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Multifractal structure of global monthly mean temperature anomaly time seriesover the period of 1850-2012 are studied in terms of the multifractal detrendedmoving average (MFDMA) analysis. We try to address the possible source(s) andthe nature of multifractality in the time series data by comparing the resultsderived from the actual series with those from a set of shuffled and surrogateseries. It is seen that the MFDMA method predicts a multifractal structure ofthe temperature anomaly records that is more or less similar to what wasobtained from the multifractal detrended analysis for the same set of data. Inour analysis the major contribution of multifractality in the data is found tobe due to the long-range temporal correlation among the measurements, howeverthe contribution of a fat-tail distribution function of the variables is notnegligible. The existence of long-range correlation is also confirmed by theconstancy of the local slopes of the fluctuation function over a sufficientscale intervals. The results of the moving average analysis are found to dependupon the location of the detrending window and tend to the observations of themultifractal detrended analysis for a specific choice of the location of thedetrending window.

Multifractal detrended moving average analysis of global temperature records