Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.There...Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.Therefore,it is necessary to establish thunderstorm wind gust identification techniques based on multisource high-resolution observations.This paper introduces a new algorithm,called thunderstorm wind gust identification network(TGNet).It leverages multimodal feature fusion to fuse the temporal and spatial features of thunderstorm wind gust events.The shapelet transform is first used to extract the temporal features of wind speeds from automatic weather stations,which is aimed at distinguishing thunderstorm wind gusts from those caused by synoptic-scale systems or typhoons.Then,the encoder,structured upon the U-shaped network(U-Net)and incorporating recurrent residual convolutional blocks(R2U-Net),is employed to extract the corresponding spatial convective characteristics of satellite,radar,and lightning observations.Finally,by using the multimodal deep fusion module based on multi-head cross-attention,the temporal features of wind speed at each automatic weather station are incorporated into the spatial features to obtain 10-minutely classification of thunderstorm wind gusts.TGNet products have high accuracy,with a critical success index reaching 0.77.Compared with those of U-Net and R2U-Net,the false alarm rate of TGNet products decreases by 31.28%and 24.15%,respectively.The new algorithm provides grid products of thunderstorm wind gusts with a spatial resolution of 0.01°,updated every 10minutes.The results are finer and more accurate,thereby helping to improve the accuracy of operational warnings for thunderstorm wind gusts.展开更多
Thunderstorm detection based on the Atmospheric Electric Field(AEF)has evolved from time-domain models to space-domain models.It is especially important to evaluate and determine the particularly Weather Attribute(WA)...Thunderstorm detection based on the Atmospheric Electric Field(AEF)has evolved from time-domain models to space-domain models.It is especially important to evaluate and determine the particularly Weather Attribute(WA),which is directly related to the detection reliability and authenticity.In this paper,a strategy is proposed to integrate three currently competitive WA's evaluation methods.First,a conventional evaluation method based on AEF statistical indicators is selected.Subsequent evaluation approaches include competing AEF-based predicted value intervals,and AEF classification based on fuzzy c-means.Different AEF attributes contribute to a more accurate AEF classification to different degrees.The resulting dynamic weighting applied to these attributes improves the classification accuracy.Each evaluation method is applied to evaluate the WA of a particular AEF,to obtain the corresponding evaluation score.The integration in the proposed strategy takes the form of a score accumulation.Different cumulative score levels correspond to different final WA results.Thunderstorm imaging is performed to visualize thunderstorm activities using those AEFs already evaluated to exhibit thunderstorm attributes.Empirical results confirm that the proposed strategy effectively and reliably images thunderstorms,with a 100%accuracy of WA evaluation.This is the first study to design an integrated thunderstorm detection strategy from a new perspective of WA evaluation,which provides promising solutions for a more reliable and flexible thunderstorm detection.展开更多
Thunderstorm gusts are a common form of severe convective weather in the warm season in North China,and it is of great importance to correctly forecast them.At present,the forecasting of thunderstorm gusts is mainly b...Thunderstorm gusts are a common form of severe convective weather in the warm season in North China,and it is of great importance to correctly forecast them.At present,the forecasting of thunderstorm gusts is mainly based on traditional subjective methods,which fails to achieve high-resolution and high-frequency gridded forecasts based on multiple observation sources.In this paper,we propose a deep learning method called Thunderstorm Gusts TransU-net(TGTransUnet)to forecast thunderstorm gusts in North China based on multi-source gridded product data from the Institute of Urban Meteorology(IUM)with a lead time of 1 to 6 h.To determine the specific range of thunderstorm gusts,we combine three meteorological variables:radar reflectivity factor,lightning location,and 1-h maximum instantaneous wind speed from automatic weather stations(AWSs),and obtain a reasonable ground truth of thunderstorm gusts.Then,we transform the forecasting problem into an image-to-image problem in deep learning under the TG-TransUnet architecture,which is based on convolutional neural networks and a transformer.The analysis and forecast data of the enriched multi-source gridded comprehensive forecasting system for the period 2021–23 are then used as training,validation,and testing datasets.Finally,the performance of TG-TransUnet is compared with other methods.The results show that TG-TransUnet has the best prediction results at 1–6 h.The IUM is currently using this model to support the forecasting of thunderstorm gusts in North China.展开更多
