Analysis and Future Projections of Seasonal Shifts in Türkiye

Date

2025-11-26

Author

Tunç, Ecenaz

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The changes in the location or duration of seasons, driven by climate change, are termed seasonal shifts. Seasonal shifts are significant phenomena that directly impact ecological balance and human life, and their effects are wide-ranging. For example, the blooming periods of plants may occur at unusual times, requiring farmers to adjust their pest control schedules accordingly. Animal migration timings may change, and hibernation patterns in some species may alter, potentially leading to disruptions in local ecosystems. Additionally, the frequency of extreme weather events, such as intense heatwaves and challenging storms, may increase. Numerous factors contribute to seasonal shifts, with changes in atmospheric events being one of the primary influences. By applying statistical methods and machine learning algorithms, factors impacting seasonal shifts can be analyzed, enabling preventive measures based on future projections. This thesis examines the main factors that contribute to seasonal shifts, using dynamic clustering methods and time-series analysis to explore changes in seasonal patterns across Türkiye. Using a 1970–2024 multivariate climate dataset and the Toeplitz Inverse Covariance-based Clustering (TICC) method, this study identifies a clear nationwide restructuring of seasonal regimes in Türkiye. The results reveal an inland and northward expansion of hot-dry summer regimes, a systematic shortening of winter regimes, and strong spatial contrasts, with the Black Sea region maintaining high stability and Eastern Anatolia preserving cold-season dominance. These findings show that seasonal shifts in Türkiye manifest not only through temperature trends but through structural transformations in regime persistence, transition timing, and seasonal dominance across the country’s major climate zones.

Subject Keywords

TICC, Seasonal Change, Climate, Clustering

URI

https://hdl.handle.net/11511/118220

Collections

Graduate School of Natural and Applied Sciences, Thesis