This study investigates the interannual and decadal variability of dominant summer thunderstorm day anomaly modes over the Tibetan Plateau(TP)using observational data from 39 stations during 1979-2013,focusing on thei...This study investigates the interannual and decadal variability of dominant summer thunderstorm day anomaly modes over the Tibetan Plateau(TP)using observational data from 39 stations during 1979-2013,focusing on their linkages to TP thermodynamics and oceanatmosphere interactions.Empirical orthogonal function and wavelet analyses reveal two primary spatiotemporal modes:The first mode exhibits a northeastsouthwest meridionally inclining dipole pattern with widespread positive anomalies over the northeastern TP,showing significant interannual variability of 35 years and 8 years.The second mode presents a southwest-northeast zonally inclining dipole pattern with prominent positive anomalies over the southwestern TP,displaying 3-year and 5-year interannual oscillations.The TP exhibits significant interannual variability in thunderstorm days,with an evident amplification after 200o.Convective available potential energy(CAPE),as a key indicator of the lightning and severe thunderstorm environment,dominates the interannual variability of TP thunderstorm days.The Indian Ocean Basin-Wide mode(IOBW)modulates thunderstorm days by influencing the large-scale divergence-convergence dynamics and moisture environment.Specifically,the IOBW strengthens the Bay of Bengal anticyclone,enhancing moisture transport to the southeastern TP,and amplifies uppertropospheric divergence.Combined with enhanced CAPE,these processes collectively lead to an increase in thunderstorm days.Multiple-variable regression analyses indicate that IOBW and CAPE collectively explain 52.1%of the interannual thunderstorm day variability.These findings advance the understanding of the mechanisms underlying TP interannual thunderstorm activity and provide crucial insights for improving regional climate projections.展开更多
利用高空、地面气象观测资料和欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)第五代大气再分析资料(ERA5),分析2008年6月25日和2017年7月21日发生在京津冀南部和中部的两次暖季高架雷暴天气,探寻对...利用高空、地面气象观测资料和欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)第五代大气再分析资料(ERA5),分析2008年6月25日和2017年7月21日发生在京津冀南部和中部的两次暖季高架雷暴天气,探寻对流发生时大气的不稳定性与触发机制。结果表明:(1)两次暖季高架雷暴发生在低层大气较冷的稳定层结状态下,当强逆温之上为条件性不稳定时,对流强度强于弱逆温之上的稳定层结过程。(2)中高层的对流不稳定层结早于高架雷暴8 h建立,强逆温高架雷暴不稳定度更高,利于生成雷暴大风,表现为强降水天气的对流不稳定性较弱;K指数对暖季高架雷暴有较强反映,SI和T85对雷暴大风的出现更敏感,LI对强降水预报的应用效果更好。(3)两次高架雷暴分别发生于低涡东南部和副热带高压控制的不同天气背景下,逆温层附近或之上大气呈对称不稳定特点,有斜升气流发展。(4)925~700 hPa的锋生,以及850 hPa的纬向风切变对强对流的形成有显著的触发作用,锋生高度下降越快、强度越强,越有利于大风出现;锋生持续时间长,则强降水持久,冷垫之上强烈垂直风切变的长时间维持预示强降水雷暴单体的发展与传播。展开更多
Accurate monitoring and timely identification of early indicators of thunderstorms are of paramount importance in preventing and mitigating the potential disasters associated with such meteorological events.This study...Accurate monitoring and timely identification of early indicators of thunderstorms are of paramount importance in preventing and mitigating the potential disasters associated with such meteorological events.This study utilizes the TOBAC(Tracking and Object-Based Analysis of Clouds)automated tracking algorithm,integrated with FY-4A geostationary satellite infrared data,to investigate the spatiotemporal characteristics and evolutionary patterns of cloud-top brightness temperature(BT),areal extent,and phase transitions of thunderstorm and non-thunderstorm clouds across the North China region.The analysis reveals that thunderstorm clouds demonstrate significantly enhanced convective intensity compared to non-thunderstorm clouds,with the following distinctive features:(1)a substantially faster drop rate in 10.8µm BT,reaching values nearly 2.3 times greater;(2)positive BT differences between the 10.8 and 8.5µm channels,exceeding 0 K;and(3)a dramatically increased areal expansion rate,approximately 4.5-fold higher than that observed in non-thunderstorm clouds.These findings provide significant scientific insights and practical implications for advancing thunderstorm identification techniques and optimizing early warning systems,which are critical to improving disaster prevention and mitigation capacity across the North China region.展开更多
