  The surface air temperature daily records at the land-based locations with
different climate conditions (from Arctic to Patagonia) have been studied on
the daily to intraseasonal time scales (low frequency annual and seasonal
variations have been removed by subtracting a wavelet regression from the daily
records). It is shown that the power spectra of the daily time series exhibit a
universal behaviour corresponding to the Hamiltonian distributed chaos. Global
average temperature fluctuations (land-based data) and the tropical Pacific sea
surface temperature fluctuations (El Ni\~no/La Ni\~na phenomenon) have been
also considered in this context. It is shown that the practical smooth
predictability for the surface air temperature dynamics is possible at least up
to the fundamental (pumping) period of the distributed chaos.
