Thunderstorms life cycle observation: satellite multi-channel model for warning system
| Ano de defesa: | 2017 |
|---|---|
| Autor(a) principal: | |
| Orientador(a): | |
| Banca de defesa: | , , |
| Tipo de documento: | Dissertação |
| Tipo de acesso: | Acesso aberto |
| Idioma: | eng |
| Instituição de defesa: |
Instituto Nacional de Pesquisas Espaciais (INPE)
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação do INPE em Meteorologia
|
| Departamento: |
Não Informado pela instituição
|
| País: |
BR
|
| Link de acesso: | http://urlib.net/sid.inpe.br/mtc-m21b/2017/07.03.18.29 |
Resumo: | The principal objective of this research is to identify typical cloud-top signatures of incipient thunderstorms and its early electrification process in satellite multi-channel observations as means of building a conceptual model of thunderstorm detection based on brightness temperature and electrification life cycle association. The methods toward the principal objective analyzed the data set of CHUVA-Vale field campaign from 01 November 2011 to 31 March 2012, including multi-channel observations from the SEVIRI infrared fields, a radar-lightning co-located data set and a sample of 40 compact isolated thunderstorms. The sequence for each infrared field comprises the parallax correction in satellite observations; the co-location of satellite and radar-lightning data; the selection of an evaluation area for thunderstorm detection, and the construction of brightness temperature relative cumulative-frequency distributions along with respective thresholds analysis and validation. Consequently, 4 thunderstorm predictors used in tandem to detect the largest differentiation among the lightning time steps and significant cumulus cloud and electrification intensification, resulted throughout parameters in corresponding brightness temperature histograms whose thresholds are as follows: IF1 or Predictor 1= Ch05-Ch06: (6.2 − 7.3) $\mu$m: Tbd $\geq$ −14.0 K; IF2 or Predictor 2= 10.8 $\mu$m: Tb $\leq$ +263.0 K, IF3 or Predictor 3= (6.2 − 10.8) $\mu$m: Tbd $\geq$ −14.0 K and IF4 or Predictor 4= (8.7−10.8)−(10.8−12.0) $\mu$m: Tbd $\geq$ 0 K. Additionally, an independent 2-day validation test indicated that the conceptual model has a higher probability of lightning detection for the interval of index sums from 16 to 12 because of the higher POD and lower FAR. Also the results indicated that the conceptual model has a lower probability of lightning detection for the interval of index sums from 8 to 4 because of the lower POD and higher FAR. This representative behavior of the thunderstorm electrification life cycle in geostationary satellite multi-channel observations will allow a potential development of nowcasting tools at the boundary of subtropical regions using data from the Meteosat Second Generation Satellite, and with the perspective to use in the near future, the data from the Geostationary Operational Environmental Satellite-R and the imminent Meteosat Third Generation Satellite. |
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info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisThunderstorms life cycle observation: satellite multi-channel model for warning systemObservação do ciclo de vida de electricação das tempestades: aplicação de multicanais para modelo conceitual de nowcasting2017-08-03Luiz Augusto Toledo MachadoJuan Carlos CeballosEnrique Viera MattosStephen William NesbittLina Esther Rivelli ZeaInstituto Nacional de Pesquisas Espaciais (INPE)Programa de Pós-Graduação do INPE em MeteorologiaINPEBRnowcastingthunderstormseletrificationsatellitemulti-channelnowcastingtempestadeseletrificaçãosatélitemulticanaisThe principal objective of this research is to identify typical cloud-top signatures of incipient thunderstorms and its early electrification process in satellite multi-channel observations as means of building a conceptual model of thunderstorm detection based on brightness temperature and electrification life cycle association. The methods toward the principal objective analyzed the data set of CHUVA-Vale field campaign from 01 November 2011 to 31 March 2012, including multi-channel observations from the SEVIRI infrared fields, a radar-lightning co-located data set and a sample of 40 compact isolated thunderstorms. The sequence for each infrared field comprises the parallax correction in satellite observations; the co-location of satellite and radar-lightning data; the selection of an evaluation area for thunderstorm detection, and the construction of brightness temperature relative cumulative-frequency distributions along with respective thresholds analysis and validation. Consequently, 4 thunderstorm predictors used in tandem to detect the largest differentiation among the lightning time steps and significant cumulus cloud and electrification intensification, resulted throughout parameters in corresponding brightness temperature histograms whose thresholds are as follows: IF1 or Predictor 1= Ch05-Ch06: (6.2 − 