Evaluation of Seasonal Ensemble Precipitation Hindcasts at Upper São Francisco River in Brazil

Detalhes bibliográficos
Autor(a) principal: Weber, Taciana Menezes
Data de Publicação: 2016
Outros Autores: Dereczynski, Claudine Pereira, Souza, Ricardo Henrique dos Santos, Chou, Sin Chan, Bustamante, Josiane Ferreira, Paiva Neto, Arthur Chaves de
Tipo de documento: Artigo
Idioma: por
Título da fonte: Anuário do Instituto de Geociências (Online)
Texto Completo: https://revistas.ufrj.br/index.php/aigeo/article/view/6982
Resumo: Seasonal rainfall forecasts generated with regional Eta model for the rainy season of the São Francisco River Basin, upstream Hydroeletric Power Plant (HPP) Três Marias in Minas Gerais are evaluated in this work. The use of such forecasts as an input in energy planning models, represent a better management in the generation, transmission and distribution of electricity. However, it is well known that most of the globe, seasonal climate predictability is much reduced, since the effects of boundary conditions to determine the evolution of the average state of the atmosphere compete with internal variability associated with the chaotic instabilities and nonlinear interactions of the atmospheric flow. The forecasts of the Eta-Seasonal-15km model are initiated on days 13 to 17 October, extending until February 28, during the years 2001-2010. The evaluation results indicate that the noise (inter members variability) is higher than the signal (interannual variability), suggesting low reliability of the forecasts for the region during the rainy season. Forecasts of precipitation are underestimated and the Root Mean Square Error of 77.03 mm / month is high, almost twice its standard deviation. Note A high spatial variability of rainfall due to very steep topography, which further reduces the performance of numerical models. A hit rating category of precipitation (IACP), based on the distribution of tertiles, was applied to account for the number of times that the forecasts point to the same category of observed rainfall: rainfall below, within or above the normal range. The IACP for the whole area and during the ten years was low (mean 29%), however in the southern Basin IACP is a bit higher, around 50% to 70% in the Southeast region. The annual review of the forecasts for the entire area indicated that the best model performance occurred in 2005, when conditions ATMS negative in Pacific, near the coast of Peru were persisted in October 2005 and in fact such anomalies occurred through the month of February 2006.
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spelling Evaluation of Seasonal Ensemble Precipitation Hindcasts at Upper São Francisco River in BrazilInvestigação da Previsibilidade Sazonal da Precipitação na Região do Alto São Francisco em Minas GeraisSeasonal forecasting; Precipitation; Eta model; Minas GeraisPrevisão sazonal; Precipitação; Modelo Eta; Minas GeraisSeasonal rainfall forecasts generated with regional Eta model for the rainy season of the São Francisco River Basin, upstream Hydroeletric Power Plant (HPP) Três Marias in Minas Gerais are evaluated in this work. The use of such forecasts as an input in energy planning models, represent a better management in the generation, transmission and distribution of electricity. However, it is well known that most of the globe, seasonal climate predictability is much reduced, since the effects of boundary conditions to determine the evolution of the average state of the atmosphere compete with internal variability associated with the chaotic instabilities and nonlinear interactions of the atmospheric flow. The forecasts of the Eta-Seasonal-15km model are initiated on days 13 to 17 October, extending until February 28, during the years 2001-2010. The evaluation results indicate that the noise (inter members variability) is higher than the signal (interannual variability), suggesting low reliability of the forecasts for the region during the rainy season. Forecasts of precipitation are underestimated and the Root Mean Square Error of 77.03 mm / month is high, almost twice its standard deviation. Note A high spatial variability of rainfall due to very steep topography, which further reduces the performance of numerical models. A hit rating category of precipitation (IACP), based on the distribution of tertiles, was applied to account for the number of times