Using multi-satellite observations, the authors examined 20 upward discharge events from thunderstorms (15blue jets (BJs)/blue starters (BSs) and 5 gigantic jets (GJs)) observed by ISUAL (Imager of Sprites and Upper A...Using multi-satellite observations, the authors examined 20 upward discharge events from thunderstorms (15blue jets (BJs)/blue starters (BSs) and 5 gigantic jets (GJs)) observed by ISUAL (Imager of Sprites and Upper Atmospheric Lightning) between 2009 and 2015. The analyses reveal that these BJ/BS and GJ discharges consistently originated from thunderstorms with vigorous convection, strong mixed-phase microphysics, and high CAPE (convective available potential energy) of greater than 1000 J kg-1 in most cases, yet cloud tops remained 13 km below the 1617 km tropical tropopause. Notably, one GJ emerged from a shallow thunderstorm with exceptionally low CAPE (~140 J kg−1) and cloud tops of only ~6 km, exposing previously unrecognized initiation pathways. It is concluded that thunderstorms in Central Africa can produce BJ/BSs and GJs without penetrating the tropopause, challenging the prevailing overshooting-top paradigm that has dominated jet initiation theory.The results demonstrate that tropopause penetration is probably not a prerequisite for jet production and identify Central Africa as a critical natural laboratory for advancing our understanding of troposphere-ionosphere coupling and the dynamics of transient luminous events.展开更多
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
Changes in the Atmospheric Electric Field Signal(AEFS)are highly correlated with weather changes,especially with thunderstorm activities.However,little attention has been paid to the ambiguous weather information impl...Changes in the Atmospheric Electric Field Signal(AEFS)are highly correlated with weather changes,especially with thunderstorm activities.However,little attention has been paid to the ambiguous weather information implicit in AEFS changes.In this paper,a Fuzzy C-Means(FCM)clustering method is used for the first time to develop an innovative approach to characterize the weather attributes carried by AEFS.First,a time series dataset is created in the time domain using AEFS attributes.The AEFS-based weather is evaluated according to the time-series Membership Degree(MD)changes obtained by inputting this dataset into the FCM.Second,thunderstorm intensities are reflected by the change in distance from a thunderstorm cloud point charge to an AEF apparatus.Thus,a matching relationship is established between the normalized distance and the thunderstorm dominant MD in the space domain.Finally,the rationality and reliability of the proposed method are verified by combining radar charts and expert experience.The results confirm that this method accurately characterizes the weather attributes and changes in the AEFS,and a negative distance-MD correlation is obtained for the first time.The detection of thunderstorm activity by AEF from the perspective of fuzzy set technology provides a meaningful guidance for interpretable thunderstorms.展开更多
Numerical simulation of the merging of a thunderstorm cluster from the mountain area near Beijing and a thunderstorm over the adjacent plains on 23 August 2021,along with a diagnosis and analysis of the cold pool and ...Numerical simulation of the merging of a thunderstorm cluster from the mountain area near Beijing and a thunderstorm over the adjacent plains on 23 August 2021,along with a diagnosis and analysis of the cold pool and vertical motion,reveals the following:(1)The thunderstorm cluster in the mountain area moved slowly westward,weakening during its descent,whereas the thunderstorm cluster in the urban area moved rapidly eastward and intensified.Eventually,the two thunderstorm clusters encountered each other at the foot of the mountain and organized into a linear convective system.(2)Prior to merging,the thunderstorm cluster in the mountain area was blocked by warm advection to the east,causing the system to slow down,the cold pool to weaken,and the convergence and ascent associated with the cold pool outflow to diminish.In contrast,the thunderstorm cluster over the adjacent plains was driven by cold advection to the west,accelerating the system’s movement,strengthening the cold pool,and enhancing the convergence and ascent driven by the cold pool outflow.After the thunderstorm clusters merged,the convergence of the northwesterly and southeasterly winds,as well as precipitation,led to the rapid accumulation of cold air,strengthening the cold pool and its upward development,which acted similarly to a terrain feature,further enhancing convergence and ascent.(3)The vertical motion reveals that before merging,the thunderstorm cluster in the mountain area was dominated by negative buoyancy at lower levels,which suppressed the development of ascent,whereas the thunderstorm cluster over the adjacent plains was driven by positive disturbances in the vertical pressure gradient force,which increased ascent.After the merging,the positive disturbances in the vertical pressure gradient force dominated below 2 km,and as the vertical motion increased,the positive buoyancy gradually became the dominant driver,further strengthening the ascent.The analysis suggests that the positive potential temperature disturbance and the southeasterly or southerly winds over the adjacent plains had opposing effects on the two approaching thunderstorm clusters,with the thunderstorm cluster over the adjacent plains taking the lead during the merging process.展开更多
