Distribution of Air Temperature Multifractal Characteristics Over Greece

Abstract

In this study, Multifractal Detrended Fluctuation Analysis (MF-DFA) is applied to daily temperature time series (mean, maximum and minimum values) from 22 Greek meteorological stations with the purpose of examining firstly their scaling behavior and then checking if there are any differences in their multifractal characteristics. The results showed that the behavior is the same at almost all stations, i.e., time series are positive long-term correlated and their multifractal structure is insensitive to local fluctuations with large magnitude. Moreover, this study deals with the spatial distribution of the main characteristics of multifractal (singularity) spectrum: the dominant Hurst exponent, the width of the spectrum, the asymmetry and the truncation type of the spectrum. The spatial distributions are discussed in terms of possible effects from various climatic features. In general, local atmospheric circulation and weather conditions are found to affect the shape of the spectrum and the corresponding spatial distributions. Furthermore, the intercorrelation of the main multifractal spectrum parameters resulted in a well-defined group of stations sharing similar multifractal characteristics. The results indicate the usefulness of the non-linear analysis in climate research due to the complex interactions among the natural processes.

Multifractal Detrended Fluctuation Analysis of Temperature Reanalysis Data over Greece

“…An additional scope of this study is to compare the scaling behavior of the reanalysis temperature time series with the corresponding findings from observational records from 22 land-based meteorological stations presented in [49]. The multifractal spectral parameters from the observational records and those from their nearest reanalysis data grid points are illustrated in Table 1.…”

“…Following the findings of Kalamaras et al [49], which are based on observational temperature records over Greece, the scope of this study is to examine the behavior and the spatial distribution of multifractal spectrum characteristics using temperature time series from a reanalysis dataset. In the following section, the characteristics of the area under study are presented along with the extracted subset of the temperature time series from the ERA-Interim dataset.…”

“…In the methodology section, there is a detailed reference for the main multifractal spectrum features. In the results and discussion sections, the resulting multifractal spectra are examined in association with climatic features and compared with the principal results presented in [49].…”

“…The shape of the spectrum can be symmetrical, left truncated, or right truncated. According to [49], the truncation type is grouped into four categories: LL (a high degree of truncation on the left side, i.e., when the left side of the spectrum is shorter than the half of the length of the right side); L (left-truncated, when the left side of the spectrum is shorter (but not less than half) than the right side); S (symmetrical, when left side has almost equal length to the right side); and R (right-truncated, when the right side is shorter than the left side). The distinction between L and LL was made because it was found that most of the spectra are left-truncated, and this can be a convenient way to better study their asymmetry.…”

Multi-fractal Behaviors of long term daily relative humidity and temperature observed over Benin synoptic stations (West Africa)

“…Researchers have explained these findings by the fact that the atmosphere and the natural processes taking place in it are a complex natural system (Kantz and Schreiber, 2004;Peters and Neelin, 2006;Vassoler and Zebende, 2012;Shi, 2014). Therefore, meteorological parameters are characterized by a high degree of nonlinearity, non-stationarity and complexity (He, 2015;Agbazo et al, 2019a;Philippopoulos et al, 2019;Kalamaras et al, 2017Kalamaras et al, , 2019Jiang et al, 2016;Burgueño et al, 2014 andDong et al, 2016). In this context, multifractal methods are suitable to analyze processes that obey to nonlinearity characteristics.…”