Applicatıon of detrended fluctuation analysis to temperature data from Turkey

Orun, Mediha; Koçak, Kasım

doi:10.1002/joc.1853

Cited by 24 publications

(21 citation statements)

References 26 publications

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“…A great number of studies have applied DFA successfully to meteorological time series. More specifically, DFA has been used in the study of climate for temperature time series [17][18][19][20][21][22], relative humidity [23,24], precipitation amount [25], drought and flood indices [26], ozone data [27][28][29][30], incident flux of solar radiation [31], examining the variability of the atmosphere for a very wide temporal range [32], and the North Atlantic Oscillation [33], among others.…”

Section: Introductionmentioning

confidence: 99%

Multifractal Detrended Fluctuation Analysis of Temperature Reanalysis Data over Greece

et al. 2019

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The Multifractal Detrended Fluctuation Analysis (MF-DFA) is used to examine the scaling behavior and the multifractal characteristics of the mean daily temperature time series of the ERA-Interim reanalysis data for a domain centered over Greece. The results showed that the time series from all grid points exhibit the same behavior: they have a positive long-term correlation and their multifractal structure is insensitive to local fluctuations with a large magnitude. Special emphasis was given to the spatial distribution of the main characteristics of the multifractal spectrum: the value of the Hölder exponent, the spectral width, the asymmetry, and the truncation type of the spectra. The most interesting finding is that the spatial distribution of almost all spectral parameters is decisively determined by the land-sea distribution. The results could be useful in climate research for examining the reproducibility of the nonlinear dynamics of reanalysis datasets and model outputs.

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Section: Introductionmentioning

confidence: 99%

Multifractal Detrended Fluctuation Analysis of Temperature Reanalysis Data over Greece

et al. 2019

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“…As early as 1951, Hurst () demonstrated that the annual run‐off record from the Nile River displayed a long‐term persistence (self‐similar), and he developed the “Hurst exponent” to characterize the long‐term persistence. Subsequently, long‐term persistence has been recognized in many time series, such as economic (Muchnik, Bunde, & Havlin, ), climatic (Orun & KoçAk, ), and water quality (Shi, Liu, Huang, Zhang, & Su, ) data sets. Calculation methods for the Hurst exponent include detrended fluctuation analysis (DFA) (Onderka et al, ), wavelet transforms (Simonsen, Hansen, & Nes, ), and rescaled range analysis (Nnaji, ).…”

Section: Introductionmentioning

confidence: 99%

“…As early as 1951, Hurst (1951) demonstrated that the annual run-off record from the Nile River displayed a long-term persistence (self-similar), and he developed the "Hurst exponent" to characterize the long-term persistence. Subsequently, longterm persistence has been recognized in many time series, such as economic (Muchnik, Bunde, & Havlin, 2009), climatic (Orun & KoçAk, 2009), and water quality (Shi, Liu, Huang, Zhang, & Su, 2010) data sets.…”

Section: Introductionmentioning

confidence: 99%

Influence of land use on the persistence effect of riverine phosphorus

Huang

Wang

Chen

et al. 2017

Hydrological Processes

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The persistence effect contribution of legacy nutrients is often cited as a reason for little or no improvement in water quality following extensive implementation of watershed nutrient mitigation actions, yet there is limited knowledge concerning factors influencing this response, often called the "persistence effect." Here, we adopted detrended fluctuation analysis and Spearman analysis methods to assess the influence of land use on the watershed phosphorus (P) persistence effect, using monthly water quality records during 2010-2016 in 13 catchments within a drinking water reservoir watershed in eastern China. Detrended fluctuation analysis was used to calculate the Hurst exponent α to assess watershed legacy P characteristics (α ≈ 0.5, α > 0.5, and α < 0.5 indicate white noise, persistence, and anti-persistence, respectively). Results showed weak to strong P persistence (0.60-0.81) in the time series of riverine P in the 13 catchments. The Hurst exponent α had negative relationships with agricultural land (R = −.47, p = .11) and developed land (R = −.67, p = .01) and a positive relationship with forest land cover (R = .48, p = .10). The persistence effect of riverine P was mainly determined by retention ability (biogeochemical legacy) and migration efficiency (hydrological legacy). A catchment with strong retention capacity (e.g., biomass uptake/storage and soil PO 4 sorption) and low migration efficiency results in a stronger persistence effect for riverine P. In practice, source control is more effective in catchments with weak persistence, whereas sink control (e.g., riparian buffers and wetlands) is preferred in catchments with strong persistence effects.

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“…In the current literature, determination of long-term persistence is another important research area. In this area, autocorrelation function, fluctuation analysis (FA), de-trended fluctuation analysis (DFA), spectral analysis, Hurst method, wavelet method and fractal dimension are e96 F. M. KORKMAZ AND K. KOÇAK used frequently in order to determine the long-term persistence properties of a given variable (Govindan and Kantz, 2004;Kavasseri, 2004;Kavasseri and Nagarajan, 2005;Harrouni and Guessoum, 2009;Koçak, 2009;Orun and Koçak, 2009;Telesca et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Climatology of wind speed persistence over Turkey

Korkmaz¹,

Koçak

2017

Intl Journal of Climatology

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It is a well‐known fact that, sustainability is very important issue in the field of energy production of any kind. Wind speed persistence, as a climatological indicator, is one of the most important components of wind phenomenon which is closely related with sustainability of wind energy production. The most suitable areas for wind energy production are the areas with high wind speed persistence. On the other hand, there are a few studies on how to measure persistence of wind properly. In this study, two novel methods used to investigate persistence characteristics of a given area were applied to Turkey's wind speed data. The results have revealed some important characteristics of persistence throughout Turkey. According to these results western parts of Anatolia have highest persistence. The second region that has high persistence is inner parts of Anatolia because the topography of the Aegean region which enables wind to penetrate along long distances from the coast to the inner parts of Anatolia. All of the results obtained from the study are in accordance with the observations.

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Applicatıon of detrended fluctuation analysis to temperature data from Turkey

Cited by 24 publications

References 26 publications

Multifractal Detrended Fluctuation Analysis of Temperature Reanalysis Data over Greece

Multifractal Detrended Fluctuation Analysis of Temperature Reanalysis Data over Greece

Influence of land use on the persistence effect of riverine phosphorus

Climatology of wind speed persistence over Turkey

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