Climatological diagnosis and precipitation trend in Cabaceiras - PB, Brazil

Autores

  • Romildo Morant de Holanda Universidade Federal Rural de Pernambuco
  • Raimundo Mainar de Medeiros Universidade Federal Rural de Pernambuco

DOI:

https://doi.org/10.29150/jhrs.v8.3.p120-125

Palavras-chave:

Variability timeline, trend, linear regression

Resumo

The analysis of trends in historical rainfall series is important to verify the interannual and decadal climatic variability in order to identify how climate changes can modulate these temporal patterns of variability. We analyzed the temporal distribution of the historical series and the rainfall trend for the municipality of Cabaceiras - PB and a study with linear regression and measures of central tendency and dispersion of the monthly and annual rainfall indices. Based on the results it was verified that the median is the measure of central tendency most likely to occur; The rainy season occurs between February and July, with an average value of 278.9 mm, corresponding to 82.5% of the annual precipitation. The months of maximum rainfall occur between March and April and those with the lowest rainfall indexes center in the months of October and November; It was verified in the linear regression analysis of the historical series of precipitation of the period from 1926 to 2011, the trend of greater variability of precipitation is centered between the months of February to June, which has high rainfall rates for the region and the smaller ones Pluviometric indexes is centered between the months of October and December, which has low rainfall indexes.

Biografia do Autor

Romildo Morant de Holanda, Universidade Federal Rural de Pernambuco

DEpartamento de Tecnologia Rural

Raimundo Mainar de Medeiros, Universidade Federal Rural de Pernambuco

Departament de Tecnologia Rural

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Publicado

2019-04-13

Como Citar

de Holanda, R. M., & de Medeiros, R. M. (2019). Climatological diagnosis and precipitation trend in Cabaceiras - PB, Brazil. Journal of Hyperspectral Remote Sensing, 8(3), 120–125. https://doi.org/10.29150/jhrs.v8.3.p120-125

Edição

v. 8 n. 3 (2018): Journal of Hyperspectral Remote Sensing

Seção

Artigos

Licença

Copyright (c) 2019 Journal of Hyperspectral Remote Sensing - ISSN: 2237-2202

Creative Commons License

Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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