7.3) $\mu$m: Tbd $\geq$ −14.0 K; IF2 or Predictor 2= 10.8 $\mu$m: Tb $\leq$ +263.0 K, IF3 or Predictor 3= (6.2 − 10.8) $\mu$m: Tbd $\geq$ −14.0 K and IF4 or Predictor 4= (8.7−10.8)−(10.8−12.0) $\mu$m: Tbd $\geq$ 0 K. Additionally, an independent 2-day validation test indicated that the conceptual model has a higher probability of lightning detection for the interval of index sums from 16 to 12 because of the higher POD and lower FAR. Also the results indicated that the conceptual model has a lower probability of lightning detection for the interval of index sums from 8 to 4 because of the lower POD and higher FAR. This representative behavior of the thunderstorm electrification life cycle in geostationary satellite multi-channel observations will allow a potential development of nowcasting tools at the boundary of subtropical regions using data from the Meteosat Second Generation Satellite, and with the perspective to use in the near future, the data from the Geostationary Operational Environmental Satellite-R and the imminent Meteosat Third Generation Satellite.O objetivo principal desta pesquisa é identificar um conjunto de assinaturas típicas do topo das nuvens que permitam prever o processo de eletrificação quando as nuvens se transformam em tempestades. Através das combinações de canais dos imageadores de satélites geoestacionários este trabalho visa construir um modelo conceitual de detecção de início dos processos de eletrificação de tempestades utilizando a tendência dos histogramas de temperatura de brilho (ou diferença de canais). Para construção deste modelo conceitual foram utilizadas observações em diferentes canais infravermelhos co-localizados com observações de radar polarimétrico banda X e de medidas do LMA (Lightning Mapping Array) que consiste de fontes emitidas pelos relâmpagos em Very Higher Frequency. Foram selecionadas 40 tempestades compactas durante a campanha CHUVA-Vale para a elaboração do modelo conceitual e posteriormente os resultados foram testados em casos independentes. A sequência dos procedimentos metodológicos para campo de interesse compreende a correção da paralaxe nas observações de satélite; a co-localização com os dados de radar e descargas elétricas; a seleção de uma área de avaliação para detecção das tempestades e a construção de distribuições de frequência relativa-cumulativa de temperatura de brilho (ou diferenças) e a definição de limiares para a construção das frequências cumuladas. Quatro canais ou diferença de canais foram selecionados para detectar o processo de eletrificação da nuvem. Os seguintes preditores foram utilizados: IF1 or Predictor 1= (6.2 − 7.3) $\mu$m: Tbd $\geq$−14.0 K; IF2 or Predictor 2= 10.8 $\mu$m: Tb $\leq$+223.0 K, IF3 or Predictor 3= (6.2 − 10.8) $\mu$m: Tbd $\geq$−14.0 K and IF4 or Predictor 4= (8.7 − 10.8) − (10.8 − 12.0) $\mu$m: Tbd $\geq$ 0 K. Esse conjunto de preditores foi utilizado em função das propriedades que esses canais têm para descrever os processos microfísicos das nuvens. Após a definição do modelo, um teste de validação independente de 2 dias permitiu definir as incertezas do modelo conceitual. O emprego dos campos selecionados quando empregados juntos melhoram significativamente a previsibilidade do processo de eletrificação da nuvem. Este comportamento representativo do ciclo de vida da eletrificação das tempestades através de combinações de canais de satélite geoestacionário permitirá o desenvolvimento de ferramentas de previsão a curtíssimo prazo nas regiões tropicais e subtropicais usando dados do Meteosat Second Generation e, em breve, do Geostationary Operational Environmental Satellite-R e do futuro Meteosat Third Generation Satellite.http://urlib.net/sid.inpe.br/mtc-m21b/2017/07.03.18.29info:eu-repo/semantics/openAccessengreponame:Biblioteca Digital de Teses e Dissertações do INPEinstname:Instituto Nacional de Pesquisas Espaciais (INPE)instacron:INPE2021-07-31T06:55:28Zoai:urlib.net:sid.inpe.br/mtc-m21b/2017/07.03.18.29.54-0Biblioteca Digital de Teses e Dissertaçõeshttp://bibdigital.sid.inpe.br/PUBhttp://bibdigital.sid.inpe.br/col/iconet.com.br/banon/2003/11.21.21.08/doc/oai.cgiopendoar:32772021-07-31 06:55:28.478Biblioteca Digital de Teses e Dissertações do INPE - Instituto Nacional de Pesquisas Espaciais (INPE)false |
| dc.title.en.fl_str_mv |
Thunderstorms life cycle observation: satellite multi-channel model for warning system |
| dc.title.alternative.pt.fl_str_mv |
Observação do ciclo de vida de electricação das tempestades: aplicação de multicanais para modelo conceitual de nowcasting |
| title |
Thunderstorms life cycle observation: satellite multi-channel model for warning system |
| spellingShingle |
Thunderstorms life cycle observation: satellite multi-channel model for warning system Lina Esther Rivelli Zea |
| title_short |
Thunderstorms life cycle observation: satellite multi-channel model for warning system |
| title_full |
Thunderstorms life cycle observation: satellite multi-channel model for warning system |
