Aplicação do modelo de pulsos retangulares de Bartlett-Lewis modificado para estimativa de eventos extremos de precipitação

Back, Álvaro José; Uggioni, Edison

doi:10.1590/s0100-69162010000600005

Cited by 3 publications

(1 citation statement)

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“…The aforementioned arguments, associated with the fact that a severe/extreme rainfall deficit frequently leads to crop yield reductions (BACK & UGGIONI, 2010), have motivated us to verify (i) whether the BM and/or POT can be used to assess the probability of occurrence of extreme dry SPI values in an agricultural region of the State of São Paulo, Brazil and (ii) which of these approaches provides the best characterization of the probability of occurrence of extreme dry months. Thus, the goals of this study were to apply both BM and POT to sample the extreme SPI data, obtained from the weather station of Ribeirão Preto (1937Preto ( -2012, and to empirically compare the performance of these both approaches in providing the best fit extreme value distribution.…”

Section: Introductionmentioning

confidence: 99%

Dry months in the agricultural region of Ribeirão Preto, state of São Paulo-Brazil: an study based on the extreme value theory

Blain

2014

Eng. Agríc.

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ABSTRACT:The application of the Extreme Value Theory (EVT) to model the probability of occurrence of extreme low Standardized Precipitation Index (SPI) values leads to an increase of the knowledge related to the occurrence of extreme dry months. This sort of analysis can be carried out by means of two approaches: the block maxima (BM; associated with the General Extreme Value distribution) and the peaks-over-threshold (POT; associated with the Generalized Pareto distribution). Each of these procedures has its own advantages and drawbacks. Thus, the main goal of this study is to compare the performance of BM and POT in characterizing the probability of occurrence of extreme dry SPI values obtained from the weather station of Ribeirão Preto-SP (1937. According to the goodness-of-fit tests, both BM and POT can be used to assess the probability of occurrence of the aforementioned extreme dry SPI monthly values. However, the scalar measures of accuracy and the return level plots indicate that POT provides the best fit distribution. The study also indicated that the uncertainties in the parameters estimates of a probabilistic model should be taken into account when the probability associated with a severe/extreme dry event is under analysis. KEYWORDS:Extreme Value distribution, Pareto distribution, goodness-of-fit tests. TEORIA DOS VALORES EXTREMOS APLICADA À OCORRÊNCIA DE MESES SECOS EM UMA REGIÃO AGRÍCOLA DO ESTADO DE SÃO PAULO RESUMO:A aplicação da Teoria dos Valores Extremos (EVT) para modelar a probabilidade de ocorrência dos extremos inferiores do Índice Padronizado de Precipitação (SPI) leva ao aprofundamento do conhecimento relativo à ocorrência de meses secos. Esse tipo de análise pode ser realizado com base nos métodos dos máximos em bloco (BM; associado à distribuição Geral dos Valores Extremos) e dos peaks-over-threshold (POT; associado à distribuição Pareto Generalizada). Considerando que cada um desses procedimentos apresenta vantagens e desvantagens, o objetivo principal do trabalho foi comparar o desempenho de ambos os métodos na caracterização da probabilidade de ocorrência dos extremos secos do SPI obtidos a partir da estação meteorológica de Ribeirão Preto-SP (1937. De acordo com os testes de aderência, o BM e o POT podem ser usados para avaliar a probabilidade de ocorrência de valores mensais extremamente secos do SPI obtidos na referida localidade. Entretanto, medidas escalares de precisão e gráficos de nível de returno indicam que o POT resulta no melhor ajuste. O estudo também demonstrou que as incertezas na estimação dos parâmetros de modelos probabilísticos devem ser consideradas quando a probabilidade de ocorrência dos eventos em análise estiver sendo avaliada.

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Section: Introductionmentioning

confidence: 99%

Dry months in the agricultural region of Ribeirão Preto, state of São Paulo-Brazil: an study based on the extreme value theory

Blain

2014

Eng. Agríc.

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Bartlett-Lewis of rectangular pulse modified model: estimate of parameters for simulation of precipitation in sub-hourly duration

Teixeira-Gandra

Damé

2014

Eng. Agríc.

