Rainfall Patterns and Trends on São Miguel Island (Azores, Portugal): A Hierarchical Clustering and Trend Analysis Approach

This study addressed rainfall patterns and trends on São Miguel Island (Azores, Portugal). Homogeneous rainfall areas were identified using Ward’s hierarchical clustering method. The analysis was performed using monthly rainfall data from 21 rainfall stations, considering the climatological periods of 1978/79–2019/20 (full dataset), 1978/79–2009/10 (oldest sub-dataset), and 2010/11–2019/20 (latest sub-dataset). Four rainfall clusters were identified, with Mean Annual Rainfall (MAP) ranging from 835.8 mm in low-altitude areas to 2925.5 mm in regions with higher elevation. These clusters showed consistent patterns for the analysed periods, although some changes in their composition were observed when considering the oldest and latest sub-datasets. The correlation between altitude and rainfall was strong (R2 up to 0.83), indicating an increase of approximately 196 mm of MAP per 100 m elevation gain. Moreover, no notable variation was observed between the island’s windward and leeward slopes. Rainfall trend analysis using Mann–Kendall and Sen’s slope tests revealed significant declines in both annual and seasonal rainfall in recent years. The strongest decreases occurred in autumn and winter, with trends as steep as −31.6 mm/year and −12.1 mm/year in autumn (both at the Fogo III station). Between the oldest and most recent periods, rainfall reductions reached up to 41% in autumn (P10) and 55% in winter (P10), particularly affecting clusters at lower and mid-altitudes. Although certain stations showed significant declines, the overall trend hints at a potential deviation from projections of global climate change models, as well as from trends identified in previous long-term rainfall studies. The predominantly positive phase of the North Atlantic Oscillation (NAO) observed in recent years has likely contributed, at least partially, to the decrease in the rainfall trend. Overall, the results provide a refined spatial and temporal characterisation of rainfall across São Miguel Island, improving the understanding of local climatic variability and offering valuable insights for regional water management and climate adaptation strategies.