Estimating return periods for daily precipitation extreme events over the Brazilian Amazon

• Published in: Theoretical and applied climatology Vol. 126; no. 3-4; pp. 585 - 595
• Main Authors: Santos, Eliane Barbosa, Lucio, Paulo Sérgio, Santos e Silva, Cláudio Moisés
• Format: Journal Article
• Language: English
• Published: Vienna Springer Vienna 01.11.2016; Springer; Springer Nature B.V
• Subjects: Analysis; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; Climate change; Climatology; Coastal zone; Distribution (Probability theory); Earth and Environmental Science; Earth Sciences; Extreme weather; Meteorology; Original Paper; Precipitation; Precipitation (Meteorology); Waste Water Technology; Water Management; Water Pollution Control; Weather forecasting; Brazil; Amazonas Brazil; Return Level; Daily Precipitation; Generalize Extreme Value; Return Period; Generalize Pareto Distribution
• ISSN: 0177-798X; 1434-4483
• DOI: 10.1007/s00704-015-1605-9

This paper aims to model the occurrence of daily precipitation extreme events and to estimate the return period of these events through the extreme value theory (generalized extreme value distribution (GEV) and the generalized Pareto distribution (GPD)). The GEV and GPD were applied in precipitation series of homogeneous regions of the Brazilian Amazon. The GEV and GPD goodness of fit were evaluated by quantile–quantile (Q-Q) plot and by the application of the Kolmogorov–Smirnov (KS) test, which compares the cumulated empirical distributions with the theoretical ones. The Q-Q plot suggests that the probability distributions of the studied series are appropriated, and these results were confirmed by the KS test, which demonstrates that the tested distributions have a good fit in all sub-regions of Amazon, thus adequate to study the daily precipitation extreme event. For all return levels studied, more intense precipitation extremes is expected to occur within the South sub-regions and the coastal area of the Brazilian Amazon. The results possibly will have some practical application in local extreme weather forecast.