Wednesday, 30 August 2023: 11:30 AM
Great Lakes BC (Hyatt Regency Minneapolis)
Lightning responds to kinematic changes within the mixed-phase region of thunderstorms, a relationship applied by operational forecasting where rapid increases in lightning are used to monitor storm intensification. Thunderstorm electrification is a product of the microphysical environment; lightning is intimately related to microphysical conditions within the thundercloud. Microphysical conditions are also profoundly connected to thunderstorm kinematics via precipitation mode, vertical draft structure, and cold pool evolution. However, the temporal evolution of these relationships is underdeveloped.
In this study, we leverage Texas Tech University’s surface StickNet measurements to complement the ground-based lightning data from the Lightning Mapping Array (LMA) and WSR-88D radar data to quantify lightning activity alongside the temporal evolution of microphysical signals in response to kinematic shifts in Southeastern US thunderstorms. Using the Tracking and Object-based Analysis of Clouds (tobac) open-source Python tool, a Lagrangian approach is taken to tracking all thunderstorm cells on 13 case days from the VORTEX-SE and PERiLS field campaigns.
Previously, this work has shown the maximum in columns of specific differential phase (KDP) in a 3km depth above the melting level are 2.5 times more intense in thunderstorm cells producing lightning than those without lightning in the same storm day. We examine the time delay between microphysical signals and increases in lightning activity. In preliminary results, we find that the onset of the coldpool (indicated via the theta-E gradient) precedes the growth of the glaciation signal in KDP, followed also by an increase in lightning. This increase in lightning can be seen in both small and large flashes. Linking the onset of the cold pool to developments in the microphysical signals and lightning observations is crucial for improving our understanding of thunderstorm behavior and enhancing operational forecasting of storm intensity.
In this study, we leverage Texas Tech University’s surface StickNet measurements to complement the ground-based lightning data from the Lightning Mapping Array (LMA) and WSR-88D radar data to quantify lightning activity alongside the temporal evolution of microphysical signals in response to kinematic shifts in Southeastern US thunderstorms. Using the Tracking and Object-based Analysis of Clouds (tobac) open-source Python tool, a Lagrangian approach is taken to tracking all thunderstorm cells on 13 case days from the VORTEX-SE and PERiLS field campaigns.
Previously, this work has shown the maximum in columns of specific differential phase (KDP) in a 3km depth above the melting level are 2.5 times more intense in thunderstorm cells producing lightning than those without lightning in the same storm day. We examine the time delay between microphysical signals and increases in lightning activity. In preliminary results, we find that the onset of the coldpool (indicated via the theta-E gradient) precedes the growth of the glaciation signal in KDP, followed also by an increase in lightning. This increase in lightning can be seen in both small and large flashes. Linking the onset of the cold pool to developments in the microphysical signals and lightning observations is crucial for improving our understanding of thunderstorm behavior and enhancing operational forecasting of storm intensity.
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