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The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude
Optical space‐based lightning sensors such as the Geostationary Lightning Mapper (GLM) detect and geolocate lightning by recording rapid changes in cloud top illumination. While lightning locations can be determined to within a pixel on the GLM imaging array, these instruments are not individually a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9285908/ https://www.ncbi.nlm.nih.gov/pubmed/35865262 http://dx.doi.org/10.1029/2021EA001944 |
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author | Peterson, Michael Light, Tracy E. L. Mach, Douglas |
author_facet | Peterson, Michael Light, Tracy E. L. Mach, Douglas |
author_sort | Peterson, Michael |
collection | PubMed |
description | Optical space‐based lightning sensors such as the Geostationary Lightning Mapper (GLM) detect and geolocate lightning by recording rapid changes in cloud top illumination. While lightning locations can be determined to within a pixel on the GLM imaging array, these instruments are not individually able to natively report lightning altitude. It has previously been shown that thunderclouds are illuminated differently based on the altitude of the optical source. In this study, we examine how altitude information can be extracted from the spatial distributions of GLM energy recorded from each optical pulse. We match GLM “groups” with Lightning Mapping Array (LMA) source data that accurately report the 3‐D positions of coincident Radio‐Frequency (RF) emitters. We then use machine learning methods to predict the mean LMA source altitudes matched to GLM groups using metrics from the optical data that describe the amplitude, breadth, and texture of the group spatial energy distribution. The resulting model can predict the LMA mean source altitude from GLM group data with a median absolute error of <1.5 km, which is sufficient to determine the location of the charge layer where the optical energy originated. This model is able to capture changes to the source altitude distribution in response to convective processes in the thunderstorm, and the GLM predictions can reveal the vertical structure of individual flashes ‐ enabling 3‐D flash geolocation with GLM for the first time. Future work will account for differences in thunderstorm charge/precipitation structures and viewing angle across the GLM Field of View. |
format | Online Article Text |
id | pubmed-9285908 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92859082022-07-19 The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude Peterson, Michael Light, Tracy E. L. Mach, Douglas Earth Space Sci Research Article Optical space‐based lightning sensors such as the Geostationary Lightning Mapper (GLM) detect and geolocate lightning by recording rapid changes in cloud top illumination. While lightning locations can be determined to within a pixel on the GLM imaging array, these instruments are not individually able to natively report lightning altitude. It has previously been shown that thunderclouds are illuminated differently based on the altitude of the optical source. In this study, we examine how altitude information can be extracted from the spatial distributions of GLM energy recorded from each optical pulse. We match GLM “groups” with Lightning Mapping Array (LMA) source data that accurately report the 3‐D positions of coincident Radio‐Frequency (RF) emitters. We then use machine learning methods to predict the mean LMA source altitudes matched to GLM groups using metrics from the optical data that describe the amplitude, breadth, and texture of the group spatial energy distribution. The resulting model can predict the LMA mean source altitude from GLM group data with a median absolute error of <1.5 km, which is sufficient to determine the location of the charge layer where the optical energy originated. This model is able to capture changes to the source altitude distribution in response to convective processes in the thunderstorm, and the GLM predictions can reveal the vertical structure of individual flashes ‐ enabling 3‐D flash geolocation with GLM for the first time. Future work will account for differences in thunderstorm charge/precipitation structures and viewing angle across the GLM Field of View. John Wiley and Sons Inc. 2022-01-10 2022-01 /pmc/articles/PMC9285908/ /pubmed/35865262 http://dx.doi.org/10.1029/2021EA001944 Text en © 2021. The Authors. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Article Peterson, Michael Light, Tracy E. L. Mach, Douglas The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude |
title | The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude |
title_full | The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude |
title_fullStr | The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude |
title_full_unstemmed | The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude |
title_short | The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude |
title_sort | illumination of thunderclouds by lightning: 3. retrieving optical source altitude |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9285908/ https://www.ncbi.nlm.nih.gov/pubmed/35865262 http://dx.doi.org/10.1029/2021EA001944 |
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