基金supported by a project of the National Natural Science Foundation of China[grant numbers 41230419 and 42322505]the National Key R&D Program of China[grant number 2023YFE0121100]。
摘要This study investigates the interannual and decadal variability of dominant summer thunderstorm day anomaly modes over the Tibetan Plateau(TP)using observational data from 39 stations during 1979-2013,focusing on their linkages to TP thermodynamics and oceanatmosphere interactions.Empirical orthogonal function and wavelet analyses reveal two primary spatiotemporal modes:The first mode exhibits a northeastsouthwest meridionally inclining dipole pattern with widespread positive anomalies over the northeastern TP,showing significant interannual variability of 35 years and 8 years.The second mode presents a southwest-northeast zonally inclining dipole pattern with prominent positive anomalies over the southwestern TP,displaying 3-year and 5-year interannual oscillations.The TP exhibits significant interannual variability in thunderstorm days,with an evident amplification after 200o.Convective available potential energy(CAPE),as a key indicator of the lightning and severe thunderstorm environment,dominates the interannual variability of TP thunderstorm days.The Indian Ocean Basin-Wide mode(IOBW)modulates thunderstorm days by influencing the large-scale divergence-convergence dynamics and moisture environment.Specifically,the IOBW strengthens the Bay of Bengal anticyclone,enhancing moisture transport to the southeastern TP,and amplifies uppertropospheric divergence.Combined with enhanced CAPE,these processes collectively lead to an increase in thunderstorm days.Multiple-variable regression analyses indicate that IOBW and CAPE collectively explain 52.1%of the interannual thunderstorm day variability.These findings advance the understanding of the mechanisms underlying TP interannual thunderstorm activity and provide crucial insights for improving regional climate projections.
摘要利用高空、地面气象观测资料和欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)第五代大气再分析资料(ERA5),分析2008年6月25日和2017年7月21日发生在京津冀南部和中部的两次暖季高架雷暴天气,探寻对流发生时大气的不稳定性与触发机制。结果表明:(1)两次暖季高架雷暴发生在低层大气较冷的稳定层结状态下,当强逆温之上为条件性不稳定时,对流强度强于弱逆温之上的稳定层结过程。(2)中高层的对流不稳定层结早于高架雷暴8 h建立,强逆温高架雷暴不稳定度更高,利于生成雷暴大风,表现为强降水天气的对流不稳定性较弱;K指数对暖季高架雷暴有较强反映,SI和T85对雷暴大风的出现更敏感,LI对强降水预报的应用效果更好。(3)两次高架雷暴分别发生于低涡东南部和副热带高压控制的不同天气背景下,逆温层附近或之上大气呈对称不稳定特点,有斜升气流发展。(4)925~700 hPa的锋生,以及850 hPa的纬向风切变对强对流的形成有显著的触发作用,锋生高度下降越快、强度越强,越有利于大风出现;锋生持续时间长,则强降水持久,冷垫之上强烈垂直风切变的长时间维持预示强降水雷暴单体的发展与传播。
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDB0760402]the National Natural Science Foundation of China[grant number42322505]。
摘要Accurate monitoring and timely identification of early indicators of thunderstorms are of paramount importance in preventing and mitigating the potential disasters associated with such meteorological events.This study utilizes the TOBAC(Tracking and Object-Based Analysis of Clouds)automated tracking algorithm,integrated with FY-4A geostationary satellite infrared data,to investigate the spatiotemporal characteristics and evolutionary patterns of cloud-top brightness temperature(BT),areal extent,and phase transitions of thunderstorm and non-thunderstorm clouds across the North China region.The analysis reveals that thunderstorm clouds demonstrate significantly enhanced convective intensity compared to non-thunderstorm clouds,with the following distinctive features:(1)a substantially faster drop rate in 10.8µm BT,reaching values nearly 2.3 times greater;(2)positive BT differences between the 10.8 and 8.5µm channels,exceeding 0 K;and(3)a dramatically increased areal expansion rate,approximately 4.5-fold higher than that observed in non-thunderstorm clouds.These findings provide significant scientific insights and practical implications for advancing thunderstorm identification techniques and optimizing early warning systems,which are critical to improving disaster prevention and mitigation capacity across the North China region.
