2021•Unpublished venueOpen access

Lightning Geolocation and Classification During the RELAMPAGO Field Campaign

Andre Lucas Antunes de Sa, Robert Andrew Marshall, Wiebke Deierling, Austin Sousa

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Abstract

Severe weather forecasting is an important tool for mitigating damages brought by intense lightning, large hail, heavy precipitation, strong winds, or tornadoes during thunderstorms, yet the reliability of such forecasts suffers from our limited understanding of the severe weather generative processes inside thunderclouds. With an increasing knowledge of the occurrence context of distinct types of lightning within storms, lightning remote sensing may elucidate the kinematic and microphysical environment where severe weather initiates. In particular, distinct energetic intra-cloud (IC) lightning discharges, compact intra-cloud lightning discharges [CID; e.g., Nag and Rakov, 2010] and energetic intra-cloud pulses [EIP; e.g., Lyu et al., 2015], have been shown to have different occurrence contexts, making them strong candidates for thunderstorm remote sensing research. In this study, observations from the RELAMPAGO field campaign in Argentina (November 1 to December 12th 2018) are used to determine lightning flash rates and the prevalence of different energetic lightning types in RELAMPAGO storms, enabling further research on the link between lightning activity and severe weather production inside thunderstorms.Lightning events during RELAMPAGO were observed by a deployed array of four Low-Frequency (LF, ~1-400 kHz) radio receivers. Using time of arrival, magnetic direction finding, and peak amplitude for each observed event at different stations, lightning source locations are estimated using a statistical least squares filter, along with clock and site errors associated with the receivers. Return stroke peak current for each event is also estimated in the filter, using an atmospheric attenuation observation model. The energetic lightning events in the campaign are then classified automatically between cloud-to-ground (CG), IC, CID or EIP, following an improved parametrization scheme originally proposed by Lyu et al. [2015]. In this paper we present the geolocation and classification of RELAMPAGO lightning events, and we also provide an analysis of lightning flash rates during the campaign. A few individual thunderstorm case studies are also discussed, which are augmented by other meteorological data from dual-polarimetric radar, hailpads, and other sources.

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Severe weather forecasting is an important tool for mitigating damages brought by intense lightning, large hail, heavy precipitation, strong winds, or tornadoes during thunderstorms, yet the reliability of such forecasts suffers from our limited understanding of the severe weather generative processes inside thunderclouds. With an increasing knowledge of the occurrence context of distinct types of lightning within storms, lightning remote sensing may elucidate the kinematic and microphysical environment where severe weather initiates. In particular, distinct energetic intra-cloud (IC) lightning discharges, compact intra-cloud lightning discharges [CID; e.g., Nag and Rakov, 2010] and energetic intra-cloud pulses [EIP; e.g., Lyu et al., 2015], have been shown to have different occurrence contexts, making them strong candidates for thunderstorm remote sensing research. In this study, observations from the RELAMPAGO field campaign in Argentina (November 1 to December 12th 2018) are used to determine lightning flash rates and the prevalence of different energetic lightning types in RELAMPAGO storms, enabling further research on the link between lightning activity and severe weather production inside thunderstorms.Lightning events during RELAMPAGO were observed by a deployed array of four Low-Frequency (LF, ~1-400 kHz) radio receivers. Using time of arrival, magnetic direction finding, and peak amplitude for each observed event at different stations, lightning source locations are estimated using a statistical least squares filter, along with clock and site errors associated with the receivers. Return stroke peak current for each event is also estimated in the filter, using an atmospheric attenuation observation model. The energetic lightning events in the campaign are then classified automatically between cloud-to-ground (CG), IC, CID or EIP, following an improved parametrization scheme originally proposed by Lyu et al. [2015]. In this paper we present the geolocation and classification of RELAMPAGO lightning events, and we also provide an analysis of lightning flash rates during the campaign. A few individual thunderstorm case studies are also discussed, which are augmented by other meteorological data from dual-polarimetric radar, hailpads, and other sources.

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Available abstract

Severe weather forecasting is an important tool for mitigating damages brought by intense lightning, large hail, heavy precipitation, strong winds, or tornadoes during thunderstorms, yet the reliability of such forecasts suffers from our limited understanding of the severe weather generative processes inside thunderclouds. With an increasing knowledge of the occurrence context of distinct types of lightning within storms, lightning remote sensing may elucidate the kinematic and microphysical environment where severe weather initiates. In particular, distinct energetic intra-cloud (IC) lightning discharges, compact intra-cloud lightning discharges [CID; e.g., Nag and Rakov, 2010] and energetic intra-cloud pulses [EIP; e.g., Lyu et al., 2015], have been shown to have different occurrence contexts, making them strong candidates for thunderstorm remote sensing research. In this study, observations from the RELAMPAGO field campaign in Argentina (November 1 to December 12th 2018) are used to determine lightning flash rates and the prevalence of different energetic lightning types in RELAMPAGO storms, enabling further research on the link between lightning activity and severe weather production inside thunderstorms.Lightning events during RELAMPAGO were observed by a deployed array of four Low-Frequency (LF, ~1-400 kHz) radio receivers. Using time of arrival, magnetic direction finding, and peak amplitude for each observed event at different stations, lightning source locations are estimated using a statistical least squares filter, along with clock and site errors associated with the receivers. Return stroke peak current for each event is also estimated in the filter, using an atmospheric attenuation observation model. The energetic lightning events in the campaign are then classified automatically between cloud-to-ground (CG), IC, CID or EIP, following an improved parametrization scheme originally proposed by Lyu et al. [2015]. In this paper we present the geolocation and classification of RELAMPAGO lightning events, and we also provide an analysis of lightning flash rates during the campaign. A few individual thunderstorm case studies are also discussed, which are augmented by other meteorological data from dual-polarimetric radar, hailpads, and other sources.

Key concepts: Thunderstorm, Lightning (connector), Meteorology, Context (archaeology), Severe weather, Storm, Lightning detection, Environmental science

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