In this study,we examine the dynamics and microphysical structures of a deep compact thunderstorm event driving cloud-to-ground(CG)lightning over the Nanjing area located within the Yangtze-Huai River Basin(YHRB)durin...In this study,we examine the dynamics and microphysical structures of a deep compact thunderstorm event driving cloud-to-ground(CG)lightning over the Nanjing area located within the Yangtze-Huai River Basin(YHRB)during the monsoon break period.The microphysical structures combined with the dynamics in the glaciated,mixed-phase,and warm-phase layers during the formative,intensifying,and mature stages of the thunderstorm were first investigated using C-band polarimetric radar and CG lightning observations.The results show that the mature phase of the thunderstorm produced a local cold pool,which collided with a southerly warm wind,resulting in a strong updraft.The strong updraft favored the lifting of raindrops to the mixed-phase region to form abundant supercooled liquid water and graupel.From the formative stage to the developing stage and further to the mature stage,increased ZH-and reduced ZDR-values within the mixed-phase region are found,especially within the strong updraft region(>5 m s^(-1)).This phenomenon suggests that supercooled raindrops evolved into large hydrometeors(graupel and hail),indicative of a strong riming process.The signatures within this region are consistent with a favorable environment for thunderstorm electrification and generate the most frequent lightning during the thunderstorm life cycle.展开更多
This paper presents an analysis of spatial and temporal variation of rainfall and thunderstorm occurrence over Ken-ya from January 1987 to December 2017.The meteorological data used were obtained from the Kenya Meteor...This paper presents an analysis of spatial and temporal variation of rainfall and thunderstorm occurrence over Ken-ya from January 1987 to December 2017.The meteorological data used were obtained from the Kenya Meteorological Department(KMD)for the same period.This included the monthly thunderstorm occurrences and rainfall amounts of 26 synoptic stations across the country.The characteristics of monthly,seasonal and annual frequency results were presented on spatial maps while Time series graphs were used to display the pattern for annual cycle,seasonal varia-tions and the inter-annual variability of rainfall amounts and thunderstorm occurrences.A well-known non-parametric statistical method Mann Kendall(MK)trend test was used to determine and compare the statistical significance of the trends.Thunderstorm frequencies over the Eastern,Central and Coast regions of the country showed a bimodal pattern with high frequencies coinciding with March-April-May(MAM)and October-November-December(OND)rainy sea-sons.Very few thunderstorm days were detected over June-July-August(JJA)season.The areas to the western part of the country,near Lake Victoria,had the highest thunderstorm frequencies in the country over the three seasons:MAM,JJAS and OND.The annual frequency showed a quasi-unimodal pattern.These places near Lake Victoria showed sig-nificantly increasing thunderstorm trends during the MAM and OND seasons irrespective of the rainfall trends.This shows the effects of Lake Victoria over these areas,and it acts as a continuous source of moisture for thunderstorm for-mation.However,most stations across the country showed a reducing trend of thunderstorm frequency during MAM and JJA seasons.The importance of these findings is that they could support various policy makers,and users of cli-mate information,especially in the agriculture and aviation industries.展开更多
为了进一步认识上升气流对雷暴云内复杂电荷结构特征的影响,利用加入起放电参数化方案的WRF模式对DC3试验中2012年6月6日一次出现反极性电荷结构的强雷暴过程进行模拟。结果表明,起电区对应强回波区,主要发生在上升气流区中心云水混合...为了进一步认识上升气流对雷暴云内复杂电荷结构特征的影响,利用加入起放电参数化方案的WRF模式对DC3试验中2012年6月6日一次出现反极性电荷结构的强雷暴过程进行模拟。结果表明,起电区对应强回波区,主要发生在上升气流区中心云水混合比大于0.2 g kg^(-1)的冰水混合区,非感应起电机制主导着雷暴云内的起电过程。上升气流区外围区域存在可观的电荷,主要是由气流将起电区域的荷电粒子向后水平输送形成的。同类粒子带电极性在较大范围内变化少,但由于各类粒子的含量和荷电量不同,导致净电荷密度分布呈现较复杂的结构。达到一定强度的上升气流可以破坏电荷区的连续性,导致对流区出现高密度的、正负极性交错分布的、范围更小的电荷区。层云区由于没有上升气流,荷电粒子主要源自上升气流区的水平输送,所以其电荷区分布较连续且范围较大,但电荷密度相对弱。处于不同生命期的单体由于上升气流强度和倾斜程度不同,单体间的水成物粒子分布特征会存在一定差异,使得反转温度和起电率出现较大不同,因此单体合并时上升气流区之间的电荷区更破碎,电荷结构更复杂。展开更多
Based on the radar data and lightning position indicator data of strong thunderstorm weather which happened in Fuxin on July 8,2007,the relationship between the lightning activity and the radar echo was analyzed.The r...Based on the radar data and lightning position indicator data of strong thunderstorm weather which happened in Fuxin on July 8,2007,the relationship between the lightning activity and the radar echo was analyzed.The results showed that Fuxin area located in the cross position of T-shaped trough and was affected by the cold air which continuously glided down.The corresponding warm front on the ground advanced southward and arrived here.It was the weather background of this thunderstorm weather.The position variation of lightning occurrence was closely related to the strong echo movement of squall line,and the velocity echo clearly reflected and predicted the movement tendency of the radar echo.展开更多
