Multifractal analysis of standardize precipitation index (Research, Society and Development, 2021)
In many tropical countries including Brazil it has been observed that changes in rainfall patterns cause severe floods and with a tendency to continue to worsen during the 21st century. In order to reduce the consequences on human life and health, economic activities, ecosystems and infrastructure with efficient protection measures in mind, it is necessary to develop the most reliable forecasting models. The first step in this direction is a detailed analysis of the climatic variability in the region. In this work, we analyze the multifractal properties of the time series of Standardized Precipitation Index (SPI) developed to classify dry/wet conditions according to severity. This index was calculated for different time scales (1,3,6 and 12 months) and analyzed using the Multifractal detrended fluctuation analysis method. The multifractal spectrum complexity parameters (position of maximum, width and asymmetry) together with Hurst's exponent showed that the SPI series are generated by the multifractal process with stronger multifractality and stronger persistence for larger scales of rainfall accumulation.