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

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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 Ni˜no–Southern Oscillation (ENSO), and the Madden–Julian Oscillation (MJO).

The presentation can be followed online from the public link:

Thesis supervisors: Emilio Hernández-García, Cristóbal López, Reik V. Donner


President: Cristina Masoller, UPC

Secretary: Enrico Ser-Giacomi, IFISC

Vocal: Jonathan F. Donges, PIK

Detalls de contacte:

Emilio Hernández-García

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