Qualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do Sul

Detalhes bibliográficos
Autor(a) principal: Bernardi, Ewerthon Cezar Schiavo
Data de Publicação: 2016
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional Manancial UFSM
Texto Completo: http://repositorio.ufsm.br/handle/1/7658
Resumo: Understanding the spatial and temporal rainfall occurrence, improves the water resources management, both in order to prevent losses related to the occurrence of floods and droughts events, as in relation to the supply of the various sectors. Thus, satellite rainfall estimates are an alternative to obtain representative data of large areas, since the gauge data from meteorological stations are scarce, frequently due the low density of stations per area. However, these satellite products contain uncertainties when compared to gauge data. In this way, this study aims to evaluate the representativeness of rainfall estimates derived from satellites in the Rio Grande do Sul state. To this, were used satellite TRMM (3B42 V7) products, which were compared with gauge data in the State provided by the Agência Nacional de Águas and by the Instituto Nacional de Meteorologia, considering the period from 1998 to 2013. This paper compared rainfall estimates and gauge data was accomplished through a set statistics like skill scores, such as event detection percentage (PC), hit rate (H), false alerts ratios (FAR and F), critical success index (CSI), the ratio of planned events and observed (B), and the indexes of Heidke (HSS) and Pierce (PSS). Some equations were applied too: correlation coefficient (r) mean absolute error (MPE), root mean square error (RMSE), the Nash-Sutcliffe efficiency coefficient (NS) and bias. The data were compared in daily and accumulated series of 15 and 30 days, through the following methods: Pixel to Point, Point to Point, Pixel to Pixel, from Sub-pixels and aggregate analysis. The 3B42 products were also evaluated for their skill to determine heavy rainfall, using as reference intensity-duration-frequency equations (IDF) derived from gauge data. The results obtained by the methods, except for the analysis of heavy rainfall, not differ much from each other. Spatial analysis showed the relationship of assessments estimates has to the density of stations and the regions of Rio Grande do Sul, while specific analyzes indicated the good performance of TRMM even in Pixel to Point comparison. The results improved in steps that the daily series were accumulated in 15 and 30 days. It was evident the decrease of the quality of the estimates in the eastern RS region, where the ocean effects generates overestimates.
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spelling 2016-08-122016-08-122016-04-27BERNARDI, Ewerthon Cezar Schiavo. QUALITY RAINFALL ESTIMATIVES FROM TRMM SATELLITE IN RIO GRANDE DO SUL STATE. 2016. 166 f. Dissertação (Mestrado em Engenharias) - Universidade Federal de Santa Maria, Santa Maria, 2016.http://repositorio.ufsm.br/handle/1/7658Understanding the spatial and temporal rainfall occurrence, improves the water resources management, both in order to prevent losses related to the occurrence of floods and droughts events, as in relation to the supply of the various sectors. Thus, satellite rainfall estimates are an alternative to obtain representative data of large areas, since the gauge data from meteorological stations are scarce, frequently due the low density of stations per area. However, these satellite products contain uncertainties when compared to gauge data. In this way, this study aims to evaluate the representativeness of rainfall estimates derived from satellites in the Rio Grande do Sul state. To this, were used satellite TRMM (3B42 V7) products, which were compared with gauge data in the State provided by the Agência Nacional de Águas and by the Instituto Nacional de Meteorologia, considering the period from 1998 to 2013. This paper compared rainfall estimates and gauge data was accomplished through a set statistics like skill scores, such as event detection percentage (PC), hit rate (H), false alerts ratios (FAR and F), critical success index (CSI), the ratio of planned events and observed (B), and the indexes of Heidke (HSS) and Pierce (PSS). Some equations were applied too: correlation coefficient (r) mean absolute error (MPE), root mean square error (RMSE), the Nash-Sutcliffe efficiency coefficient (NS) and bias. The data were compared in daily and accumulated series of 15 and 30 days, through the following methods: Pixel to Point, Point to Point, Pixel to Pixel, from Sub-pixels and aggregate analysis. The 3B42 products were also evaluated for their skill to determine heavy rainfall, using as reference intensity-duration-frequency equations (IDF) derived from gauge data. The results obtained by the methods, except for the analysis of