Climate Network

Climate networks analyze the interconnectedness of climate variables across geographical regions, aiming to understand teleconnections and improve climate prediction. Current research focuses on refining network construction methods, addressing statistical uncertainties in correlation estimations, and leveraging machine learning, including deep learning and explainable AI, to enhance predictive capabilities and interpret complex relationships. This work is crucial for improving the accuracy and interpretability of climate models, particularly in predicting extreme weather events and their impacts on regional hydrology, such as river flows influenced by El Niño. Improved understanding of these networks will lead to better climate projections and more effective adaptation strategies.

Papers