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dc.contributor.author
Cancelada, Maite  
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Salio, Paola Veronica  
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Vila, Daniel  
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Nesbitt, Stephen William  
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Vidal, Luciano  
dc.date.available
2021-10-18T17:13:50Z  
dc.date.issued
2020-01  
dc.identifier.citation
Cancelada, Maite; Salio, Paola Veronica; Vila, Daniel; Nesbitt, Stephen William; Vidal, Luciano; Backward adaptive brightness temperature threshold technique (BAB3T): A methodology to determine extreme convective initiation regions using satellite infrared imagery; Molecular Diversity Preservation International; Remote Sensing; 12; 2; 1-2020; 1-19  
dc.identifier.issn
2072-4292  
dc.identifier.uri
http://hdl.handle.net/11336/144124  
dc.description.abstract
Thunderstorms in southeastern South America (SESA) stand out in satellite observations as being among the strongest on Earth in terms of satellite-based convective proxies, such as lightning flash rate per storm, the prevalence for extremely tall, wide convective cores and broad stratiform regions. Accurately quantifying when and where strong convection is initiated presents great interest in operational forecasting and convective system process studies due to the relationship between convective storms and severe weather phenomena. This paper generates a novel methodology to determine convective initiation (CI) signatures associated with extreme convective systems, including extreme events. Based on the well-established area-overlapping technique, an adaptive brightness temperature threshold for identification and backward tracking with infrared data is introduced in order to better identify areas of deep convection associated with and embedded within larger cloud clusters. This is particularly important over SESA because ground-based weather radar observations are currently limited to particular areas. Extreme rain precipitation features (ERPFs) from Tropical Rainfall Measurement Mission are examined to quantify the full satellite-observed life cycle of extreme convective events, although this technique allows examination of other intense convection proxies such as the identification of overshooting tops. CI annual and diurnal cycles are analyzed and distinctive behaviors are observed for different regions over SESA. It is found that near principal mountain barriers, a bimodal diurnal CI distribution is observed denoting the existence of multiple CI triggers, while convective initiation over flat terrain has a maximum frequency in the afternoon.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Molecular Diversity Preservation International  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
ALGORITHMS  
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CONVECTIVE INITIATION  
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SATELLITE OBSERVATIONS  
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SEVERE WEATHER  
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Meteorología y Ciencias Atmosféricas  
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Ciencias de la Tierra y relacionadas con el Medio Ambiente  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
Backward adaptive brightness temperature threshold technique (BAB3T): A methodology to determine extreme convective initiation regions using satellite infrared imagery  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
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info:eu-repo/semantics/publishedVersion  
dc.date.updated
2021-09-07T18:14:46Z  
dc.journal.volume
12  
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2  
dc.journal.pagination
1-19  
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Suiza  
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Basel  
dc.description.fil
Fil: Cancelada, Maite. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina  
dc.description.fil
Fil: Salio, Paola Veronica. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina  
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Fil: Vila, Daniel. National Institute for Space Research; Brasil  
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Fil: Nesbitt, Stephen William. University of Illinois at Urbana; Estados Unidos  
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Fil: Vidal, Luciano. Ministerio de Defensa. Secretaria de Planeamiento. Servicio Meteorológico Nacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.journal.title
Remote Sensing  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2072-4292/12/2/337  
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info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3390/rs12020337