  We introduce a method for decomposition of trend, cycle and seasonal
components in spatio-temporal models and apply it to investigate the existence
of climate changes in temperature and rainfall series. The method incorporates
critical features in the analysis of climatic problems - the importance of
spatial heterogeneity, information from a large number of weather stations, and
the presence of missing data. The spatial component is based on continuous
projections of spatial covariance functions, allowing modeling the complex
patterns of dependence observed in climatic data.
  We apply this method to study climate changes in the Northeast region of
Brazil, characterized by a great wealth of climates and large amplitudes of
temperatures and rainfall. The results show the presence of a tendency for
temperature increases, indicating changes in the climatic patterns in this
region.
