Theoretical and Applied Climatology

, Volume 121, Issue 3–4, pp 641–648 | Cite as

Multifractal characterization of global temperature anomalies

  • Provash MaliEmail author
Original Paper


The global monthly temperature anomaly time series for the period 1850–2012 has been investigated in terms of multifractal detrended fluctuation analysis (MF-DFA). Various multifractal observables, such as the generalized Hurst exponent, the multifractal exponent, and the singularity spectrum, are extracted and are fitted to a generalized binomial multifractal model consists of only two free parameters. The results of this analysis give a clear indication of the presence of long-term memory in the global temperature anomaly time series which causes multifractal pattern in the data. We investigate the possible other source(s) of multifractality in the series by random shuffling as well as by surrogating the original series and find that the probability density function also contributes to the observed multifractal pattern along with the long-memory effect. Surprisingly, the temperature anomaly time series are well described by the two-parameter multifractal binomial model.


Temperature Anomaly Detrended Fluctuation Analysis Multifractal Analysis Singularity Spectrum Fluctuation Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



I thank the anonymous reviewer for his/her careful reading of the manuscript and valuable comments and suggestions which help to improve the quality of the paper.


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Copyright information

© Springer-Verlag Wien 2014

Authors and Affiliations

  1. 1.Department of PhysicsUniversity of North BengalWest BengalIndia

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