Spatiotemporal Variability of Precipitation in Serbia (1961–2020) Using Innovative Polygon‐Based Trend Methods

ABSTRACT Understanding long‐term changes in precipitation seasonality is essential for improving climate monitoring and supporting water‐resource management. Conventional trend analyses primarily identify monotonic changes but provide limited information on how transitions between consecutive months evolve over time. This study investigates monthly precipitation variability across Serbia during 1961–2020 using two polygon‐based methods, the Innovative Polygon Trend Analysis (IPTA) and the Trend Polygon Star Concept (TPSC). IPTA was applied to characterise trends in mean monthly precipitation, while TPSC was used to examine changes in month‐to‐month precipitation transitions between two subperiods (1961–1990 and 1991–2020). The Modified Mann–Kendall (MMK) test was additionally employed to assess the statistical significance of the detected trends. The results reveal coherent seasonal precipitation changes across Serbia. IPTA identified widespread increasing trends during September and October, followed by predominantly decreasing trends in November, while TPSC showed consistent wetting tendencies during spring and drying tendencies during winter. Comparison with MMK demonstrated strong agreement in the direction of detected trends, whereas IPTA identified additional weak regional trends that were classified as non‐significant by MMK, indicating its higher sensitivity to subtle precipitation changes. Novi Sad consistently displayed increasing trends across all months, whereas Belgrade showed the most stable precipitation regime. Most stations showed maximum trend lengths between April and May, and minimum values between January and February. The largest transition magnitude was observed between June and July in Belgrade (37.64 mm), while the highest trend slope occurred between August and September in Niš (20.23). These findings demonstrate that IPTA and TPSC complement conventional trend analyses by revealing changes in the internal structure of the annual precipitation cycle and transitions between consecutive months that remain hidden in traditional statistical approaches. The proposed framework provides a comprehensive characterisation of seasonal precipitation dynamics and offers a useful tool for hydro‐climatological investigations of regional climate variability.