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ABSTRACT:The Bartlett-Lewis Rectangular Pulse Modified (BLPRM) model simulates the precipitous slide in the hourly and sub-hourly and has six parameters for each of the twelve months of the year. This study aimed to evaluate the behavior of precipitation series in the duration of 15 min, obtained by simulation using the model BLPRM in situations: (a) where the parameters are estimated from a combination of statistics, creating five different sets; (b) suitability of the model to generate rain. To adjust the parameters were used rain gauge records of Pelotas/RS/Brazil, which statistics were estimated -mean, variance, covariance, autocorrelation coefficient of lag 1, the proportion of dry days in the period considered. The results showed that the parameters related to the time of onset of precipitation () and intensities (x) were the most stable and the most unstable were  parameter, related to rain duration. The BLPRM model adequately represented the mean, variance, and proportion of the dry period of the series of precipitation lasting 15 min and, the time dependence of the heights of rain, represented autocorrelation coefficient of the first retardation was statistically less simulated series suitability for the duration of 15 min.KEYWORDS: sub-hourly rainfall, daily rainfall disaggregation, hydrologic modeling. MODELO BARTLETT-LEWIS DE PULSO RETANGULAR MODIFICADO: ESTIMATIVA DOS PARÂMETROS PARA SIMULAÇÃO DA PRECIPITAÇÃO EM DURAÇÃO SUB-HORÁRIA RESUMO:O modelo Bartlett-Lewis de Pulso Retangular Modificado (BLPRM) simula a lâmina precipitada em duração horária e sub-horária, e possui seis parâmetros para cada um dos doze meses do ano. Objetivou-se avaliar o comportamento das séries de precipitação na duração de 15 min, obtidas por simulação mediante o uso do modelo BLPRM, nas situações: (a) em que os parâmetros são estimados a partir da combinação de estatísticas, formando cinco diferentes conjuntos; (b) adequabilidade do modelo na geração de chuva. Para o ajuste dos parâmetros, foram utilizados registros pluviográficos do município de Pelotas-RS/Brasil, dos quais foram estimadas as estatísticas -média, variância, covariância, coeficiente de autocorrelação de retardo 1, proporção de dias secos no período considerado. Os resultados mostraram que os parâmetros relacionados ao tempo de início da chuva () e as intensidades máximas (x) foram os mais estáveis, e o parâmetro mais instável foi , relacionado à duração da chuva. O modelo BLPRM representou adequadamente a média, a variância e a proporção de período seco da série de chuva com duração de 15 min, e a dependência temporal das alturas de chuva, representada de coeficiente de autocorrelação de retardo 1, foi a estatística da série simulada com menor adequação, para a duração de 15 min. PALAVRAS-CHAVE:chuva sub-horária, desagregação da chuva diária, modelagem hidrológica.

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Statistical downscaling and disaggregation for supporting regional climate change impact studies

Yan¹

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A warmer climate may affect the frequency and severity of weather extremes, such as heavy rainfalls, hurricanes and heatwaves. Based on the records around the world, the numbers of observed extreme events have presented increasing tendencies over the past decades. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report points out that the temperature would be continuously increasing in this century. This implies that some disasters (e.g. flood and drought) which are caused by weather extremes could become more frequent. The Southeast Asia is vulnerable to the impact of climate change. Especially in the urban areas, the flash flood has become one of major disasters caused by heavy rainfall. It is thus critical to develop flexible and applicable approaches to investigate the climate change impact on local regions. The General Circulation Models (GCMs) are the powerful tools to simulate either current or future climate conditions. But the bias and resolution problems have limited their applications for some specific regions like Southeast Asia. The dynamical and statistical downscaling are the two basic approaches to help bridge the gaps between GCMs and local weather information. Compared with dynamical approaches, the statistical ones are computationally cheap and easily applicable to many different regions. The objective of this PhD study is to develop and apply statistical downscaling and disaggregation methods for supporting hydrological and climate change impact studies. It covers three major components including development of novel statistical downscaling tools, applications of combined statistical downscaling and disaggregation methods, and assessment of climate change impact on hydrological processes. Firstly, two novel methods of statistical downscaling approaches were developed. One was a regression-based method which included the K nearest neighbor (KNN) and Bayesian neural network (BNN) models. In this method, KNN was used for classifying the dry/wet day and rainfall typing based on rainfall intensity. BNN was vii applied for prediction of rainfall amount. The other one was a semi-empirical stochastic weather generator which was mainly based on the Markov chain, semi-empirical random generator, and KNN. In detail, a four-state first-order Markov chain was employed to estimate day status which includes dry-day, wet-day with low-intensity rain, wet-day with moderate-intensity rain and wet-day with high-intensity rain based on the mean areal rainfall; then, three semi-empirical distributions were used to fit the three wet categories of rainfalls; finally, the KNN method was used in spatial disaggregation to generate daily rainfalls at multiple stations. A common idea of the two models was to use classification technique to describe different rainfall magnitudes based on rainfall intensity. The study results demonstrated that classification was helpful to enhance characterization of the convective rainfalls in the tropical region in the downscaling processes. Secondly, a number of com...

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Aplicação do modelo de pulsos retangulares de Bartlett-Lewis modificado para estimativa de eventos extremos de precipitação

Cited by 3 publications

References 22 publications

Dry months in the agricultural region of Ribeirão Preto, state of São Paulo-Brazil: an study based on the extreme value theory

Dry months in the agricultural region of Ribeirão Preto, state of São Paulo-Brazil: an study based on the extreme value theory

Bartlett-Lewis of rectangular pulse modified model: estimate of parameters for simulation of precipitation in sub-hourly duration

Statistical downscaling and disaggregation for supporting regional climate change impact studies

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