The first thunderstorm weather appeared in southern Shenyang on May 2,2010 and did not bring about severe lightning disaster for Shenyang region,but forecast service had poor effect without forecasting thunderstorm we...The first thunderstorm weather appeared in southern Shenyang on May 2,2010 and did not bring about severe lightning disaster for Shenyang region,but forecast service had poor effect without forecasting thunderstorm weather accurately.In our paper,the reasons for missing report of this thunderstorm weather were analyzed,and analysis on thunderstorm potential was carried out by means of mesoscale analysis technique,providing technical index and vantage point for the prediction of thunderstorm potential.The results showed that the reasons for missing report of this weather process were as follows:surface temperature at prophase was constantly lower going against the development of convective weather;the interpreting and analyzing ability of numerical forecast product should be improved;the forecast result of T639 model was better than that of Japanese numerical forecast;the study and application of mesoscale analysis technique should be strengthened,and this service was formally developed after thunderstorm weather on June 1,2010.展开更多
Based in 11 daily weather observation station data in Shanghai from 1971 to 2008,a careful research and analysis on the features of thunderstorms spatial and temporal distribution and thunderstorm movement in Shanghai...Based in 11 daily weather observation station data in Shanghai from 1971 to 2008,a careful research and analysis on the features of thunderstorms spatial and temporal distribution and thunderstorm movement in Shanghai was carried out by using the statistical software of SAS,the method of Mann-Kendall test and wavelets. The results showed that the average annual numbers of thunderstorms days were 26.1,and inter-annual thunderstorm variability was obvious,the annual number of thunderstorm days had a decreasing trend,its value of decreasing days was about-0.418 5 d/10 a. Mann-Kendall test showed that there was an abrupt change in 2000. The seasonal variation of thunderstorm in Shanghai was explicit. The period from March to September was the season when thunderstorm occurred most frequently,about 64.9% of the thunderstorms in a year took place in summer. The results from wavelets analysis showed that the variation cycle period of the annual number of thunderstorms days was about 3,5,12 and 20 years.展开更多
[Objective] The study aims to analyze characteristics of thunderstorm activity in Hefei City. [Method] Based on conventional ground observational data during1981-2010 and lightning location data in 2010-2013 in Hefei ...[Objective] The study aims to analyze characteristics of thunderstorm activity in Hefei City. [Method] Based on conventional ground observational data during1981-2010 and lightning location data in 2010-2013 in Hefei City, temporal and spatial variation of thunderstorm days were analyzed using statistical methods, and then the distribution laws of thunderstorm days were compared with the lightning location data. [Result] In Hefei City, multi-year average of thunderstorm days from1981 to 2010 was more in the south but less in the north, and annual distribution of thunderstorm days was extremely uneven. Moreover, there were obvious seasonal and monthly variation in thunderstorm days in Hefei City. Thunderstorm days were the most in summer, and monthly average of thunderstorm days in Hefei City had a peak in July. From 2010 to 2013, the monthly variation curves of total frequency of cloud-to-ground lightning and frequency of negative cloud-to-ground lightning in Hefei City had a peak each, and cloud-to-ground lightning was frequent in July and August, especially August. The frequency of cloud-to-ground lightning exceeded the average from 12：00 to 21：00. The maximum intensity of cloud-to-ground lightning in Hefei City varied greatly in different months, and it was the highest in July. There are certain differences between the two kinds of data in the distribution laws, so it is needed to combine data of lightning position indicator and long-term artificial observation data to study the detection efficiency of lightning position indicator. [Conclusion] The research can provide theoretical references for lightning protection and disaster reduction in Hefei City.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2022YFC3004104)the National Natural Science Foundation of China(Grant No.U2342204)+4 种基金the Innovation and Development Program of the China Meteorological Administration(Grant No.CXFZ2024J001)the Open Research Project of the Key Open Laboratory of Hydrology and Meteorology of the China Meteorological Administration(Grant No.23SWQXZ010)the Science and Technology Plan Project of Zhejiang Province(Grant No.2022C03150)the Open Research Fund Project of Anyang National Climate Observatory(Grant No.AYNCOF202401)the Open Bidding for Selecting the Best Candidates Program(Grant No.CMAJBGS202318)。
