Spatial and Temporal Patterns of Rainfall Anomalies and Their Relationship With Global Climate Indices in Rio Grande do Norte, Brazil

This study analysed the climate variability of the Rainfall Anomaly Index (RAI) and its relationship with global climate indices in Rio Grande do Norte (RN), Brazil, using monthly precipitation data from 115 weather stations (1963–2023). RN experienced significant changes in precipitation, with both positive and negative anomalies over the decades. Principal Component Analysis (PCA) revealed 12 components explaining 73.15% of the total variance, whereas the K‐means algorithm identified three homogeneous regions corresponding to the state's climatology. Pearson's correlation coefficient showed that teleconnections such as the Atlantic Multidecadal Oscillation (AMO), Tropical North Atlantic (TNA), and Niño indices had a direct relationship with rainfall patterns, whereas the Global Mean Land/Ocean Temperature Index (LOTI) and Solar Flux exhibited an inverse relationship, suggesting that higher solar radiation and global temperatures are linked to fewer anomalous rains. The Niño indices showed substantial variation during extreme drought events in 1966, 1982–83, 1987–88, 1991–92, 1997–98, and 2015–16. Wavelet coherence analysis revealed interannual and interdecadal periodicities in rainfall anomalies, particularly in region R3, characterised by low rainfall and frequent droughts. The findings emphasise the importance of understanding extreme climate patterns over time to improve climate prediction and resource management in the region.