that the forecasts point to the same category of observed rainfall: rainfall below, within or above the normal range. The IACP for the whole area and during the ten years was low (mean 29%), however in the southern Basin IACP is a bit higher, around 50% to 70% in the Southeast region. The annual review of the forecasts for the entire area indicated that the best model performance occurred in 2005, when conditions ATMS negative in Pacific, near the coast of Peru were persisted in October 2005 and in fact such anomalies occurred through the month of February 2006.Previsões sazonais de precipitação geradas com modelo regional Eta para a estação chuvosa da Bacia do Rio São Francisco, a montante da Usina Hidrelétrica (UHE) de Três Marias em Minas Gerais são avaliadas neste trabalho. A utilização de tais previsões como insumo nos modelos de planejamento energético, representaria um melhor gerenciamento na geração, transmissão e distribuição da energia elétrica. Contudo, é conhecido o fato de que na maior parte do globo, a previsibilidade climática sazonal é muito reduzida, uma vez que os efeitos das condições de contorno em determinar a evolução do estado médio da atmosfera competem com a variabilidade caótica interna associada às instabilidades e interações não lineares do escoamento atmosférico. As previsões do modelo Eta-Sazonal-15km são iniciadas nos dias 13 a 17 de outubro, estendendo-se até 28 de fevereiro, durante os anos de 2001 a 2010. Os resultados da avaliação indicam que o ruído (variabilidade intermembros) é superior ao sinal (variabilidade interanual), sugerindo baixa confiabilidade das previsões para a região no período chuvoso. As previsões de precipitação são subestimadas e a Raiz Quadrada do Erro Quadrático Médio, de 77,03 mm/mês é elevada , quase o dobro de seu desvio padrão. Nota-se elevada variabilidade espacial da precipitação devido a topografia bastante acentuada, o que reduz ainda mais o desempenho dos modelos numéricos. Um índice de acerto da categoria da precipitação (IACP), baseado na distribuição de tercis, foi aplicado para contabilizar o número de vezes em que as previsões apontam para a mesma categoria das chuvas observadas: chuvas abaixo, acima ou dentro da normalidade. O IACP para toda a área e durante os dez anos foi baixo (média de 29%), contudo no sul da Bacia o IACP é um pouco mais elevado, em torno de 50%, chegando a 70% no sudeste da região. A avaliação anual das previsões para toda a área indicou que a melhor performance do modelo ocorreu no ano de 2005, quando condições de ATMS negativas no Pacífico, próximo a costa do Peru foram persistidas no mês de outubro de 2005 e de fato tais anomalias se verificaram até o mês de fevereiro de 2006.Universidade Federal do Rio de Janeiro2016-05-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufrj.br/index.php/aigeo/article/view/698210.11137/2015_2_24-36Anuário do Instituto de Geociências; Vol 38, No 2 (2015); 24-36Anuário do Instituto de Geociências; Vol 38, No 2 (2015); 24-361982-39080101-9759reponame:Anuário do Instituto de Geociências (Online)instname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJporhttps://revistas.ufrj.br/index.php/aigeo/article/view/6982/5549Copyright (c) 2016 Anuário do Instituto de Geociênciashttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessWeber, Taciana MenezesDereczynski, Claudine PereiraSouza, Ricardo Henrique dos SantosChou, Sin ChanBustamante, Josiane FerreiraPaiva Neto, Arthur Chaves de2017-01-23T22:46:08Zoai:www.revistas.ufrj.br:article/6982Revistahttps://revistas.ufrj.br/index.php/aigeo/indexPUBhttps://revistas.ufrj.br/index.php/aigeo/oaianuario@igeo.ufrj.br||1982-39080101-9759opendoar:2017-01-23T22:46:08Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ)false
dc.title.none.fl_str_mv Evaluation of Seasonal Ensemble Precipitation Hindcasts at Upper São Francisco River in Brazil
Investigação da Previsibilidade Sazonal da Precipitação na Região do Alto São Francisco em Minas Gerais
title Evaluation of Seasonal Ensemble Precipitation Hindcasts at Upper São Francisco River in Brazil
spellingShingle Evaluation of Seasonal Ensemble Precipitation Hindcasts at Upper São Francisco River in Brazil
Weber, Taciana Menezes
Seasonal forecasting; Precipitation; Eta model; Minas Gerais
Previsão sazonal; Precipitação; Modelo Eta; Minas Gerais
title_short Evaluation of Seasonal Ensemble Precipitation Hindcasts at Upper São Francisco River in Brazil