文摘Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.Therefore,it is necessary to establish thunderstorm wind gust identification techniques based on multisource high-resolution observations.This paper introduces a new algorithm,called thunderstorm wind gust identification network(TGNet).It leverages multimodal feature fusion to fuse the temporal and spatial features of thunderstorm wind gust events.The shapelet transform is first used to extract the temporal features of wind speeds from automatic weather stations,which is aimed at distinguishing thunderstorm wind gusts from those caused by synoptic-scale systems or typhoons.Then,the encoder,structured upon the U-shaped network(U-Net)and incorporating recurrent residual convolutional blocks(R2U-Net),is employed to extract the corresponding spatial convective characteristics of satellite,radar,and lightning observations.Finally,by using the multimodal deep fusion module based on multi-head cross-attention,the temporal features of wind speed at each automatic weather station are incorporated into the spatial features to obtain 10-minutely classification of thunderstorm wind gusts.TGNet products have high accuracy,with a critical success index reaching 0.77.Compared with those of U-Net and R2U-Net,the false alarm rate of TGNet products decreases by 31.28%and 24.15%,respectively.The new algorithm provides grid products of thunderstorm wind gusts with a spatial resolution of 0.01°,updated every 10minutes.The results are finer and more accurate,thereby helping to improve the accuracy of operational warnings for thunderstorm wind gusts.
基金supported in part by the National Natural Science Foundation of China under Grant 62171228in part by the National Key R&D Program of China under Grant 2021YFE0105500in part by the Program of China Scholarship Council under Grant 202209040027。
文摘Thunderstorm detection based on the Atmospheric Electric Field(AEF)has evolved from time-domain models to space-domain models.It is especially important to evaluate and determine the particularly Weather Attribute(WA),which is directly related to the detection reliability and authenticity.In this paper,a strategy is proposed to integrate three currently competitive WA's evaluation methods.First,a conventional evaluation method based on AEF statistical indicators is selected.Subsequent evaluation approaches include competing AEF-based predicted value intervals,and AEF classification based on fuzzy c-means.Different AEF attributes contribute to a more accurate AEF classification to different degrees.The resulting dynamic weighting applied to these attributes improves the classification accuracy.Each evaluation method is applied to evaluate the WA of a particular AEF,to obtain the corresponding evaluation score.The integration in the proposed strategy takes the form of a score accumulation.Different cumulative score levels correspond to different final WA results.Thunderstorm imaging is performed to visualize thunderstorm activities using those AEFs already evaluated to exhibit thunderstorm attributes.Empirical results confirm that the proposed strategy effectively and reliably images thunderstorms,with a 100%accuracy of WA evaluation.This is the first study to design an integrated thunderstorm detection strategy from a new perspective of WA evaluation,which provides promising solutions for a more reliable and flexible thunderstorm detection.
基金supported in part by the Beijing Natural Science Foundation(Grant No.8222051)the National Key R&D Program of China(Grant No.2022YFC3004103)+2 种基金the National Natural Foundation of China(Grant Nos.42275003 and 42275012)the China Meteorological Administration Key Innovation Team(Grant Nos.CMA2022ZD04 and CMA2022ZD07)the Beijing Science and Technology Program(Grant No.Z221100005222012).
文摘Thunderstorm gusts are a common form of severe convective weather in the warm season in North China,and it is of great importance to correctly forecast them.At present,the forecasting of thunderstorm gusts is mainly based on traditional subjective methods,which fails to achieve high-resolution and high-frequency gridded forecasts based on multiple observation sources.In this paper,we propose a deep learning method called Thunderstorm Gusts TransU-net(TGTransUnet)to forecast thunderstorm gusts in North China based on multi-source gridded product data from the Institute of Urban Meteorology(IUM)with a lead time of 1 to 6 h.To determine the specific range of thunderstorm gusts,we combine three meteorological variables:radar reflectivity factor,lightning location,and 1-h maximum instantaneous wind speed from automatic weather stations(AWSs),and obtain a reasonable ground truth of thunderstorm gusts.Then,we transform the forecasting problem into an image-to-image problem in deep learning under the TG-TransUnet architecture,which is based on convolutional neural networks and a transformer.The analysis and forecast data of the enriched multi-source gridded comprehensive forecasting system for the period 2021–23 are then used as training,validation,and testing datasets.Finally,the performance of TG-TransUnet is compared with other methods.The results show that TG-TransUnet has the best prediction results at 1–6 h.The IUM is currently using this model to support the forecasting of thunderstorm gusts in North China.
