Nonstationary time series analysis of monthly global temperature anomalies

In recent years modelling climatic variables has attracted the attention of many researchers. The scientific assessment of the Intergovernmental Panel on Climate Change (IPCC) (Folland et al. (1990)) concluded that despite limitations in the quality and quantity of the available temperature data, there is evidence to a real but irregular warming in the climate. Here, our object is to analyze three important temperature sets using evolutionary spectral methods. We test for stationarity, Gaussianity and linearity and based on the conclusions we fit nonstationary time series models. We also consider forecasting aspects.