基金supported by the Deployment Project of CAS-BIC for Overseas Science and Education Cooperation Center [grant number 119GJHZ2024027MI]the National Natural Science Foundation of China [grant number 42394122]+2 种基金the CAS Project of Stable Support for Youth Team in Basic Research Field [grant number YSBR-018]supported by the Climbing Program of NSSC [grant number E1PD3001]the Chinese Meridian Project。
摘要Using multi-satellite observations, the authors examined 20 upward discharge events from thunderstorms (15blue jets (BJs)/blue starters (BSs) and 5 gigantic jets (GJs)) observed by ISUAL (Imager of Sprites and Upper Atmospheric Lightning) between 2009 and 2015. The analyses reveal that these BJ/BS and GJ discharges consistently originated from thunderstorms with vigorous convection, strong mixed-phase microphysics, and high CAPE (convective available potential energy) of greater than 1000 J kg-1 in most cases, yet cloud tops remained 13 km below the 1617 km tropical tropopause. Notably, one GJ emerged from a shallow thunderstorm with exceptionally low CAPE (~140 J kg−1) and cloud tops of only ~6 km, exposing previously unrecognized initiation pathways. It is concluded that thunderstorms in Central Africa can produce BJ/BSs and GJs without penetrating the tropopause, challenging the prevailing overshooting-top paradigm that has dominated jet initiation theory.The results demonstrate that tropopause penetration is probably not a prerequisite for jet production and identify Central Africa as a critical natural laboratory for advancing our understanding of troposphere-ionosphere coupling and the dynamics of transient luminous events.
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)。
摘要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。
摘要Changes in the Atmospheric Electric Field Signal(AEFS)are highly correlated with weather changes,especially with thunderstorm activities.However,little attention has been paid to the ambiguous weather information implicit in AEFS changes.In this paper,a Fuzzy C-Means(FCM)clustering method is used for the first time to develop an innovative approach to characterize the weather attributes carried by AEFS.First,a time series dataset is created in the time domain using AEFS attributes.The AEFS-based weather is evaluated according to the time-series Membership Degree(MD)changes obtained by inputting this dataset into the FCM.Second,thunderstorm intensities are reflected by the change in distance from a thunderstorm cloud point charge to an AEF apparatus.Thus,a matching relationship is established between the normalized distance and the thunderstorm dominant MD in the space domain.Finally,the rationality and reliability of the proposed method are verified by combining radar charts and expert experience.The results confirm that this method accurately characterizes the weather attributes and changes in the AEFS,and a negative distance-MD correlation is obtained for the first time.The detection of thunderstorm activity by AEF from the perspective of fuzzy set technology provides a meaningful guidance for interpretable thunderstorms.
基金funded by the Beijing Municipal Science and Technology Commission[grant number Z221100005222012]the Department of Science and Technology of Hebei Province[grant number 22375404D]+1 种基金the National Natural Science Foundation of China[grant numbers U2233218 and 42275010]supported by the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDB0760300].
摘要Numerical simulation of the merging of a thunderstorm cluster from the mountain area near Beijing and a thunderstorm over the adjacent plains on 23 August 2021,along with a diagnosis and analysis of the cold pool and vertical motion,reveals the following:(1)The thunderstorm cluster in the mountain area moved slowly westward,weakening during its descent,whereas the thunderstorm cluster in the urban area moved rapidly eastward and intensified.Eventually,the two thunderstorm clusters encountered each other at the foot of the mountain and organized into a linear convective system.(2)Prior to merging,the thunderstorm cluster in the mountain area was blocked by warm advection to the east,causing the system to slow down,the cold pool to weaken,and the convergence and ascent associated with the cold pool outflow to diminish.In contrast,the thunderstorm cluster over the adjacent plains was driven by cold advection to the west,accelerating the system’s movement,strengthening the cold pool,and enhancing the convergence and ascent driven by the cold pool outflow.After the thunderstorm clusters merged,the convergence of the northwesterly and southeasterly winds,as well as precipitation,led to the rapid accumulation of cold air,strengthening the cold pool and its upward development,which acted similarly to a terrain feature,further enhancing convergence and ascent.(3)The vertical motion reveals that before merging,the thunderstorm cluster in the mountain area was dominated by negative buoyancy at lower levels,which suppressed the development of ascent,whereas the thunderstorm cluster over the adjacent plains was driven by positive disturbances in the vertical pressure gradient force,which increased ascent.After the merging,the positive disturbances in the vertical pressure gradient force dominated below 2 km,and as the vertical motion increased,the positive buoyancy gradually became the dominant driver,further strengthening the ascent.The analysis suggests that the positive potential temperature disturbance and the southeasterly or southerly winds over the adjacent plains had opposing effects on the two approaching thunderstorm clusters,with the thunderstorm cluster over the adjacent plains taking the lead during the merging process.