Scientific content and goals

This new project aims to apply modern methods of complex networks and artificial intelligence to the study and analysis of time series related to the problems of climate evolution and its natural and social impacts.

In recent years, the Copernicus Climate Change Service (C3S) of the European Commission has collected and reconstructed several data sets on climate evolution over a very wide range of space-time scales.

The scientific activity of CREF, carried out in collaboration with researchers from the C3S service and with partners from other scientific institutions, aims to develop an innovative approach to the multi-scale analysis of such data through the synergistic use of modern filtering methods, signal extraction, classification and representation based on the theory of stochastic processes, complex and neural networks. In the first year we will focus on data collection and analysis, with particular attention to correlations between time series and overfitting problems. In the following years, we will focus on scenario construction using methods from complex network theory and artificial intelligence, focusing on scenarios with impacts at both natural and social levels.

The resulting analysis of the time series of individual observables and the dependencies and correlations between different observables will provide the basis for building scenarios of evolution and impact at local and mesoscopic scales.