| title_fullStr |
Thunderstorms life cycle observation: satellite multi-channel model for warning system |
| title_full_unstemmed |
Thunderstorms life cycle observation: satellite multi-channel model for warning system |
| title_sort |
Thunderstorms life cycle observation: satellite multi-channel model for warning system |
| author |
Lina Esther Rivelli Zea |
| author_facet |
Lina Esther Rivelli Zea |
| author_role |
author |
| dc.contributor.advisor1.fl_str_mv |
Luiz Augusto Toledo Machado |
| dc.contributor.referee1.fl_str_mv |
Juan Carlos Ceballos |
| dc.contributor.referee2.fl_str_mv |
Enrique Viera Mattos |
| dc.contributor.referee3.fl_str_mv |
Stephen William Nesbitt |
| dc.contributor.author.fl_str_mv |
Lina Esther Rivelli Zea |
| contributor_str_mv |
Luiz Augusto Toledo Machado Juan Carlos Ceballos Enrique Viera Mattos Stephen William Nesbitt |
| dc.description.abstract.por.fl_txt_mv |
The principal objective of this research is to identify typical cloud-top signatures of incipient thunderstorms and its early electrification process in satellite multi-channel observations as means of building a conceptual model of thunderstorm detection based on brightness temperature and electrification life cycle association. The methods toward the principal objective analyzed the data set of CHUVA-Vale field campaign from 01 November 2011 to 31 March 2012, including multi-channel observations from the SEVIRI infrared fields, a radar-lightning co-located data set and a sample of 40 compact isolated thunderstorms. The sequence for each infrared field comprises the parallax correction in satellite observations; the co-location of satellite and radar-lightning data; the selection of an evaluation area for thunderstorm detection, and the construction of brightness temperature relative cumulative-frequency distributions along with respective thresholds analysis and validation. Consequently, 4 thunderstorm predictors used in tandem to detect the largest differentiation among the lightning time steps and significant cumulus cloud and electrification intensification, resulted throughout parameters in corresponding brightness temperature histograms whose thresholds are as follows: IF1 or Predictor 1= Ch05-Ch06: (6.2 − 7.3) $\mu$m: Tbd $\geq$ −14.0 K; IF2 or Predictor 2= 10.8 $\mu$m: Tb $\leq$ +263.0 K, IF3 or Predictor 3= (6.2 − 10.8) $\mu$m: Tbd $\geq$ −14.0 K and IF4 or Predictor 4= (8.7−10.8)−(10.8−12.0) $\mu$m: Tbd $\geq$ 0 K. Additionally, an independent 2-day validation test indicated that the conceptual model has a higher probability of lightning detection for the interval of index sums from 16 to 12 because of the higher POD and lower FAR. Also the results indicated that the conceptual model has a lower probability of lightning detection for the interval of index sums from 8 to 4 because of the lower POD and higher FAR. This representative behavior of the thunderstorm electrification life cycle in geostationary satellite multi-channel observations will allow a potential development of nowcasting tools at the boundary of subtropical regions using data from the Meteosat Second Generation Satellite, and with the perspective to use in the near future, the data from the Geostationary Operational Environmental Satellite-R and the imminent Meteosat Third Generation Satellite. O objetivo principal desta pesquisa é identificar um conjunto de assinaturas típicas do topo das nuvens que permitam prever o processo de eletrificação quando as nuvens se transformam em tempestades. Através das combinações de canais dos imageadores de satélites geoestacionários este trabalho visa construir um modelo conceitual de detecção de início dos processos de eletrificação de tempestades utilizando a tendência dos histogramas de temperatura de brilho (ou diferença de canais). Para construção deste modelo conceitual foram utilizadas observações em diferentes canais infravermelhos co-localizados com observações de radar polarimétrico banda X e de medidas do LMA (Lightning Mapping Array) que consiste de fontes emitidas pelos relâmpagos em Very Higher Frequency. Foram selecionadas 40 tempestades compactas durante a campanha CHUVA-Vale para a elaboração do modelo conceitual e posteriormente os resultados foram testados em casos independentes. A sequência dos procedimentos metodológicos para campo de interesse compreende a correção da paralaxe nas observações de satélite; a co-localização com os dados de radar e descargas elétricas; a seleção de uma área de avaliação para detecção das tempestades e a construção de distribuições de frequência relativa-cumulativa de temperatura de brilho (ou diferenças) e a definição de limiares para a construção das frequências cumuladas. Quatro canais ou diferença de canais foram selecionados para detectar o processo de eletrificação da nuvem. Os seguintes preditores foram utilizados: IF1 or Predictor 1= (6.2 − 7.3) $\mu$m: Tbd $\geq$−14.0 K; IF2 or Predictor 2= 10.8 $\mu$m: Tb $\leq$+223.0 K, IF3 or Predictor 3= (6.2 − 10.8) $\mu$m: Tbd $\geq$−14.0 K and IF4 or Predictor 4= (8.7 − 10.8) − (10.8 − 12.0) $\mu$m: Tbd $\geq$ 0 K. Esse conjunto de preditores foi utilizado em função das propriedades que esses canais têm para descrever os processos microfísicos das nuvens. Após a definição do modelo, um teste de validação independente de 2 dias permitiu definir as incertezas do modelo conceitual. O emprego dos campos selecionados quando empregados juntos melhoram significativamente a previsibilidade do processo de eletrificação da nuvem. Este comportamento representativo do ciclo de vida da eletrificação das tempestades através de combinações de canais de satélite geoestacionário permitirá o desenvolvimento de ferramentas de previsão a curtíssimo prazo nas regiões tropicais e subtropicais usando dados do Meteosat Second Generation e, em breve, do Geostationary Operational Environmental Satellite-R e do futuro Meteosat Third Generation Satellite. |
| description |
The principal objective of this research is to identify typical cloud-top signatures of incipient thunderstorms and its early electrification process in satellite multi-channel observations as means of building a conceptual model of thunderstorm detection based on brightness temperature and electrification life cycle association. The methods toward the principal objective analyzed the data set of CHUVA-Vale field campaign from 01 November 2011 to 31 March 2012, including multi-channel observations from the SEVIRI infrared fields, a radar-lightning co-located data set and a sample of 40 compact isolated thunderstorms. The sequence for each infrared field comprises the parallax correction in satellite observations; the co-location of satellite and radar-lightning data; the selection of an evaluation area for thunderstorm detection, and the construction of brightness temperature relative cumulative-frequency distributions along with respective thresholds analysis and validation. Consequently, 4 thunderstorm predictors used in tandem to detect the largest differentiation among the lightning time steps and significant cumulus cloud and electrification intensification, resulted throughout parameters in corresponding brightness temperature histograms whose thresholds are as follows: IF1 or Predictor 1= Ch05-Ch06: (6.2 − 7.3) $\mu$m: Tbd $\geq$ −14.0 K; IF2 or Predictor 2= 10.8 $\mu$m: Tb $\leq$ +263.0 K, IF3 or Predictor 3= (6.2 − 10.8) $\mu$m: Tbd $\geq$ −14.0 K and IF4 or Predictor 4= (8.7−10.8)−(10.8−12.0) $\mu$m: Tbd $\geq$ 0 K. Additionally, an independent 2-day validation test indicated that the conceptual model has a higher probability of lightning detection for the interval of index sums from 16 to 12 because of the higher POD and lower FAR. Also the results indicated that the conceptual model has a lower probability of lightning detection for the interval of index sums from 8 to 4 because of the lower POD and higher FAR. This representative behavior of the thunderstorm electrification life cycle in geostationary satellite multi-channel observations will allow a potential development of nowcasting tools at the boundary of subtropical regions using data from the Meteosat Second Generation Satellite, and with the perspective to use in the near future, the data from the Geostationary Operational Environmental Satellite-R and the imminent Meteosat Third Generation Satellite. |
| publishDate |
2017 |
| dc.date.issued.fl_str_mv |
2017-08-03 |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| status_str |
publishedVersion |
| format |
masterThesis |
| dc.identifier.uri.fl_str_mv |
http://urlib.net/sid.inpe.br/mtc-m21b/2017/07.03.18.29 |
| url |
http://urlib.net/sid.inpe.br/mtc-m21b/2017/07.03.18.29 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.publisher.none.fl_str_mv |
Instituto Nacional de Pesquisas Espaciais (INPE) |
| dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação do INPE em Meteorologia |
| dc.publisher.initials.fl_str_mv |
INPE |
| dc.publisher.country.fl_str_mv |
BR |
| publisher.none.fl_str_mv |
Instituto Nacional de Pesquisas Espaciais (INPE) |
| dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações do INPE instname:Instituto Nacional de Pesquisas Espaciais (INPE) instacron:INPE |
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Biblioteca Digital de Teses e Dissertações do INPE |
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Biblioteca Digital de Teses e Dissertações do INPE |
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Instituto Nacional de Pesquisas Espaciais (INPE) |
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INPE |
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INPE |
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Biblioteca Digital de Teses e Dissertações do INPE - Instituto Nacional de Pesquisas Espaciais (INPE) |
| repository.mail.fl_str_mv |
|
| publisher_program_txtF_mv |
Programa de Pós-Graduação do INPE em Meteorologia |
| contributor_advisor1_txtF_mv |
Luiz Augusto Toledo Machado |
| _version_ |
1706805040767827968 |