Complex Systems Perspectives on Large-Scale Weather and Climate Variability Patterns

Understanding and predicting extreme weather events is essential for effective hazard prevention and risk management. However, achieving these objectives is challenging, as such events are often driven by nonlinear and/or multiscale processes, and involve multiple interactions within the climate system. In this thesis we employ complex network-based techniques and stochastic modeling to examine three large-scale weather and climate phenomena recognized for their association with extreme weather conditions: atmospheric blocking events, the El Niño–Southern Oscillation (ENSO), and the Madden–Julian Oscillation (MJO).