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We introduce a method for decomposition of trend, cycle and seasonalcomponents in spatio-temporal models and apply it to investigate the existenceof climate changes in temperature and rainfall series. The method incorporatescritical features in the analysis of climatic problems - the importance ofspatial heterogeneity, information from a large number of weather stations, andthe presence of missing data. The spatial component is based on continuousprojections of spatial covariance functions, allowing modeling the complexpatterns of dependence observed in climatic data.  We apply this method to study climate changes in the Northeast region ofBrazil, characterized by a great wealth of climates and large amplitudes oftemperatures and rainfall. The results show the presence of a tendency fortemperature increases, indicating changes in the climatic patterns in thisregion.

A continuous spatio-temporal approach to estimate climate change