This study utilizes data from a 3D lightning location system,polarimetric radar,and current measurements from channels of triggered lightning flashes(TLFs)to analyze the structural characteristics of the parent thunde...This study utilizes data from a 3D lightning location system,polarimetric radar,and current measurements from channels of triggered lightning flashes(TLFs)to analyze the structural characteristics of the parent thunderstorms associated with negative TLFs in South China.The triggered-flash region(TFR)displays distinct stratiform cloud characteristics,including lower radar reflectivity heights and a predominance of ice crystals and dry snow above the 0℃ layer.In contrast,the thunderstorm convection core region(CCR)tends to have more graupel particles in the mixed-phase layers and exhibits an ice-water content peak approximately 3.4 times that of the TFR.The charge regions involved in discharges in TFRs exhibit a dipolar charge structure,with the-5℃ layer roughly dividing the upper positive and lower negative charge regions.Conversely,the CCRs feature a typical tripolar charge structure.The dominant dipole charge structure in the TFR results in an increase in the negative charge field below the negative charge region with height,providing a necessary condition for successfully triggering negative TLFs.Furthermore,the horizontal extent of TLFs is positively correlated with their duration and charge transfer.Regions where TLF channels with larger charge transfers propagate tend to have greater maximum radar reflectivity but lower average radar reflectivity compared to regions with TLFs with smaller charge transfer.展开更多
航路网络作为民航运输网络的运行载体,承担着保障航空器安全高效运行的重要任务。当重要航路点因雷暴扰动失效时,易连锁反应至相邻节点最终导致网络性能的显著下降。针对现有复杂网络节点重要度评估模型未有效考虑雷暴扰动的问题,面向...航路网络作为民航运输网络的运行载体,承担着保障航空器安全高效运行的重要任务。当重要航路点因雷暴扰动失效时,易连锁反应至相邻节点最终导致网络性能的显著下降。针对现有复杂网络节点重要度评估模型未有效考虑雷暴扰动的问题,面向雷暴天气场景,将雷暴扰动特性纳入航路点重要度评估体系,利用博弈论方法对评估指标进行组合赋权,基于引力模型理论改进了TOPSIS(technique for order preference by similarity to an ideal solution)综合评价方法,建立基于博弈论-改进TOPSIS法的节点重要度评估模型,进而采用K中心点算法实现航路点聚类分级。以京津冀地区航班运行为例,对雷暴天气场景下的航路网络节点重要度进行评估,结果表明:在京津冀航路网络内,南部地区的航路点更易受雷暴天气影响且分布较为密集,该航路网络包含9个重要航路点,当航路网络中的重要航路点因雷暴影响而失效时,会对航路网络性能产生显著的负面影响。提出的基于博弈论-改进TOPSIS法的节点重要度评估模型可以有效识别出雷雨季节或雷暴高发地区航路网络中的重要航路点,从而为雷暴场景下航路网络结构优化与资源配置提供有效依据。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
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
利用实况资料和再分析资料,结合WRF(weather research and forecasting)模式对南通一次极端大风过程进行诊断分析及数值模拟。分析了该个例发生的天气形势背景和系统的水平、垂直结构,探究大风天气成因,并进一步对比不同参数化方案的模...利用实况资料和再分析资料,结合WRF(weather research and forecasting)模式对南通一次极端大风过程进行诊断分析及数值模拟。分析了该个例发生的天气形势背景和系统的水平、垂直结构,探究大风天气成因,并进一步对比不同参数化方案的模拟效果。结果表明:1)大风过程发生在高空深厚冷涡和地面强暖湿低压的环流背景下,上空存在不稳定层结和不稳定能量的累积;雷暴大风在12—13时经历了发展、成熟、消散3个阶段,飑线以碎块型的方式形成。2)3种微物理方案中,MG方案模拟出更大面积的层云、强回波和极端大风,模拟的最大地面阵风为44.47 m·s^(-1)。Lin方案较好地模拟出飑线的演变过程和垂直结构特征,模拟的最强上升气流达23.55 m·s^(-1),下沉气流达-13.21 m·s^(-1)。3)水平方向上,雷暴大风附近存在成熟的飑线地面中尺度系统,地面存在深厚冷池出流、变压梯度大值区和冷锋过境,它们共同促进了地面大风的生成。4)垂直方向上,对流单体上空高层辐散、低层辐合,存在强上升气流和水汽潜热释放;后侧的干空气蒸发和粒子的拖曳加强下沉运动,配合地面冷池出流和辐散气流,造成了极端大风天气。展开更多
