS Ta before downscaling is low and shows an obvious sense of fuzzy patches, while the spatial resolution of Ta after downscaling is significantly improved and shows richer Ta spatial details, especially in high-altitude mountainous areas.
Near-surface air temperature (Ta
2025, 53(3):427-437.
DOI: 10.19517/j.1671-6345.20240117
Abstract:
Based on the summer daily mean, maximum, and minimum temperature data from 72 national surface meteorological stations in Hebei Province from 1961 to 2023, a comparative analysis examines the distribution characteristics of summer mean temperature, summer mean maximum and minimum temperatures, as well as the diurnal temperature range, across the time periods and regions with different levels of urbanisation to explore the potential impact of urbanisation on summer temperature changes in Hebei Province. The results indicate that: compared to the previous 30 years (from 1961 to 1990), the probability density distribution of summer mean temperature, summer mean maximum and minimum temperatures in Hebei shifts towards the higher temperature side in the latter 30 years (from 1994 to 2023), which is particularly pronounced in the summer mean minimum temperature. From 1961 to 2023, the contribution rate of urbanisation to temperature mostly exceeds 30%, according to station comparisons in regions with different levels of urbanisation. Additionally, the trend of summer temperature changes in Hebei Province significantly intensifies in both the rate and the scope in the latter 30 years, while the areas with relatively strong temperature increases are primarily concentrated in Langfang, Tangshan, and central and southern Hebei, which are regions that are economically developed and highly urbanised. The decreasing trend of the diurnal temperature range is alleviated in the central and southern parts of Hebei Province. The levels of urbanisation affect the distribution characteristics of site temperatures, while in areas with higher and medium levels of urbanisation, the increase in temperature at selected urban station sites is significantly greater compared to suburban stations. Furthermore, the warming is mostly concentrated near cities, and the probability distribution of temperature elements at urban stations, especially the summer mean minimum temperature, shifts more evidently towards higher temperatures compared to suburban stations, with the steepness increasing, resulting in a shift of the diurnal temperature range towards lower temperatures. In areas with relatively lower levels of urbanisation, the increase and the shift of probability density distribution towards higher temperatures at urban stations compared to suburban stations become more pronounced in summer mean maximum temperature, resulting in an increase in the diurnal temperature range.
Based on the summer daily mean, maximum, and minimum temperature data from 72 national surface meteorological stations in Hebei Province from 1961 to 2023, a comparative analysis examines the distribution characteristics of summer mean temperature, summer mean maximum and minimum temperatures, as well as the diurnal temperature range, across the time periods and regions with different levels of urbanisation to explore the potential impact of urbanisation on summer temperature changes in Hebei Province. The results indicate that: compared to the previous 30 years (from 1961 to 1990), the probability density distribution of summer mean temperature, summer mean maximum and minimum temperatures in Hebei shifts towards the higher temperature side in the latter 30 years (from 1994 to 2023), which is particularly pronounced in the summer mean minimum temperature. From 1961 to 2023, the contribution rate of urbanisation to temperature mostly exceeds 30%, according to station comparisons in regions with different levels of urbanisation. Additionally, the trend of summer temperature changes in Hebei Province significantly intensifies in both the rate and the scope in the latter 30 years, while the areas with relatively strong temperature increases are primarily concentrated in Langfang, Tangshan, and central and southern Hebei, which are regions that are economically developed and highly urbanised. The decreasing trend of the diurnal temperature range is alleviated in the central and southern parts of Hebei Province. The levels of urbanisation affect the distribution characteristics of site temperatures, while in areas with higher and medium levels of urbanisation, the increase in temperature at selected urban station sites is significantly greater compared to suburban stations. Furthermore, the warming is mostly concentrated near cities, and the probability distribution of temperature elements at urban stations, especially the summer mean minimum temperature, shifts more evidently towards higher temperatures compared to suburban stations, with the steepness increasing, resulting in a shift of the diurnal temperature range towards lower temperatures. In areas with relatively lower levels of urbanisation, the increase and the shift of probability density distribution towards higher temperatures at urban stations compared to suburban stations become more pronounced in summer mean maximum temperature, resulting in an increase in the diurnal temperature range.
2025, 53(3):438-447.
