Uncovering rainfall dynamics in Pernambuco, Brazil, through innovative polygon trend analysis

Abstract This study applied the Innovative Polygon Trend Analysis (IPTA) and the Trend Polygon Star Concept (TPSC) to high-resolution precipitation records (1961–2022) across Pernambuco, Brazil, to assess the spatial variability of monthly rainfall trends and transitions. Monthly precipitation totals derived from 820 BR-DWGD grid cells were analyzed to characterize long-term changes in rainfall patterns across the semiarid Sertão, humid Zona da Mata, and transitional Agreste regions. The results revealed a predominance of negative rainfall trends during March, April, and December, suggesting a reduction in precipitation during both the wet and dry seasons. Distinct regional patterns were observed: The Sertão and Zona da Mata generally exhibited negative trends during the dry season, whereas the Agreste showed predominantly positive trends during the wet season, reflecting its transitional climatic characteristics. Zona da Mata displayed the largest spatial extent of negative rainfall trends across seasons, indicating a greater reduction in precipitation during the second half of the study period relative to the first. The Mann–Kendall (MK) test corroborated the principal spatial patterns identified by IPTA, with significant negative trends occurring mainly in the Sertão and Zona da Mata during March, central Sertão in April, northwestern Sertão during June and July, and Zona da Mata in September. TPSC analysis highlighted temporal transitions in monthly rainfall, identifying increasing transitions during the rainy season in Zona da Mata and during the dry season in the Sertão across both study periods. In contrast, the Agreste exhibited a less consistent seasonal pattern and changes in the direction of monthly transitions between the two periods. These findings improve the understanding of the spatial and temporal variability of rainfall in Pernambuco and provide useful information for water resource management, agricultural planning, and climate adaptation strategies.