A complex network based early warning indicator of the MOC collapse

Abstract

Early warning indicators of the collapse of the Atlantic Meridional Overturning Circulation (MOC) have up to now only been based on temporal correlations of single time series. In this thesis, we use spatial correlations of the time series of the temperature and salinity fields to construct complex networks. These networks are constructed at different points approaching the tipping point of the MOC. In these points, we observe a clear evolution of the network degree. We explain this evolution by considering the eigenvectors and the empirical orthogonal functions (EOFs) of the system. To investigate the application of this procedure to grids with limited spatial resolution, we also construct networks from two different limited grids. We find a new early warning indicator for the MOC based on the evolution in the network degree. This indicator is also applicable to the limited grids.