Teleconnection Patterns and Climate Variability: Insights into European Potato Growing Seasons

Potato cultivation is one of Europe's and also Finland’s most important agricultural sectors, and climatic variability highly affects its yield. Large-scale atmospheric phenomena, such as teleconnection patterns, are paramount for the regional climatic features to which temperature and precipitation are significant components of potato growth. This is due to the complex climatic interactions caused by teleconnections such as the North Atlantic Oscillation (NAO), El Niño-Southern Oscillation (ENSO), Arctic Oscillation (AO), and Scandinavian Pattern (SCA), which have not been fully discussed within the context of potato farming. This study aims to address possible potato yield predictions from the teleconnection patterns. The study employs machine learning techniques to investigate the relationship between different teleconnection indices and European potato yield variability. Advanced algorithms such as Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) were applied to integrate historical climatic data, teleconnection indices, and potato yield records to develop robust predictive models to help identify the most important climatic drivers and capture nonlinear interactions among teleconnections and agricultural outputs. We examine the spatial and temporal dynamics of teleconnection patterns and their correlation with climate variations across European regions during potato growing seasons. By focusing on the relationship between teleconnections and agrarian outputs, the study seeks to contribute to developing climate-resilient farm strategies in Europe to achieve better food security in the face of changing climate.