Publication
A Dynamical System Approach to Uni and Multi-Variate Weather Analysis over Portuguese Territory
| dc.contributor.author | Belime,Timothée Franck | |
| dc.contributor.institution | Department of Physics | |
| dc.contributor.supervisor | Nunes,Ana Maria Ribeiro Ferreira | |
| dc.contributor.supervisor | Câmara,Carlos do Carmo de Portugal e Castro da | |
| dc.date.accessioned | 2025-12-29T14:40:09Z | |
| dc.date.available | 2025-12-29T14:40:09Z | |
| dc.date.issued | 2025 | |
| dc.description | Tese de mestrado, Física e Astrofísica, 2025, Universidade de Lisboa, Faculdade de Ciências | |
| dc.description.abstract | The main objective of this work is to investigate and reproduce some of the existing research in the analysis of weather dynamics with an approach based on dynamical system. Most studies of climate extremes rely on statistical approaches or machine learning, but chaotic dynamics can provide a deeper understanding of atmospheric behavior. The method can easily be extended to multivariate systems. The general observation that the atmosphere displays chaotic dynamics leads us to numerical analysis of some chaotic attractors. The Lorenz attractor is used extensively in this study. We use these systems to see how much information can be obtained from the time series of a few metrics derived from a discrete trajectory in phase space. This trajectory must be long enough to represent the system globally, meaning that it must be longer than the characteristic time of the system. After probing with numerically integrated systems, we transpose the acquired knowledge to practical applications of real data over Portuguese territory, from 1979 to 2020. We search for the physical meaning behind each metric and investigate if they can provide a better understanding of weather extremes and compound events. Practical applications are explored by crossing the data with registered wildfire activity in the same period of time. We mainly focus on temperature and wind speed and assessment is made of their role in major wildfires. According to their dynamical signatures, warm-windy compound extremes fall into two different classes, one with a more predictable character, and the other less predictable. | en |
| dc.format | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/10400.5/116453 | |
| dc.language.iso | eng | |
| dc.subject | dynamical systems | |
| dc.subject | extremes | |
| dc.subject | data science | |
| dc.subject | weather | |
| dc.title | A Dynamical System Approach to Uni and Multi-Variate Weather Analysis over Portuguese Territory | en |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess |
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