Givanildo de Gois

Prof. Dr. Givanildo de Gois

orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2019 in Atmospheric Research
Verified
Journal Article
Closed access
BSBRUNO SOBRAL
BRUNO SOBRAL
JOJosé Francisco de Oliveira-Júnior
José Francisco de Oliveira-Júnior
Givanildo de GoisGivanildo de Gois
Givanildo de Gois
EPEdson Rodrigues Pereira-Júnior
Edson Rodrigues Pereira-Júnior
Paulo Miguel De Bodas TerassiPaulo Miguel De Bodas Terassi
Paulo Miguel De Bodas Terassi
Marcelo ZeriMarcelo Zeri
Marcelo Zeri

5 October 2016 in Meteorology and Atmospheric Physics
Verified
Journal Article
Closed access
PDF file
TBThábata T. Brito
Thábata T. Brito
JOJosé F. Oliveira-Júnior
José F. Oliveira-Júnior
GLGustavo Bastos Lyra
Gustavo Bastos Lyra
Givanildo de GoisGivanildo de Gois
Givanildo de Gois
Marcelo ZeriMarcelo Zeri
Marcelo Zeri

10 September 2020 in International Journal of Climatology
Verified
Journal Article
Open access
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MCMicejane da Silva Costa
Micejane da Silva Costa
José Francisco Oliveira JúniorJosé Francisco Oliveira Júnior
José Francisco Oliveira Júnior
PSPaulo José dos Santos
Paulo José dos Santos
WFWashington Luiz Félix Correia Filho
Washington Luiz Félix Correia Filho
Givanildo de GoisGivanildo de Gois
Givanildo de Gois
Alexandre Maniçoba da Rosa Ferraz JardimAlexandre Maniçoba da Rosa Ferraz Jardim
Alexandre Maniçoba da Rosa Ferraz Jardim
The objective of this study was to evaluate the annual standardized precipitation index (SPI) obtained from the DrinC software based on multivariate analysis in the identification of rainfall and drought extremes in the State of Alagoas and its relationship with El Niño–Southern Oscillation. Monthly rainfall data from 1960 to 2016 from National Water Agency were analysed. Annual SPI (SPI‐12) has been designed for comparison with ENSO phases via Oceanic Niño Index for 3.4 region and in identifying climate extremes in the State of Alagoas. The principal component analysis and cluster analysis techniques were applied to the rainfall series of SPI‐12. Extreme events were identified in both rainy and drought periods according to SPI‐12, and were associated with the ENSO phases (El Niño, La Niña, and Neutral). The first four principal components explained 46.68% of the variance. Our findings are crucial for agriculture and civil defence since northeastern Brazil has several areas of risk and social vulnerability.

2 October 2019 in Big Earth Data
Verified
Journal Article
Open access
WFWashington Luiz Félix Correia Filho
Washington Luiz Félix Correia Filho
José Francisco Oliveira JúniorJosé Francisco Oliveira Júnior
José Francisco Oliveira Júnior
DSDimas de Barros Santiago
Dimas de Barros Santiago
Paulo Miguel De Bodas TerassiPaulo Miguel De Bodas Terassi
Paulo Miguel De Bodas Terassi
Paulo TeodoroPaulo Teodoro
Paulo Teodoro
PSPaulo José Dos Santos
Paulo José Dos Santos
Brazilian biomes are home to a significant portion of the world’s biodiversity, with a total of 14% of existing species and still concentrate 20% of the world’s water resources. However, changes in biomes have a direct impact on rainfall patterns and water recycling. Based on this, the objective was to evaluate the variability of rainfall in the four existing biomes in the Northeast Brazil (NEB) and their interaction with the ENSO climate variability mode and regional scale meteorological systems via CHELSA product. For this, monthly rainfall data were used from 1979 to 2013, with a spatial resolution of 1 km × 1 km of the CHELSA product, and seasonal and annual rainfall patterns were extracted via boxplot. It was found that the rainy season in the Amazon, Caatinga and Cerrado biomes occurred between January and April, with varying intensities, except for the Atlantic Forest. Such seasonality patterns are associated with the NEB meteorological systems, with emphasis on ITCZ (all Biomes), UTCV (Amazon, Caatinga and Cerrado), Frontal Systems (extreme south of Caatinga, Cerrado and Atlantic Forest) and EWD/TWD in the (Atlantic Forest). In the inter-annual scale, the remarkable influence of ENSO was verified, mainly in the years 1983, 1985, 1989, 1993, 1998, 2009 and 2012. It is noteworthy that 1985 was the wettest year of the period, with a surplus in all biomes, while the driest year differs between the Amazon (1983), Atlantic Forest and Caatinga (1993) and Cerrado (2012) biomes. The study via orbital product in NEB showed that anthropogenic processes and natural variability interfere with the forms of rain interception in the biomes and hence in rainfall patterns and water recycling in NEB.

21 May 2016 in Meteorology and Atmospheric Physics
Verified
Journal Article
Closed access
PDF file
GLGustavo Bastos Lyra
Gustavo Bastos Lyra
JOJ. F. Oliveira-Júnior
J. F. Oliveira-Júnior
Givanildo de GoisGivanildo de Gois
Givanildo de Gois
GCG. Cunha-Zeri
G. Cunha-Zeri
Marcelo ZeriMarcelo Zeri
Marcelo Zeri

1 March 2018 in Infrared Physics & Technology
Verified
Journal Article
Closed access
Carlos Antonio da Silva JuniorCarlos Antonio da Silva Junior
Carlos Antonio da Silva Junior
MNMarcos Rafael Nanni
Marcos Rafael Nanni
MSMuhammad Shakir
Muhammad Shakir
Paulo TeodoroPaulo Teodoro
Paulo Teodoro
JOJosé Francisco de Oliveira-Júnior
José Francisco de Oliveira-Júnior
LSLuciano Shozo Shiratsuchi
Luciano Shozo Shiratsuchi