DOI: 10.19517/j.1671-6345.20240185
Abstract:
This paper presents a detailed analysis of cloud-to-ground (CG) lightning data collected by the Shaanxi VLF/LF lightning location system over a period of seven years, from 2017 to 2023. The research begins by constructing a CG lightning kernel density surface, which is derived from the collected data and implemented using intensity weighting through a Geographic Information System (GIS) kernel density field model. This model facilitates the visualisation and quantification of lightning activity across the Shaanxi region, thus providing a robust foundation for subsequent analyses. Upon establishing the kernel density surface, the study utilises a hotspot detection model to identify and categorise regions with high lightning density. This crucial step pinpoints specific areas where lightning activity is exceptionally intense, thereby offering vital data for risk assessment and mitigation strategies. The analysis explores the relationships between the distribution of CG lightning kernel density, its identified hotspots, and various environmental factors such as topography and vegetation coverage, both of which significantly influence lightning activity. Key insights revealed by the findings include the effectiveness of the GIS kernel density field model and the hotspot detection model in accurately identifying regions with intense lightning activity. This enhanced understanding of the spatial distribution characteristics of CG lightning is essential for predicting and managing lightning-related hazards. Additionally, the research identifies significant spatiotemporal variations in CG lightning activity within the Shaanxi region. The analysis shows that lightning activity is most frequent and intense during the summer months, followed by spring and autumn, with winter experiencing the least activity. Spatially, the lightning density is higher in the northern and southern parts of Shaanxi, while the central region shows relatively lower density. Further, the study examines the correlation between kernel density and altitude. A positive correlation is observed below 1 km in altitude, suggesting that lightning activity increases with altitude. Above 1 km, however, this trend reverses, with a decrease in kernel density as altitude increases. The research also investigates how topography and vegetation impact kernel density values, revealing that both factors significantly affect kernel density, with topography having a more pronounced impact. This indicates that variations in terrain play a crucial role in shaping the patterns of lightning activity. In conclusion, the study identifies the primary distribution areas for large and medium-large hotspots, predominantly located in grasslands and forest areas within mid-altitude loess ridges and mounds, as well as moderately undulating mountains. These findings are instrumental for targeting lightning protection measures and enhancing safety in these vulnerable areas. Overall, this paper significantly advances understanding of lightning activity in the Shaanxi region, providing valuable insights for future research and practical applications, thereby enriching the scientific community’s resources for better managing the risks associated with lightning.
This paper presents a detailed analysis of cloud-to-ground (CG) lightning data collected by the Shaanxi VLF/LF lightning location system over a period of seven years, from 2017 to 2023. The research begins by constructing a CG lightning kernel density surface, which is derived from the collected data and implemented using intensity weighting through a Geographic Information System (GIS) kernel density field model. This model facilitates the visualisation and quantification of lightning activity across the Shaanxi region, thus providing a robust foundation for subsequent analyses. Upon establishing the kernel density surface, the study utilises a hotspot detection model to identify and categorise regions with high lightning density. This crucial step pinpoints specific areas where lightning activity is exceptionally intense, thereby offering vital data for risk assessment and mitigation strategies. The analysis explores the relationships between the distribution of CG lightning kernel density, its identified hotspots, and various environmental factors such as topography and vegetation coverage, both of which significantly influence lightning activity. Key insights revealed by the findings include the effectiveness of the GIS kernel density field model and the hotspot detection model in accurately identifying regions with intense lightning activity. This enhanced understanding of the spatial distribution characteristics of CG lightning is essential for predicting and managing lightning-related hazards. Additionally, the research identifies significant spatiotemporal variations in CG lightning activity within the Shaanxi region. The analysis shows that lightning activity is most frequent and intense during the summer months, followed by spring and autumn, with winter experiencing the least activity. Spatially, the lightning density is higher in the northern and southern parts of Shaanxi, while the central region shows relatively lower density. Further, the study examines the correlation between kernel density and altitude. A positive correlation is observed below 1 km in altitude, suggesting that lightning activity increases with altitude. Above 1 km, however, this trend reverses, with a decrease in kernel density as altitude increases. The research also investigates how topography and vegetation impact kernel density values, revealing that both factors significantly affect kernel density, with topography having a more pronounced impact. This indicates that variations in terrain play a crucial role in shaping the patterns of lightning activity. In conclusion, the study identifies the primary distribution areas for large and medium-large hotspots, predominantly located in grasslands and forest areas within mid-altitude loess ridges and mounds, as well as moderately undulating mountains. These findings are instrumental for targeting lightning protection measures and enhancing safety in these vulnerable areas. Overall, this paper significantly advances understanding of lightning activity in the Shaanxi region, providing valuable insights for future research and practical applications, thereby enriching the scientific community’s resources for better managing the risks associated with lightning.
2025, 53(3):448-456.
