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Selfsimilar space-time fractal fluctuations are generic to dynamical systemsin nature such as atmospheric flows, heartbeat patterns, population dynamics,etc. The physics of the long-range correlations intrinsic to fractalfluctuations is not yet identified. It is important to quantify the physicsunderlying the irregular fractal fluctuations for predictability studies. Ageneral systems theory for fractals visualizes the emergence of successivelylarger scale fluctuations to result from the space-time integration of enclosedsmaller scale fluctuations. The model predictions are as follows. Theprobability distribution and the power spectrum for fractal fluctuations is thesame inverse power law function incorporating the golden mean. The predicteddistribution is close to the Gaussian distribution for small-scale fluctuationsbut exhibits fat long tail for large-scale fluctuations with higher probabilityof occurrence than predicted by Gaussian distribution. Since the power(variance i.e. square of eddy amplitude) spectrum also represents theprobability densities as in the case of quantum systems such as the electron orphoton, fractal fluctuations exhibit quantumlike chaos. The fine structureconstant for spectrum of fractal fluctuations is a function of the golden meanand is analogous to atomic spectra equal to about 1/137. Global gridded timeseries data sets of monthly mean temperatures for the period 1880 - 2007/2008are analysed to show that data sets and corresponding power spectra exhibitdistributions close to the model predicted inverse power law distribution. Themodel predicted and observed universal spectrum for interannual variabilityrules out linear secular trends in global monthly mean temperatures. Globalwarming results in intensification of fluctuations of all scales and manifestedimmediately in high frequency fluctuations.

Signatures of Universal Characteristics of Fractal Fluctuations in Global Mean Monthly Temperature Anomalies