基金funded by the Natural Science Foundation of China(Grant No.U2342215)Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province(Grant No.SCSF202302)。
文摘This study utilizes data from a 3D lightning location system,polarimetric radar,and current measurements from channels of triggered lightning flashes(TLFs)to analyze the structural characteristics of the parent thunderstorms associated with negative TLFs in South China.The triggered-flash region(TFR)displays distinct stratiform cloud characteristics,including lower radar reflectivity heights and a predominance of ice crystals and dry snow above the 0℃ layer.In contrast,the thunderstorm convection core region(CCR)tends to have more graupel particles in the mixed-phase layers and exhibits an ice-water content peak approximately 3.4 times that of the TFR.The charge regions involved in discharges in TFRs exhibit a dipolar charge structure,with the-5℃ layer roughly dividing the upper positive and lower negative charge regions.Conversely,the CCRs feature a typical tripolar charge structure.The dominant dipole charge structure in the TFR results in an increase in the negative charge field below the negative charge region with height,providing a necessary condition for successfully triggering negative TLFs.Furthermore,the horizontal extent of TLFs is positively correlated with their duration and charge transfer.Regions where TLF channels with larger charge transfers propagate tend to have greater maximum radar reflectivity but lower average radar reflectivity compared to regions with TLFs with smaller charge transfer.
文摘航路网络作为民航运输网络的运行载体,承担着保障航空器安全高效运行的重要任务。当重要航路点因雷暴扰动失效时,易连锁反应至相邻节点最终导致网络性能的显著下降。针对现有复杂网络节点重要度评估模型未有效考虑雷暴扰动的问题,面向雷暴天气场景,将雷暴扰动特性纳入航路点重要度评估体系,利用博弈论方法对评估指标进行组合赋权,基于引力模型理论改进了TOPSIS(technique for order preference by similarity to an ideal solution)综合评价方法,建立基于博弈论-改进TOPSIS法的节点重要度评估模型,进而采用K中心点算法实现航路点聚类分级。以京津冀地区航班运行为例,对雷暴天气场景下的航路网络节点重要度进行评估,结果表明:在京津冀航路网络内,南部地区的航路点更易受雷暴天气影响且分布较为密集,该航路网络包含9个重要航路点,当航路网络中的重要航路点因雷暴影响而失效时,会对航路网络性能产生显著的负面影响。提出的基于博弈论-改进TOPSIS法的节点重要度评估模型可以有效识别出雷雨季节或雷暴高发地区航路网络中的重要航路点,从而为雷暴场景下航路网络结构优化与资源配置提供有效依据。
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.
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。
文摘利用实况资料和再分析资料,结合WRF(weather research and forecasting)模式对南通一次极端大风过程进行诊断分析及数值模拟。分析了该个例发生的天气形势背景和系统的水平、垂直结构,探究大风天气成因,并进一步对比不同参数化方案的模拟效果。结果表明:1)大风过程发生在高空深厚冷涡和地面强暖湿低压的环流背景下,上空存在不稳定层结和不稳定能量的累积;雷暴大风在12—13时经历了发展、成熟、消散3个阶段,飑线以碎块型的方式形成。2)3种微物理方案中,MG方案模拟出更大面积的层云、强回波和极端大风,模拟的最大地面阵风为44.47 m·s^(-1)。Lin方案较好地模拟出飑线的演变过程和垂直结构特征,模拟的最强上升气流达23.55 m·s^(-1),下沉气流达-13.21 m·s^(-1)。3)水平方向上,雷暴大风附近存在成熟的飑线地面中尺度系统,地面存在深厚冷池出流、变压梯度大值区和冷锋过境,它们共同促进了地面大风的生成。4)垂直方向上,对流单体上空高层辐散、低层辐合,存在强上升气流和水汽潜热释放;后侧的干空气蒸发和粒子的拖曳加强下沉运动,配合地面冷池出流和辐散气流,造成了极端大风天气。
