Distinctive Signals in 1‐min Observations of Overshooting Tops and Lightning Activity in a Severe Supercell Thunderstorm

Abstract

This work examines a severe weather event that took place over central Argentina on 11 December 2018. The evolution of the storm from its initiation, rapid organization into a supercell, and eventual decay was analyzed with high-temporal resolution observations. This work provides insight into the spatio-temporal co-evolution of storm kinematics (updraft area and lifespan), cloud-top cooling rates, and lightning production that led to severe weather. The analyzed storm presented two convective periods with associated severe weather. An overall decrease in cloud-top local minima IR brightness temperature (MinIR) and lightning jump (LJ) preceded both periods. LJs provided the highest lead time to the occurrence of severe weather, with the ground-based lightning networks providing the maximum warning time of around 30 min. Lightning flash counts from the Geostationary Lightning Mapper (GLM) were underestimated when compared to detections from ground-based lightning networks. Among the possible reasons for GLM's lower detection efficiency were an optically dense medium located above lightning sources and the occurrence of flashes smaller than GLM's footprint. The minimum MinIR provided the shorter warning time to severe weather occurrence. However, the secondary minima in MinIR that preceded the absolute minima improved this warning time by more than 10 min. Trends in MinIR for time scales shorter than 6 min revealed shorter cycles of fast cooling and warming, which provided information about the lifecycle of updrafts within the storm. The advantages of using observations with high-temporal resolution to analyze the evolution and intensity of convective storms are discussed. Plain Language Summary Severe thunderstorms can have distinctive signals in satellite observations. Cloud-top temperature minima are one of the most studied metrics as a severe weather indicator. The newest geostationary weather satellites (GOES-16/17) offer a unique opportunity to study storms through their rapid-scan mode and lightning detector. In this study, we analyzed high-temporal (1-min) observations of cloud-top temperature and lightning detected from space and the surface to study the evolution of a severe thunderstorm that took place over central Argentina on 11 December 2018. Overall, cloud-top temperature minimum and fast increases in lightning activity preceded the occurrence of severe weather. The signature present in lightning observations provided the highest severe weather lead time, with ground-based sensors providing the maximum warning time (~30 min). A cloud-top temperature absolute minimum provided the shortest warning time, whereas secondary minima, that preceded the absolute minima, improved the warning time by more than 10 min. This improvement in lead time can result in better societal preparedness for imminent hazardous weather where no ground-based lightning observations are available. Observations with high-temporal resolution also show cycles of fast cloud-top cooling and warming that can provide important insight o...

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“…In particular, several recent studies are being made based on the RELAMPAGO field-campaign data (Nesbitt et al 2021). For example, Borque et al (2020) (hereafter B20) examined the evolution of a convective cell that took place on 11 December 2018, using the operational weather radar located in Córdoba City which is part of the Argentinean National System of Meteorological Radars (De Elía et al, 2017), and the spatio-temporal distribution lightning strikes derived from the RELAMPAGO 3D Lightning Mapping Array (LMA) and the Geostationary Lightning Mapper (GLM) on board of the GOES-16 satellite. They found that a decrease in cloud top temperature (CTT) and an increase in the lightning activity precede two convective periods with associated severe weather.…”

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