Multivariate Processing of Geophysical Data.
Data without structure is noise, and not information. In geophysics, the structure (thus the information) of the data is completely driven by the underlying physical processes (that are not always well known). Those physical processes do not only constraint the range of reasonable values any physical variable can take, but also establish strong links among different variables associated to the same phenomena. Geophysical data has structure, and the structure has a meaning that can explain more about the physics of phenomena than raw values.
Systematizing the study of the co-variability and data structure is essential to maximize the understanding and the extraction of the information about sensible processes affecting the dynamics of our planet, from meteorological to climatological scales.
In this course, we will explain the theoretical fundations and show practical applications about the main methods used to analyze geophysical variables, in isolation or in a coordinated, multivariate manner.