基金primarily supported by the National Natural Science Foundation of China(Grant Nos.42025501,41805025,42175005,and 61827901)the National Key R&D Program of China(2022YFC3003905)+5 种基金the National Key Laboratory on Electromagnetic Environmental Effects and Electro-optical Engineering(NO.JCKYS61422062101)the Meteorological Union Fund of the National Natural Science Foundation of China(U2142203)the Foundation of Jiangsu Provincial Meteorological Bureau(KM202308)The Open Grants of China Meteorological Administration Radar Meteorology Key Laboratory(2023LRMB04)S&T Development Fund of NJIAS(KJF202307)the Open Research Program of the State Key Laboratory of Severe Weather(2022LASW-A01)。
文摘In this study,we examine the dynamics and microphysical structures of a deep compact thunderstorm event driving cloud-to-ground(CG)lightning over the Nanjing area located within the Yangtze-Huai River Basin(YHRB)during the monsoon break period.The microphysical structures combined with the dynamics in the glaciated,mixed-phase,and warm-phase layers during the formative,intensifying,and mature stages of the thunderstorm were first investigated using C-band polarimetric radar and CG lightning observations.The results show that the mature phase of the thunderstorm produced a local cold pool,which collided with a southerly warm wind,resulting in a strong updraft.The strong updraft favored the lifting of raindrops to the mixed-phase region to form abundant supercooled liquid water and graupel.From the formative stage to the developing stage and further to the mature stage,increased ZH-and reduced ZDR-values within the mixed-phase region are found,especially within the strong updraft region(>5 m s^(-1)).This phenomenon suggests that supercooled raindrops evolved into large hydrometeors(graupel and hail),indicative of a strong riming process.The signatures within this region are consistent with a favorable environment for thunderstorm electrification and generate the most frequent lightning during the thunderstorm life cycle.
文摘This paper presents an analysis of spatial and temporal variation of rainfall and thunderstorm occurrence over Ken-ya from January 1987 to December 2017.The meteorological data used were obtained from the Kenya Meteorological Department(KMD)for the same period.This included the monthly thunderstorm occurrences and rainfall amounts of 26 synoptic stations across the country.The characteristics of monthly,seasonal and annual frequency results were presented on spatial maps while Time series graphs were used to display the pattern for annual cycle,seasonal varia-tions and the inter-annual variability of rainfall amounts and thunderstorm occurrences.A well-known non-parametric statistical method Mann Kendall(MK)trend test was used to determine and compare the statistical significance of the trends.Thunderstorm frequencies over the Eastern,Central and Coast regions of the country showed a bimodal pattern with high frequencies coinciding with March-April-May(MAM)and October-November-December(OND)rainy sea-sons.Very few thunderstorm days were detected over June-July-August(JJA)season.The areas to the western part of the country,near Lake Victoria,had the highest thunderstorm frequencies in the country over the three seasons:MAM,JJAS and OND.The annual frequency showed a quasi-unimodal pattern.These places near Lake Victoria showed sig-nificantly increasing thunderstorm trends during the MAM and OND seasons irrespective of the rainfall trends.This shows the effects of Lake Victoria over these areas,and it acts as a continuous source of moisture for thunderstorm for-mation.However,most stations across the country showed a reducing trend of thunderstorm frequency during MAM and JJA seasons.The importance of these findings is that they could support various policy makers,and users of cli-mate information,especially in the agriculture and aviation industries.
