Multifractal scaling properties of daily air temperature time series. (May 2017)

• Record Type: Journal Article
• Authors: Kalamaras, N.; Philippopoulos, K.; Deligiorgi, D.; Tzanis, C.G.; Karvounis, G.
• Is Part Of: Chaos, solitons and fractals. Volume 98(2017)
• Page Start: 38
• Page End: 43
• Publication Date: 2017-05
• Subjects: Air temperature -- Multifractal detrended fluctuation analysis -- Scaling properties; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2017.03.003
• Languages: English
• ISSNs: 0960-0779

Abstract

Highlights: Multifractal Detrended Fluctuation Analysis is applied to temperature time series. Τhe examined time series show multifractality and are long-term positive correlated. Multifractality is due to different long-range correlations for various fluctuations. Daily mean, maximum and minimum time series show the same multifractal behavior. Abstract: The aim of the current research study is to examine the scaling properties of the mean daily, maximum and minimum air temperature time series of a single coastal site, located at the island of Crete in Greece. The Multifractal Detrended Fluctuation Analysis (MF-DFA) is used to examine the time series long-term correlation and the singularity spectrum to estimate the multifractality degree. The analysis reveals that the daily temperature time series exhibit a multifractal behavior, are positive long-term correlated and that their multifractal structure is insensitive to local fluctuations with large magnitudes.