heavy rainfall, not differ much from each other. Spatial analysis showed the relationship of assessments estimates has to the density of stations and the regions of Rio Grande do Sul, while specific analyzes indicated the good performance of TRMM even in Pixel to Point comparison. The results improved in steps that the daily series were accumulated in 15 and 30 days. It was evident the decrease of the quality of the estimates in the eastern RS region, where the ocean effects generates overestimates.A compreensão da ocorrência espacial e temporal da precipitação pluviométrica permite melhorar a gestão dos recursos hídricos, tanto no sentido de prevenir prejuízos relacionados à ocorrência de eventos de enchentes e estiagens, quanto em relação ao suprimento dos diversos setores. Assim, estimativas de precipitação de satélites são uma alternativa para obtenção de dados representativos de extensas áreas, tendo em vista que os dados observados em estações meteorológicas são escassos muitas vezes. Todavia, estes produtos de satélite contêm incertezas quando comparados aos dados medidos. O estudo procura avaliar a representatividade das estimativas de chuva oriundas de satélites no estado do Rio Grande do Sul. Para tal utilizaramse produtos do satélite TRMM (3B42 V7), que foram comparados com observados no Estado, disponibilizados pela Agência Nacional de Águas e pelo Instituto Nacional de Meteorologia, no período de 1998 a 2013. O trabalho consistiu em comparar dados de precipitações estimadas e observadas por meio de um conjunto de índices de desempenho, tais como o percentual de detecção de eventos (PC), percentual de acertos (H), percentual de falsos alertas (FAR e F), índice de sucesso crítico (CSI), a razão entre eventos previstos e observados (B), bem como os índices de Heidke (HSS), e Peirce (PSS). Além de outras equações como: coeficiente de correlação (r) erro médio absoluto (EMA), erro médio quadrático (EQM), o coeficiente de eficiência de Nash-Sutcliffe (NS) e viés. Os dados foram comparados em séries diárias e acumulados de 15 e 30 dias, por meio dos seguintes métodos: Pixel a Ponto, Ponto a Ponto, Pixel a Pixel, a partir de Sub-pixels e Análise agregada. Os produtos 3B42 também foram avaliados em relação a capacidade de determinar chuvas intensas, usando como referência equações de intensidade-duração-frequência derivadas de dados observados. Os resultados obtidos pelas metodologias, com exceção da análise de precipitações intensas, não diferenciaram muito entre si. As análises espaciais mostraram a intimidade das avaliações das estimativas tem com a densidade de postos e com as regiões do Rio Grande do Sul, enquanto as análises pontuais indicaram a boa performance do TRMM mesmo na comparação Pixel a Ponto. A medida que as séries diárias foram acumuladas em 15 e 30 dias, os resultados melhoraram. Ficou evidente o decréscimo da qualidade das estimativas na região Leste do RS, onde os efeitos da maritimidade acabam gerando superestimativas.Fundação de Amparo a Pesquisa no Estado do Rio Grande do Sulapplication/pdfporUniversidade Federal de Santa MariaPrograma de Pós-Graduação em Engenharia AmbientalUFSMBREngenharia AmbientalTRMM3B42Rio Grande do SulTRMM3B42Rio Grande do Sul stateCNPQ::ENGENHARIASQualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do SulQuality rainfall estimatives from TRMM satellite in Rio Grande do Sul stateinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisPiccilli, Daniel Gustavo Allasiahttp://lattes.cnpq.br/3858010328968944Paz, Adriano Rolim dahttp://lattes.cnpq.br/2069883404215099Tatsch, Jônatan Duponthttp://lattes.cnpq.br/2365902346826079http://lattes.cnpq.br/2089488199005647Bernardi, Ewerthon Cezar Schiavo3000000000094003003003005001c2baa5d-393c-455f-a5e2-fb47cd900c302b345092-f23d-4622-82c8-8e79c29b37b1e1bfb392-55a4-4894-a884-a50e8e73a3e87ad50a33-41ac-4e96-8234-378a2fb685a0info:eu-repo/semantics/openAccessreponame:Repositório Institucional Manancial UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALBERNARDI, EWERTHON CEZAR SCHIAVO.pdfapplication/pdf15476143http://repositorio.ufsm.br/bitstream/1/7658/1/BERNARDI%2c%20EWERTHON%20CEZAR%20SCHIAVO.pdfa8ba6c5117761116c9d8949d40914b48MD51TEXTBERNARDI, EWERTHON CEZAR SCHIAVO.pdf.txtBERNARDI, EWERTHON CEZAR SCHIAVO.pdf.txtExtracted texttext/plain254946http://repositorio.ufsm.br/bitstream/1/7658/2/BERNARDI%2c%20EWERTHON%20CEZAR%20SCHIAVO.pdf.txt55de1c69724a16504201448976fc46c9MD52THUMBNAILBERNARDI, EWERTHON CEZAR SCHIAVO.pdf.jpgBERNARDI, EWERTHON CEZAR SCHIAVO.pdf.jpgIM Thumbnailimage/jpeg4946http://repositorio.ufsm.br/bitstream/1/7658/3/BERNARDI%2c%20EWERTHON%20CEZAR%20SCHIAVO.pdf.jpg3537001b2a39beb28a042ab34d3f5fedMD531/76582022-08-25 12:32:04.027oai:repositorio.ufsm.br:1/7658Repositório Institucionalhttp://repositorio.ufsm.br/PUBhttp://repositorio.ufsm.br/oai/requestouvidoria@ufsm.bropendoar:39132022-08-25T15:32:04Repositório Institucional Manancial UFSM - Universidade Federal de Santa Maria (UFSM)false
