avaliação de estimativas de campos de precipitação para modelagem hidrológica distribuída assessment of estimated precipitation fields for distributed hydrologic modeling
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ID: 162282
2011
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Abstract
É crescente a disponibilidade e utilização de campos de chuva estimados por sensoriamento remoto ou calculados por modelos de circulação da atmosfera, os quais são freqüentemente utilizados como entrada para modelos hidrológicos distribuídos. A distribuição espacial dos campos de chuva estimados é altamente relevante e deve ser avaliada frente aos campos de chuva observados. Este artigo propõe um método de comparação espaço-temporal entre campos de chuva observados e estimados baseado na comparação pixel a pixel e na construção de tabelas de contingência. Duas abordagens são utilizadas: (i) a análise integrada no espaço gera índices de performance que retratam a qualidade do campo de chuva estimada em reproduzir a ocorrência de chuva observada ao longo do tempo; (ii) a análise integrada no tempo produz mapas dos índices de performance que resumem a destreza das estimativas de ocorrência de chuva em cada pixel. Como exemplo de aplicação, é analisada a chuva estimada na climatologia do modelo global de circulação da atmosfera CPTEC/COLA sobre a bacia do Rio Grande. Utilizando-se cinco índices de performance, o método proposto permitiu identificar variações sazonais e padrões espaciais na performance das estimativas de chuva em relação a campos de chuva derivados de observações em pluviômetros.
There is an increasing availability and application of precipitation fields estimated by remote sensing or calculated by atmospheric circulation models, which are frequently used as input for distributed hydrological models. The spatial distribution of the estimated precipitation fields is extremely important and must be verified against observed precipitation fields. This paper proposes a method for spatiotemporal comparison between observed and estimated precipitation fields based on a pixel by pixel comparison and on contingency tables. Two distinct approaches are carried out: (i) the spatial integrated analysis produces skill scores denoting the ability of the estimated precipitation field in reproducing the occurrence of observed precipitation along the time; (ii) the time integrated analysis generates maps of skill scores showing the reliability of the precipitation estimates in each pixel. As an example of application, the estimated precipitation climatology of the CPTEC/COLA global circulation model over the Rio Grande basin is assessed. Using five different skill scores, the proposed method identified seasonal variations and spatial patterns in the performance of the estimated precipitation fields in relation to precipitation fields derived from pluviometers measurement.
There is an increasing availability and application of precipitation fields estimated by remote sensing or calculated by atmospheric circulation models, which are frequently used as input for distributed hydrological models. The spatial distribution of the estimated precipitation fields is extremely important and must be verified against observed precipitation fields. This paper proposes a method for spatiotemporal comparison between observed and estimated precipitation fields based on a pixel by pixel comparison and on contingency tables. Two distinct approaches are carried out: (i) the spatial integrated analysis produces skill scores denoting the ability of the estimated precipitation field in reproducing the occurrence of observed precipitation along the time; (ii) the time integrated analysis generates maps of skill scores showing the reliability of the precipitation estimates in each pixel. As an example of application, the estimated precipitation climatology of the CPTEC/COLA global circulation model over the Rio Grande basin is assessed. Using five different skill scores, the proposed method identified seasonal variations and spatial patterns in the performance of the estimated precipitation fields in relation to precipitation fields derived from pluviometers measurement.
| Reference Key |
paz2011revistaavaliao
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| Authors | ;Adriano Rolim da Paz;Walter Collischonn |
| Journal | Applied microbiology and biotechnology |
| Year | 2011 |
| DOI |
10.1590/S0102-77862011000100010
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