Avaliação das Estimativas de Precipitação do Produto 3B43-TRMM do Estado do Amazonas

Almeida, Catherine Torres de; Delgado, Rafael Coll; Oliveira, José Francisco de; Góis, Givanildo de; Cavalcanti, Alessandro Sarmento

doi:10.1590/2179-8087.112114

Cited by 35 publications

(29 citation statements)

References 14 publications

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“…In general the coefficients are not fully satisfactory on any temporal scale, however, an improvement in the results was observed proportional to the increase in temporal scale. Such behavior was also observed in other studies developed in Brazil (Pereira et al, 2013;Oliveira et al, 2014;Almeida et al, 2015).…”

Section: Resultssupporting

confidence: 86%

Applicability of TRMM Precipitation for Hydrologic Modeling in a Basin in the Northeast Brazilian Agreste

Cruz

Rocha

Aragão

et al. 2018

Rev. bras. meteorol.

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Determining precipitation using remote sensing is gaining space in hydrologic studies, helping make up for the lack of data in many regions of Brazil. The products from satellite TRMM (Tropical Rainfall Measuring Mission) are widely applied in studies in Brazil, but there are still few results about their applicability for hydrologic modeling in the Northeast Region, which is characterized by an irregular precipitation regime. The objective of this study is to evaluate the feasibility of using the TRMM 3B42 V7 data for hydrologic modeling in the Japaratuba river basin in Sergipe at three timescales: daily, every ten days, and monthly. The comparative analysis between the rainfall data from rain gauges and TRMM did not indicate satisfactory adequacy at these studied scales, since the TRMM data underestimated the total rainfall for all stations used in the study. However, for the hydrologic modeling, acceptable values were obtained for the efficiency coefficients evaluated only for the ten-day and monthly scales.

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Section: Resultssupporting

confidence: 86%

Applicability of TRMM Precipitation for Hydrologic Modeling in a Basin in the Northeast Brazilian Agreste

Cruz

Rocha

Aragão

et al. 2018

Rev. bras. meteorol.

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“…Dados da t x e t n foram obtidos de Estações Meteorológicas Automáticas (EMA) do Instituto Nacional de Meteorologia (INMET), a chuva foi obtida do satélite tropical TRMM (Tropical Rainfall Measuring Mission) via produto 3B43, com resolução espacial de 20 km e informações de chuva horária que foram convertidos para média mensal (OLIVEIRA JÚNIOR et al, 2014) (Figura 2). Segundo Almeida et al (2015) os dados do produto 3B43 podem ser utilizados quando não há dados de Estações Meteorológicas Convencionais (EMC), com boa precisão e uma malha densa de rede de estações. As informações de R s foram obtidas pelo método proposto pela FAO 56 (Food and Agriculture Organization of the United Nations) que requer informações de latitude (°) do local e número de horas de brilho solar por dia (n), sendo este último foi obtido da base de dados do INMET (ALLEN et al, 1998).…”

Section: Dados Climáticosunclassified

Influência das variáveis climáticas na produção florestal via modelo 3-PG no Norte de Minas Gerais

Oliveira¹,

Delgado²,

Araújo³

et al. 2017

Sci. For.

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Este trabalho teve por objetivo avaliar a influência das variáveis climáticas sobre a produção de plantios de Eucalyptus spp. na região Norte de Minas Gerais utilizando o modelo ecofisiológico de crescimento 3-PG (Physiological Principles in Predicting Growth). O 3-PG foi executado com base em médias históricas e mensais obtidas pelo INMET (Instituto Nacional de Meteorologia) e satélite TRMM (Tropical Rainfall Measuring Mission). A correlação linear (Pearson) (r), coeficiente de determinação (R²), erro padrão da estimativa (S yx), eficiência do modelo (EF) e raiz do erro quadrático médio (RMSE) foram utilizados para avaliar as estimativas realizadas pelo modelo 3-PG. As variáveis dendrométricas, diâmetro médio a altura do peito (DAP-cm), altura total (m), volume (m³.ha-1) e incremento médio anual (IMA-m³.ha-1), estimadas pelo 3-PG, com média histórica, apresentaram alta variação, com tendência de subestimativa das variáveis. As estatísticas r e R² apresentaram valores satisfatórios (> 0,60). Porém observou-se que o erro das estimativas tende a ser maior quando se utiliza média histórica. O modelo teve redução da EF de 0,58 para 0,50 para o IMA. Durante janeiro de 2005 a dezembro de 2011 não houve redução da produção, caso as variáveis climáticas tivessem comportamento semelhante às médias históricas. Dentre os moduladores ambientais, observou-se que o fAS teve maior restrição sobre o crescimento das árvores nessa região, seguido do modulador fDPV, o que pode estar relacionado às altas temperaturas encontradas na região. A utilização de normais climatológicas mostrou-se adequada para analisar o potencial produtivo de novas áreas para produção de Eucalyptus spp. na região, no entanto deve-se atentar para possíveis variações climáticas que podem reduzir a produção.

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“…This database was chosen due to its spatial and temporal resolution that allows a more detailed analysis of the Brazilian Legal Amazon, totalling 6614 pixels. In addition, validations performed for the Amazon region showed a significant high correlation and agreement between the data estimated by the product and those observed in the field by rainfall gauges [14,41,42].…”

Section: Rainfall Datamentioning

confidence: 86%

Spatiotemporal Rainfall Trends in the Brazilian Legal Amazon between the Years 1998 and 2015

Silva

Almeida

Santos

et al. 2018

Water

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Tropical forests play an important role as a reservoir of carbon and biodiversity, specifically forests in the Brazilian Amazon. However, the last decades have been marked by important changes in the Amazon, particularly those associated with climatic extremes. Quantifying the variability of rainfall patterns, hence, is essential for understanding changes and impacts of climate upon this ecosystem. The aim of this study was to analyse spatiotemporal trends in rainfall along the Brazilian Legal Amazon between 1998 and 2015. For this purpose, rainfall data derived from the Tropical Rainfall Measuring Mission satellite (TRMM) and nonparametric statistical methods, such as Mann–Kendall and Sen’s Slope, were used. Through this approach, some patterns were identified. No evidence of significant rainfall trends (p ≤ 0.05) for annual or monthly (except for September, which showed a significant negative trend) averages was found. However, significant monthly negative rainfall anomalies were found in 1998, 2005, 2010, and 2015, and positive in 1999, 2000, 2004, 2009, and 2013. The annual pixel-by-pixel analysis showed that 92.3% of the Brazilian Amazon had no rainfall trend during the period analysed, 4.2% had significant negative trends (p ≤ 0.05), and another 3.5% had significant positive trends (p ≤ 0.05). Despite no clear temporal rainfall trends for most of the Amazon had negative trends for September, corresponding to the peak of dry season in the majority of the region, and negative rainfall anomalies found in 22% of the years analysed, which indicate that water-dependent ecological processes may be negatively affected. Moreover, these processes may be under increased risk of disruption resulting from other drought-related events, such as wildfires, which are expect to be intensified by rainfall reduction during the Amazonian dry season.

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Avaliação das Estimativas de Precipitação do Produto 3B43-TRMM do Estado do Amazonas

Cited by 35 publications

References 14 publications

Applicability of TRMM Precipitation for Hydrologic Modeling in a Basin in the Northeast Brazilian Agreste

Applicability of TRMM Precipitation for Hydrologic Modeling in a Basin in the Northeast Brazilian Agreste

Influência das variáveis climáticas na produção florestal via modelo 3-PG no Norte de Minas Gerais

Spatiotemporal Rainfall Trends in the Brazilian Legal Amazon between the Years 1998 and 2015

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