dc.title.por.fl_str_mv Qualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do Sul
dc.title.alternative.eng.fl_str_mv Quality rainfall estimatives from TRMM satellite in Rio Grande do Sul state
title Qualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do Sul
spellingShingle Qualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do Sul
Bernardi, Ewerthon Cezar Schiavo
TRMM
3B42
Rio Grande do Sul
TRMM
3B42
Rio Grande do Sul state
CNPQ::ENGENHARIAS
title_short Qualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do Sul
title_full Qualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do Sul
title_fullStr Qualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do Sul
title_full_unstemmed Qualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do Sul
title_sort Qualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do Sul
author Bernardi, Ewerthon Cezar Schiavo
author_facet Bernardi, Ewerthon Cezar Schiavo
author_role author
dc.contributor.advisor1.fl_str_mv Piccilli, Daniel Gustavo Allasia
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/3858010328968944
dc.contributor.referee1.fl_str_mv Paz, Adriano Rolim da
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/2069883404215099
dc.contributor.referee2.fl_str_mv Tatsch, Jônatan Dupont
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/2365902346826079
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/2089488199005647
dc.contributor.author.fl_str_mv Bernardi, Ewerthon Cezar Schiavo
contributor_str_mv Piccilli, Daniel Gustavo Allasia
Paz, Adriano Rolim da
Tatsch, Jônatan Dupont
dc.subject.por.fl_str_mv TRMM
3B42
Rio Grande do Sul
topic TRMM
3B42
Rio Grande do Sul
TRMM
3B42
Rio Grande do Sul state
CNPQ::ENGENHARIAS
dc.subject.eng.fl_str_mv TRMM
3B42
Rio Grande do Sul state
dc.subject.cnpq.fl_str_mv CNPQ::ENGENHARIAS
description Understanding the spatial and temporal rainfall occurrence, improves the water resources management, both in order to prevent losses related to the occurrence of floods and droughts events, as in relation to the supply of the various sectors. Thus, satellite rainfall estimates are an alternative to obtain representative data of large areas, since the gauge data from meteorological stations are scarce, frequently due the low density of stations per area. However, these satellite products contain uncertainties when compared to gauge data. In this way, this study aims to evaluate the representativeness of rainfall estimates derived from satellites in the Rio Grande do Sul state. To this, were used satellite TRMM (3B42 V7) products, which were compared with gauge data in the State provided by the Agência Nacional de Águas and by the Instituto Nacional de Meteorologia, considering the period from 1998 to 2013. This paper compared rainfall estimates and gauge data was accomplished through a set statistics like skill scores, such as event detection percentage (PC), hit rate (H), false alerts ratios (FAR and F), critical success index (CSI), the ratio of planned events and observed (B), and the indexes of Heidke (HSS) and Pierce (PSS). Some equations were applied too: correlation coefficient (r) mean absolute error (MPE), root mean square error (RMSE), the Nash-Sutcliffe efficiency coefficient (NS) and bias. The data were compared in daily and accumulated series of 15 and 30 days, through the following methods: Pixel to Point, Point to Point, Pixel to Pixel, from Sub-pixels and aggregate analysis. The 3B42 products were also evaluated for their skill to determine heavy rainfall, using as reference intensity-duration-frequency equations (IDF) derived from gauge data. The results obtained by the methods, except for the analysis of heavy rainfall, not differ much from each other. Spatial analysis showed the relationship of assessments estimates has to the density of stations and the regions of Rio Grande do Sul, while specific analyzes indicated the good performance of TRMM even in Pixel to Point comparison. The results improved in steps that the daily series were accumulated in 15 and 30 days. It was evident the decrease of the quality of the estimates in the eastern RS region, where the ocean effects generates overestimates.
publishDate 2016
dc.date.accessioned.fl_str_mv 2016-08-12
dc.date.available.fl_str_mv 2016-08-12
dc.date.issued.fl_str_mv 2016-04-27
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dc.identifier.citation.fl_str_mv BERNARDI, Ewerthon Cezar Schiavo. QUALITY RAINFALL ESTIMATIVES FROM TRMM SATELLITE IN RIO GRANDE DO SUL STATE. 2016. 166 f. Dissertação (Mestrado em Engenharias) - Universidade Federal de Santa Maria, Santa Maria, 2016.
dc.identifier.uri.fl_str_mv http://repositorio.ufsm.br/handle/1/7658
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