  In this work we address the feasibility of estimating and isolating the
stationary and deterministic content of observational time series, {\bf Ots},
which in general have very limited characteristics. In particular, we study the
valuable earth's surface mean temperature time series, {\bf Tts}, by applying
several treatments intended to isolate the stationary and deterministic
content. We give particular attention to the sensitivity of results on the
different parameters involved. The effects of such treatments were assessed by
means of several methods designed to estimate the stationarity of time series.
In order to strengthen the significance of the results obtained we have created
a comparative framework with seven test time series of well-know origin and
characteristics with a similar small number of data points. We have obtained a
greater understanding of the potential and limitations of the different methods
when applied to real world time series. The study of the stationarity and
deterministic content of the {\bf Tts} gives useful information about the
particular complexity of global climatic evolution and the general important
problem of the isolation of a real system from its surroundings by measuring
and treating the obtained observations without any other additional information
about the system.
