Neural network modelling for the analysis of forcings/temperatures relationships at different scales in the climate system

A fully non-linear analysis of forcing influences on temperatures is performed in the climate system by means of neural network modelling. Two case studies are investigated, in order to establish the main factors that drove the temperature behaviour at both global and regional scales in the last 140 years. In particular, our neural network model shows the ability to catch non-linear relationships among these variables and to reconstruct...