文摘为了进一步认识上升气流对雷暴云内复杂电荷结构特征的影响,利用加入起放电参数化方案的WRF模式对DC3试验中2012年6月6日一次出现反极性电荷结构的强雷暴过程进行模拟。结果表明,起电区对应强回波区,主要发生在上升气流区中心云水混合比大于0.2 g kg^(-1)的冰水混合区,非感应起电机制主导着雷暴云内的起电过程。上升气流区外围区域存在可观的电荷,主要是由气流将起电区域的荷电粒子向后水平输送形成的。同类粒子带电极性在较大范围内变化少,但由于各类粒子的含量和荷电量不同,导致净电荷密度分布呈现较复杂的结构。达到一定强度的上升气流可以破坏电荷区的连续性,导致对流区出现高密度的、正负极性交错分布的、范围更小的电荷区。层云区由于没有上升气流,荷电粒子主要源自上升气流区的水平输送,所以其电荷区分布较连续且范围较大,但电荷密度相对弱。处于不同生命期的单体由于上升气流强度和倾斜程度不同,单体间的水成物粒子分布特征会存在一定差异,使得反转温度和起电率出现较大不同,因此单体合并时上升气流区之间的电荷区更破碎,电荷结构更复杂。
基金Supported by The Special Project of Public Welfare Industry Scientific Research(GYHY200806014)Nanjing University of Information Science & Technology Project(E30JG0730)
文摘Based on the radar data and lightning position indicator data of strong thunderstorm weather which happened in Fuxin on July 8,2007,the relationship between the lightning activity and the radar echo was analyzed.The results showed that Fuxin area located in the cross position of T-shaped trough and was affected by the cold air which continuously glided down.The corresponding warm front on the ground advanced southward and arrived here.It was the weather background of this thunderstorm weather.The position variation of lightning occurrence was closely related to the strong echo movement of squall line,and the velocity echo clearly reflected and predicted the movement tendency of the radar echo.
文摘The first thunderstorm weather appeared in southern Shenyang on May 2,2010 and did not bring about severe lightning disaster for Shenyang region,but forecast service had poor effect without forecasting thunderstorm weather accurately.In our paper,the reasons for missing report of this thunderstorm weather were analyzed,and analysis on thunderstorm potential was carried out by means of mesoscale analysis technique,providing technical index and vantage point for the prediction of thunderstorm potential.The results showed that the reasons for missing report of this weather process were as follows:surface temperature at prophase was constantly lower going against the development of convective weather;the interpreting and analyzing ability of numerical forecast product should be improved;the forecast result of T639 model was better than that of Japanese numerical forecast;the study and application of mesoscale analysis technique should be strengthened,and this service was formally developed after thunderstorm weather on June 1,2010.
基金Supported by Scientific Research Special Fund for Public Welfare Industry(GYHY 200806014)
文摘Based in 11 daily weather observation station data in Shanghai from 1971 to 2008,a careful research and analysis on the features of thunderstorms spatial and temporal distribution and thunderstorm movement in Shanghai was carried out by using the statistical software of SAS,the method of Mann-Kendall test and wavelets. The results showed that the average annual numbers of thunderstorms days were 26.1,and inter-annual thunderstorm variability was obvious,the annual number of thunderstorm days had a decreasing trend,its value of decreasing days was about-0.418 5 d/10 a. Mann-Kendall test showed that there was an abrupt change in 2000. The seasonal variation of thunderstorm in Shanghai was explicit. The period from March to September was the season when thunderstorm occurred most frequently,about 64.9% of the thunderstorms in a year took place in summer. The results from wavelets analysis showed that the variation cycle period of the annual number of thunderstorms days was about 3,5,12 and 20 years.
文摘[Objective] The study aims to analyze characteristics of thunderstorm activity in Hefei City. [Method] Based on conventional ground observational data during1981-2010 and lightning location data in 2010-2013 in Hefei City, temporal and spatial variation of thunderstorm days were analyzed using statistical methods, and then the distribution laws of thunderstorm days were compared with the lightning location data. [Result] In Hefei City, multi-year average of thunderstorm days from1981 to 2010 was more in the south but less in the north, and annual distribution of thunderstorm days was extremely uneven. Moreover, there were obvious seasonal and monthly variation in thunderstorm days in Hefei City. Thunderstorm days were the most in summer, and monthly average of thunderstorm days in Hefei City had a peak in July. From 2010 to 2013, the monthly variation curves of total frequency of cloud-to-ground lightning and frequency of negative cloud-to-ground lightning in Hefei City had a peak each, and cloud-to-ground lightning was frequent in July and August, especially August. The frequency of cloud-to-ground lightning exceeded the average from 12：00 to 21：00. The maximum intensity of cloud-to-ground lightning in Hefei City varied greatly in different months, and it was the highest in July. There are certain differences between the two kinds of data in the distribution laws, so it is needed to combine data of lightning position indicator and long-term artificial observation data to study the detection efficiency of lightning position indicator. [Conclusion] The research can provide theoretical references for lightning protection and disaster reduction in Hefei City.
