Is There an Increase in the Intensity and Frequency of Extreme Rainfall in Brazil along the Time?

Extreme rainfall is one of the most severe weather hazards to affect all the globe. Some works use statistical approaches for interpreting extreme events, to choose a constant threshold based on the empirical distribution of the variable at each location is an way that it ensures that a given fraction of events will by definition be extreme. The most common way to choose a threshold is to use technique of quantiles that are cut points dividing the range of a probability distribution into contiguous intervals with equal probabilities but there is still no consensus in meteorology, about the precipitation thresholds for the identification of extreme events, and is therefore quite variable. Many cases of natural disasters caused by heavy rain have been recorded in recent years, are there an increase in the intensity and frequency of extreme rainfall in Brazil along the time? With the answer to this question one can show an indicative of climatic changes in the regions of study. The main goal of this work is to select extreme events of rainfall and propose sort out a dataset with only extreme values of precipitation for understand their behaviour and then verify whether the frequency extreme rainfall events have increased during last years at the chosen regions. In this work was used different ways to statistical analysis, the first is analyse rainfall dataset of temporal e spatial manner. After that to a fitting of Extreme value distributions (EVDs) like the Generalized Extreme Value (GEV) and Generalized Pareto Distribution (GPD) and then do a trend analysis and spectral analysis. Rain gauges dataset available from 1970 to the present and three satellite products TRMM Multisatellite Precipitation Analysis - TMPA, Integrated Multi-satellitE Retrievals for GPM - IMERG and Global Satellite Mapping of Precipitation - GSMAP available from 2000 to the present were used for analysis.

Key words : Extreme Rainfall, Climate Change, Statistical analysis, Extreme value distributions.