Banca de DEFESA: JOSIEL OLIVEIRA DA LUZ

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : JOSIEL OLIVEIRA DA LUZ
DATE: 10/01/2025
TIME: 14:00
LOCAL: Ambiente virtual
TITLE:

Statistical Analyses of Extreme Rainfall on the East Coast of the Northeast Using Spatio-
Temporal Models

KEY WORDS:

Geostatistics; Spatio-temporal models; R packages; Climate extremes; Satellite data.

PAGES: 91
BIG AREA: Ciências Exatas e da Terra
AREA: Probabilidade e Estatística
SUMMARY:

The study of climatic extremes is essential for understanding the occurrence of natural
disasters. It becomes even more important when the tools available for this analysis do not
perform their functions accurately. This is the case with the extreme precipitation events that
occur on the east coast of north-eastern Brazil, where satellite estimates tend to underestimate
extreme precipitation. With this in mind, the study set out to explore the behaviour of rainfall
extremes in this region in order to build the knowledge needed to support the development of
natural disaster mitigation measures. To do this, the study extreme was the number of times
that the daily rainfall accumulated exceeded or was equal to the threshold of 30 millimetres in
a one-year period. The time series studied is 32 years old, with observations at 36 stations. As
well as rainfall, it contains the latitude, longitude and altitude of the stations. The data was taken
from the National Meteorological Institute (INMET) and the National Water and Sanitation
Agency (ANA). The study used descriptive statistics as well as spatial and spatio-temporal models
available in the literature and implemented in the R language. The extremes occur more
frequently in regions close to the coast, with spatial dependence and unclear temporal
dependence. Furthermore, in a purely observational analysis, there is an indication of patterns
of extremes repeating every 10 years from 1991 onwards. Satellite data was found to
underestimate extremes in the region studied, especially in the south of the area. Four packages
implemented in the R language capable of working with the study data were identified in the
literature, and six models from these packages were adjusted. The models obtained excellent
results when compared to the satellite estimates. They proved to be better in most of the
locations tested. They also show that they have great potential for generating more reliable data
for analysing precipitation extremes.

COMMITTEE MEMBERS:
Interno - 3010614 - ELIARDO GUIMARAES DA COSTA
Presidente - 1781198 - FIDEL ERNESTO CASTRO MORALES
Externo à Instituição - JORIO BEZERRA CABRAL JUNIOR