title_full Evaluation of Seasonal Ensemble Precipitation Hindcasts at Upper São Francisco River in Brazil
title_fullStr Evaluation of Seasonal Ensemble Precipitation Hindcasts at Upper São Francisco River in Brazil
title_full_unstemmed Evaluation of Seasonal Ensemble Precipitation Hindcasts at Upper São Francisco River in Brazil
title_sort Evaluation of Seasonal Ensemble Precipitation Hindcasts at Upper São Francisco River in Brazil
author Weber, Taciana Menezes
author_facet Weber, Taciana Menezes
Dereczynski, Claudine Pereira
Souza, Ricardo Henrique dos Santos
Chou, Sin Chan
Bustamante, Josiane Ferreira
Paiva Neto, Arthur Chaves de
author_role author
author2 Dereczynski, Claudine Pereira
Souza, Ricardo Henrique dos Santos
Chou, Sin Chan
Bustamante, Josiane Ferreira
Paiva Neto, Arthur Chaves de
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Weber, Taciana Menezes
Dereczynski, Claudine Pereira
Souza, Ricardo Henrique dos Santos
Chou, Sin Chan
Bustamante, Josiane Ferreira
Paiva Neto, Arthur Chaves de
dc.subject.por.fl_str_mv Seasonal forecasting; Precipitation; Eta model; Minas Gerais
Previsão sazonal; Precipitação; Modelo Eta; Minas Gerais
topic Seasonal forecasting; Precipitation; Eta model; Minas Gerais
Previsão sazonal; Precipitação; Modelo Eta; Minas Gerais
description Seasonal rainfall forecasts generated with regional Eta model for the rainy season of the São Francisco River Basin, upstream Hydroeletric Power Plant (HPP) Três Marias in Minas Gerais are evaluated in this work. The use of such forecasts as an input in energy planning models, represent a better management in the generation, transmission and distribution of electricity. However, it is well known that most of the globe, seasonal climate predictability is much reduced, since the effects of boundary conditions to determine the evolution of the average state of the atmosphere compete with internal variability associated with the chaotic instabilities and nonlinear interactions of the atmospheric flow. The forecasts of the Eta-Seasonal-15km model are initiated on days 13 to 17 October, extending until February 28, during the years 2001-2010. The evaluation results indicate that the noise (inter members variability) is higher than the signal (interannual variability), suggesting low reliability of the forecasts for the region during the rainy season. Forecasts of precipitation are underestimated and the Root Mean Square Error of 77.03 mm / month is high, almost twice its standard deviation. Note A high spatial variability of rainfall due to very steep topography, which further reduces the performance of numerical models. A hit rating category of precipitation (IACP), based on the distribution of tertiles, was applied to account for the number of times that the forecasts point to the same category of observed rainfall: rainfall below, within or above the normal range. The IACP for the whole area and during the ten years was low (mean 29%), however in the southern Basin IACP is a bit higher, around 50% to 70% in the Southeast region. The annual review of the forecasts for the entire area indicated that the best model performance occurred in 2005, when conditions ATMS negative in Pacific, near the coast of Peru were persisted in October 2005 and in fact such anomalies occurred through the month of February 2006.
publishDate 2016
dc.date.none.fl_str_mv 2016-05-10
dc.type.none.fl_str_mv
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv https://revistas.ufrj.br/index.php/aigeo/article/view/6982
10.11137/2015_2_24-36
url https://revistas.ufrj.br/index.php/aigeo/article/view/6982
identifier_str_mv 10.11137/2015_2_24-36
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://revistas.ufrj.br/index.php/aigeo/article/view/6982/5549
dc.rights.driver.fl_str_mv Copyright (c) 2016 Anuário do Instituto de Geociências
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 Anuário do Instituto de Geociências
http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Universidade Federal do Rio de Janeiro
publisher.none.fl_str_mv Universidade Federal do Rio de Janeiro
dc.source.none.fl_str_mv Anuário do Instituto de Geociências; Vol 38, No 2 (2015); 24-36
Anuário do Instituto de Geociências; Vol 38, No 2 (2015); 24-36
1982-3908
0101-9759
reponame:Anuário do Instituto de Geociências (Online)
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