Spatiotemporal Analysis of Extreme Rainfall Frequency in the Northeast Region of Brazil
Fidel Ernesto Castro Morales,
Daniele Torres Rodrigues,
Thiago Valentim Marques,
Ana Cleide Bezerra Amorim,
Priscilla Teles de Oliveira,
Claudio Moises Santos e Silva,
Weber Andrade Gonçalves,
Paulo Sergio Lucio
Affiliations
Fidel Ernesto Castro Morales
Department of Statistics, Federal University of Rio Grande do Norte, Natal, Av. Senador Salgado Filho 3000, Lagoa Nova, Natal 59078-970, Brazil
Daniele Torres Rodrigues
Department of Statistics, Federal University of Piauí, Av. Campus Universitário Ministro Petrônio Portella, Ininga, Teresina 64049-550, Brazil
Thiago Valentim Marques
Federal Institute of Education, Science and Technology of Rio Grande do Norte, IFRN, Rua Brusque, 2926, Conjunto Santa Catarina, Potengi, Natal 59112-490, Brazil
Ana Cleide Bezerra Amorim
ISI-ER—SENAI Innovation Institute for Renewable Energies, Av. Capitão Mor-Gouveia 2770, Natal 59071-355, Brazil
Priscilla Teles de Oliveira
Faculdade de Ciências, Universidade Estadual Paulista, Bauru, Av. Eng. Luiz Edmundo Carrijo Coube, 14-01, Vargem Limpa, Bauru 17033-360, Brazil
Claudio Moises Santos e Silva
Climate Sciences Post-Graduate Program, Department of Climate and Atmospheric Sciences, Federal University of Rio Grande do Norte, Av. Senador Salgado Filho 3000, Lagoa Nova, Natal 59078-970, Brazil
Weber Andrade Gonçalves
Climate Sciences Post-Graduate Program, Department of Climate and Atmospheric Sciences, Federal University of Rio Grande do Norte, Av. Senador Salgado Filho 3000, Lagoa Nova, Natal 59078-970, Brazil
Paulo Sergio Lucio
Climate Sciences Post-Graduate Program, Department of Climate and Atmospheric Sciences, Federal University of Rio Grande do Norte, Av. Senador Salgado Filho 3000, Lagoa Nova, Natal 59078-970, Brazil
Climate extreme events are becoming increasingly frequent worldwide, causing floods, drought, forest fires, landslides and heat or cold waves. Several studies have been developed on the assessment of trends in the occurrence of extreme events. However, most of these studies used traditional models, such as Poisson or negative binomial models. Thus, the main objective of this study is to use a space–time data counting approach in the modeling of the number of days with extreme precipitation as an alternative to the commonly used statistical methods. The study area is the Northeast Brazil region, and the analysis was carried out for the period between 1 January 1980 and 31 December 2010, by assessing the frequency of extreme precipitation represented by the R10 mm, R20 mm and R* indices.