Climate change-induced influences on the nonlinear dynamic patterns of precipitation and temperatures (case study: Central England)

Rahmani, Farhang; Fattahi, Mohammad Hadi

doi:10.1007/s00704-023-04424-1

Cited by 8 publications

(4 citation statements)

References 76 publications

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“…Similar results were found for Spain and England [58,64], indicating that multifractal analysis could be useful (along with classical statistical methods) in evaluation of climate change impact on air temperature fluctuations. By providing the information about the nature of underlying process (described by the parameters of multifractal spectrum) it could also be useful for validation of global and regional climate models, since a valid model should explain empirically detected scaling properties in observed data.…”

Section: Discussionsupporting

confidence: 75%

“…Qualitatively, our results agree well with the results obtained for other European countries. Multifractality of air temperature series were found for Spain [58,59], Greece [60,61], Poland [62,63] and England [64] with the same specific features as for Serbia: persistent long-term correlations (α 0 > 0.5) and the dominance of small fluctuations (right-skewed spectrum). Gos et al [63] compared multifractal properties of air pressure, air temperature and wind speed in Poland, from ground base data (35 meteorological stations) and reanalysis gridded MERRA-2 dataset, for the period 2007-2016 on hourly and daily resolution.…”

Section: Comparison With Studies From Other Countriesmentioning

confidence: 59%

“…In the second period the position of maximum of multifractal spectrum shifts to the right (the value of α 0 increases indicating stronger persistence) and the width of the spectrum decreased indicating lower degree of multifractality. Rahmani and Fattahi [64] investigated the influence of climate change on multifractal properties of precipitation and temperatures in central England (recorded in 11 stations) by applying MFDFA on daily and monthly data for two subperiods (1931-1989 and 1990-2019). They found that climate change induces shift in multifractal strength for all analyzed variables: on daily scale, the increase in multifractality for precipitation and maximum temperature and decrease in multifractality for minimum temperature, on monthly scale all variables display weaker multifractality which decreased for precipitation and increased for temperature in the second period.…”

Section: Comparison With Studies From Other Countriesmentioning

confidence: 99%

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Climate Change Effects through MFDFA Study of Temperature in Serbia

Stosic,

Tošić

et al. 2023

Atmosphere

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We investigate multifractal properties of daily means of air temperature over the territory of Serbia, by using Multifractal detrended fluctuation analysis. Temperature anomalies in two periods 1961–1990 and 1991–2020 are calculated from the E-OBSv26.0e gridded dataset with 0.10° (~12 km) resolution, totaling 1278 daily temperature series for each period. The MFDFA parameters: position of the maximum of the spectrum α0, width of the spectrum W and asymmetry r, obtained from the total of 2556 MFDFA runs are interpolated to yield their spatial distribution across Serbia in the two periods. We found several patterns in both the spatial distribution, and changes from first to second period. All series showed multifractal properties with overall persistent long-term correlations (α0 > 0.5) and the dominance of small fluctuations (r > 0). The persistence is weaker (smaller α0 values) and multifractality is stronger (larger width W) in southern mountainous regions. In the second period the values of α0 increased indicating stronger persistence of temperature dynamics, while multifractality became stronger (larger W) in northern region and weaker (smaller W) in southern region. In both periods the contribution to multifractality was dominated by small fluctuations (r > 0) that become stronger in the second period, indicated by the increase of the values of r over most of the country’s area. These changes in the values of multifractal parameters indicate the increase of complexity of temperature dynamics in the second 30 years period which could be related to climate change.

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Section: Discussionsupporting

confidence: 75%

Section: Comparison With Studies From Other Countriesmentioning

confidence: 59%

Section: Comparison With Studies From Other Countriesmentioning

confidence: 99%

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Climate Change Effects through MFDFA Study of Temperature in Serbia

Stosic,

Tošić

et al. 2023

Atmosphere

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“…DFA is a reliable method for spotting long-range power-law relationships in noisy, brief, non-stationary signals [1,64]. DFA has been successfully employed in different scientific domains such as the study of changes in the weather and climate [65][66][67][68], DNA sequences [69,70], heart dynamics [71][72][73][74], urban air pollution [37,39,61], pre-earthquake recordings of radon in soil [25,26], and electromagnetic variations in ULF, kHz, and MHz ranges [1,[75][76][77][78][79].…”

Section: Detrended Fluctuation Analysis (Dfa)mentioning

confidence: 99%

Fractal Patterns in Groundwater Radon Disturbances Prior to the Great 7.9 Mw Wenchuan Earthquake, China

Alam,

Nikolopoulos,

Wang

2023

Geosciences

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This study reports a fractal analysis of one-year radon in groundwater disturbances from five stations in China amidst the catastrophic Wenchuan (Mw = 7.9) earthquake of 12 May 2008 (day 133). Five techniques are used (DFA, fractal dimensions with Higuchi, Katz, Sevcik methods, power-law analysis) in segmented portions glided throughout each signal. Noteworthy fractal areas are outlined in the KDS, GS, MSS data, whilst the portions were non-significant for PZHS and SPS. Up to day 133, critical epoch DFA-exponents are 1.5≤α<2.0, with several above 1.8. The fractal dimensions exhibit Katz’s D around 1.0–1.2, Higuchi’s D between 1.5 and 2.0, and Sevcik’s D between 1.0 and 1.5. Several power-law exponents are above 1.7, and numerous are above 2.0. All fractal results of the KDS-GS-MSS are further analysed using a novel computerised methodology that locates the exact out-of-threshold fractal areas and combines the outcomes of different methods per five, four, three, and two (maximum 13 combinations) versus nineteen Mw≥ 5.5 earthquakes of the greater area. Most coincidences using different techniques are before the great Wenchuan earthquake and after the earthquake. This is not only with one method but with 13 different methods. Other interpretations are also discussed.

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Groundwater level complexity analysis based on multifractal characteristics: a case study in Baotu Spring Basin, China

Niu,

Shu,

et al. 2023

Theor Appl Climatol

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Groundwater resources are important natural resources that must be appropriately managed. Because groundwater level uctuation typically exhibits non-stationarity, revealing its complex characteristics is of scienti c and practical signi cance for understanding the response mechanism of the groundwater level to natural or human factors. Therefore, employing multifractal analysis to detect groundwater level variation irregularities is necessary. In this study, multifractal detrended uctuation analysis (MF-DFA) was applied to study the multifractal characteristics of the groundwater level in the Baotu Spring Basin and further detect the complexity of groundwater level variation. The main results indicate that groundwater level variation in the Baotu Spring Basin exhibited multifractal characteristics, and multifractality originated from broad probability density function (PDF) and the long-range correlation of the hydrological series. The groundwater level uctuations in wells 358 and 361 exhibited a high complexity, those in wells 287 and 268 were moderately complex, and the groundwater level uctuations in wells 257 and 305 were characterized by a low complexity. The spatial variability of hydrogeological conditions resulted in spatial heterogeneity in the groundwater level complexity. This study could provide important reference value for the analysis of the nonlinear response mechanism of groundwater to its in uencing factors and the development of hydrological models.

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Climate change-induced influences on the nonlinear dynamic patterns of precipitation and temperatures (case study: Central England)

Cited by 8 publications

References 76 publications

Climate Change Effects through MFDFA Study of Temperature in Serbia

Climate Change Effects through MFDFA Study of Temperature in Serbia

Fractal Patterns in Groundwater Radon Disturbances Prior to the Great 7.9 Mw Wenchuan Earthquake, China

Groundwater level complexity analysis based on multifractal characteristics: a case study in Baotu Spring Basin, China

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