DOI: 10.19517/j.1671-6345.20240156
Abstract:
On the basis of the natural disaster comprehensive risk census data, this paper refines and constructs the vulnerability index of cultural relics protection units facing rainstorm disasters and establishes the indicator system for rainstorm disaster risk assessment of cultural relics protection units by comprehensively considering the three elements of rainstorm disaster risk, disaster-conceiving environment sensitivity, and cultural relics vulnerability. The rainstorm disaster risk and environmental sensitivity indicators are selected from the rainstorm risk level obtained from the census, which includes the rainstorm risk and environmental sensitivity of the disaster-conceiving environment, in which the rainstorm disaster-causing factors include the rainstorm process precipitation, the maximum daily precipitation, the maximum hourly precipitation, and the duration of precipitation from 1978 to 2020. The environmental impact factors of the disaster-conceiving environment include the standard deviation of the elevation, elevation, and the density of the river network, etc. The vulnerability of the cultural relics protection units includes the importance, exposure, sensitivity, and susceptibility of cultural relics. The vulnerability of cultural relics protection units includes three aspects of importance, exposure, and susceptibility, which includes eight indicators: protection level, affiliated cultural relics, area/scale, pedestal/(underground palace), cultural relics type, material type, deformation damage, and historical disaster. The reference weights of the indicators at all levels are given after the experts’ argumentation on cultural relics, meteorology, and emergency response. Based on the indicator system, the storm disaster risk of national key cultural relics protection units in Jincheng, Shanxi Province, is assessed and verified, and in the assessment, the weight of storm danger accounts for 75%. The eight cultural relics protection units with high storm disaster risk levels are all located in areas with high storm danger, among which the Xiangyu Ancient Fortress, the ancient architectural complex of Guobi Village, and the city of Miakovi are all located along the Qin River. The Shuitong Cui Fujun Temple, the Yuhuang Temple, and the Qinglian Temple are located along the Dan River, while the Tashui River ruins and Zezhou Dai Temple are located on the banks of the Tashui River and the Yedi River, respectively. The cultural relics protection units with a higher risk level are located in areas with a higher risk of rainstorms and at the same time have relatively high vulnerability. The research results provide a certain reference for the storm disaster risk assessment and protection of cultural relics protection units and at the same time enhance the application scope of the results of the comprehensive natural disaster risk census.
On the basis of the natural disaster comprehensive risk census data, this paper refines and constructs the vulnerability index of cultural relics protection units facing rainstorm disasters and establishes the indicator system for rainstorm disaster risk assessment of cultural relics protection units by comprehensively considering the three elements of rainstorm disaster risk, disaster-conceiving environment sensitivity, and cultural relics vulnerability. The rainstorm disaster risk and environmental sensitivity indicators are selected from the rainstorm risk level obtained from the census, which includes the rainstorm risk and environmental sensitivity of the disaster-conceiving environment, in which the rainstorm disaster-causing factors include the rainstorm process precipitation, the maximum daily precipitation, the maximum hourly precipitation, and the duration of precipitation from 1978 to 2020. The environmental impact factors of the disaster-conceiving environment include the standard deviation of the elevation, elevation, and the density of the river network, etc. The vulnerability of the cultural relics protection units includes the importance, exposure, sensitivity, and susceptibility of cultural relics. The vulnerability of cultural relics protection units includes three aspects of importance, exposure, and susceptibility, which includes eight indicators: protection level, affiliated cultural relics, area/scale, pedestal/(underground palace), cultural relics type, material type, deformation damage, and historical disaster. The reference weights of the indicators at all levels are given after the experts’ argumentation on cultural relics, meteorology, and emergency response. Based on the indicator system, the storm disaster risk of national key cultural relics protection units in Jincheng, Shanxi Province, is assessed and verified, and in the assessment, the weight of storm danger accounts for 75%. The eight cultural relics protection units with high storm disaster risk levels are all located in areas with high storm danger, among which the Xiangyu Ancient Fortress, the ancient architectural complex of Guobi Village, and the city of Miakovi are all located along the Qin River. The Shuitong Cui Fujun Temple, the Yuhuang Temple, and the Qinglian Temple are located along the Dan River, while the Tashui River ruins and Zezhou Dai Temple are located on the banks of the Tashui River and the Yedi River, respectively. The cultural relics protection units with a higher risk level are located in areas with a higher risk of rainstorms and at the same time have relatively high vulnerability. The research results provide a certain reference for the storm disaster risk assessment and protection of cultural relics protection units and at the same time enhance the application scope of the results of the comprehensive natural disaster risk census.
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