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Thunder Hours: How Old Methods Offer New Insights into Thunderstorm Climatology

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  • 1 Earth Networks, Germantown, Maryland
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Abstract

Lightning data are often used to measure the location and intensity of thunderstorms. This study presents 5 years of data from the Earth Networks Global Lightning Detection Network (ENGLN) in the form of thunder hours. A thunder hour is defined as an hour during which thunder can be heard from a given location, and thunder hours can be calculated for the entire globe. Thunder hours are an intuitive measure of thunderstorm frequency where the 1-h interval corresponds to the life-span of most thunderstorms, and the hourly temporal resolution of the data also represents long-lived systems well. Flash-density-observing systems are incredibly useful, but they have some drawbacks that limit how they can be used to quantify global thunderstorm activity on a climatological scale: flash density distributions derived from satellite observations must sacrifice a great deal of their spatial resolution in order to capture the diurnal convective cycle, and the detection efficiencies of ground-based lightning detection systems are not uniform in space or constant in time. Examining convective patterns in the context of thunder hours lends insight into thunderstorm activity without being heavily influenced by network performance, making thunder hours particularly useful for studying thunderstorm climatology. The ENGLN thunder hour dataset offers powerful utility to climatological studies involving lightning and thunderstorms. This study first shows that the ENGLN thunder hours dataset is very consistent with past measurements of global thunderstorm activity and the global electric circuit using only 5 years of data. Then, this study showcases thunder anomaly fields, designed to be analogous to temperature anomalies, which can be used to diagnose changes in thunderstorm frequency relative to the long-term mean in both time and space.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Elizabeth A. DiGangi, edigangi@earthnetworks.com

Abstract

Lightning data are often used to measure the location and intensity of thunderstorms. This study presents 5 years of data from the Earth Networks Global Lightning Detection Network (ENGLN) in the form of thunder hours. A thunder hour is defined as an hour during which thunder can be heard from a given location, and thunder hours can be calculated for the entire globe. Thunder hours are an intuitive measure of thunderstorm frequency where the 1-h interval corresponds to the life-span of most thunderstorms, and the hourly temporal resolution of the data also represents long-lived systems well. Flash-density-observing systems are incredibly useful, but they have some drawbacks that limit how they can be used to quantify global thunderstorm activity on a climatological scale: flash density distributions derived from satellite observations must sacrifice a great deal of their spatial resolution in order to capture the diurnal convective cycle, and the detection efficiencies of ground-based lightning detection systems are not uniform in space or constant in time. Examining convective patterns in the context of thunder hours lends insight into thunderstorm activity without being heavily influenced by network performance, making thunder hours particularly useful for studying thunderstorm climatology. The ENGLN thunder hour dataset offers powerful utility to climatological studies involving lightning and thunderstorms. This study first shows that the ENGLN thunder hours dataset is very consistent with past measurements of global thunderstorm activity and the global electric circuit using only 5 years of data. Then, this study showcases thunder anomaly fields, designed to be analogous to temperature anomalies, which can be used to diagnose changes in thunderstorm frequency relative to the long-term mean in both time and space.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Elizabeth A. DiGangi, edigangi@earthnetworks.com
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