Long-term trend analysis in annual, seasonal and monthly rainfall in East Northeast of Brazil and the influence of modes of climate variability

The study of rainfall trends is crucial for food security and water availability in Alagoas state, Northeast of Brazil. In this work, monthly, seasonal and annual rainfall trends have been studied (1960-2016) for homogeneous rainfall regions over the eastern part of the Northeast Brazil (ENEB) and later related to climate variability. Cluster analysis was applied to identify homogeneous rainfall regions while the Mann-Kendall (MK), modified Mann-Kendall (MMK) and Pettitt tests were used in the analysis and identification of trends on a spatial and temporal scale. To relate rainfall and climate variability modes, Spearman's correlation was used in each homogeneous region. The rainfall series provided evidence of a general decrease in rainfall in the rainy period and an increase in the dry period, mainly over the driest region. The break points of time series occurred mostly in periods of great variations in values of modes of climate variability, especially the Monthly Nino3.4 Index and the Southern Oscillation Index (SOI), both having a robust influence across the region. Moreover, the probable rainfall in the time series with trends was different in most months before and after the breakpoint. After the breakpoint, probable rainfall was lower, influenced by the breakpoint year (size of the series before and after the breakpoint), which mainly occurred in the 1980s and 1990s and presented a warm phase and a greater number of El Nino events. The MK and MMK trend tests showed the ability to detect trends, although there is no established standard on which test or version to use due to self-correlated, nonhomogeneous series with nonrandom or nonindependent data. Rainfall is an important variable for water and food security and in the monitoring of natural disasters. The changes detected in this study can be used as reference information for public policies on water resources and future studies for Alagoas and similar regions.