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:
https://us06web.zoom.us/j/84510516378?pwd=kqbCjRxQubA6bxcxRnAZLXzMvY5MsT.1
Thesis supervisors: Emilio Hernández-García, Cristóbal López, Reik V. Donner
Jury:
President: Cristina Masoller, UPC
Secretary: Enrico Ser-Giacomi, IFISC
Vocal: Jonathan F. Donges, PIK
Detalls de contacte:
Emilio Hernández-García Contact form