{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:28:36Z","timestamp":1760146116159,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2024,10,11]],"date-time":"2024-10-11T00:00:00Z","timestamp":1728604800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordination for the Improvement of Higher Education Personnel","doi-asserted-by":"publisher","award":["001"],"award-info":[{"award-number":["001"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The study aims to develop vertical radar reflectivity profiles based on lightning density data from the Geostationary Lightning Mapper (GLM) on the GOES-16 satellite in the subtropical region of Brazil. The primary objective is to improve the assimilation of lightning data in numerical weather prediction models. The methodology involves the analysis of polarimetric radar data from Chapec\u00f3-SC and Jaraguari-MS, spanning from January 2019 to December 2023, and their correlation with lightning data from the GLM. Radar reflectivity profiles were created for different lightning density classes, categorized into six classes based on geometric progression. Results show a significant relationship between lightning activity and radar reflectivity, with distinct profiles for convective and stratiform events. These findings demonstrate the potential of using GLM data to enhance short-term weather forecasting, particularly for severe weather events. The study concludes that the integration of GLM data into weather models can lead to more accurate predictions of intense precipitation events, contributing to better preparedness and response strategies.<\/jats:p>","DOI":"10.3390\/rs16203767","type":"journal-article","created":{"date-parts":[[2024,10,11]],"date-time":"2024-10-11T03:53:47Z","timestamp":1728618827000},"page":"3767","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Development of Vertical Radar Reflectivity Profiles Based on Lightning Density Using the Geostationary Lightning Mapper Dataset in the Subtropical Region of Brazil"],"prefix":"10.3390","volume":"16","author":[{"given":"Tiago Bentes","family":"Mand\u00fa","sequence":"first","affiliation":[{"name":"National Institute for Space Research (INPE), Cachoeira Paulista 12630-970, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0215-1131","authenticated-orcid":false,"given":"Laurizio Emanuel Ribeiro","family":"Alves","sequence":"additional","affiliation":[{"name":"National Institute for Space Research (INPE), Cachoeira Paulista 12630-970, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4823-3714","authenticated-orcid":false,"given":"\u00c9der Paulo","family":"Vendrasco","sequence":"additional","affiliation":[{"name":"National Institute for Space Research (INPE), Cachoeira Paulista 12630-970, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2338-3871","authenticated-orcid":false,"given":"Thiago Souza","family":"Biscaro","sequence":"additional","affiliation":[{"name":"National Institute for Space Research (INPE), Cachoeira Paulista 12630-970, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,11]]},"reference":[{"key":"ref_1","first-page":"916","article-title":"Seasonal precipitation forecasts: Agro-ecological knowledge among rural Kalahari communities","volume":"6","author":"Mogotsi","year":"2011","journal-title":"Afr. 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