Multifractal features and dynamical thresholds of temperature extremes in Bangladesh
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Affiliation
Shandong UniversityBeijing Normal University
Oxford Universi
University of Bedfordshire
University of Chittagong
Issue Date
2023-07-13
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Multifractal detrended fluctuation analysis (DFA) can extract multi-scaling behavior and measure long-range correlations in climatic time series. In this study, with the help of multifractal DFA, we investigated the scaling behavior of daily minimum/maximum temperatures during the years 1989–2019 from 34 meteorological stations in Bangladesh. We revealed spatial patterns, topographic impacts and global warming impacts of long-range correlations embedded in small and large fluctuations in temperature time series. Meanwhile, we developed a multifractal DFA-based algorithm to dynamically determine thresholds to discriminate extreme and non-extreme events in climate systems and applied it to analyze the frequency and trends of temperature extremes in Bangladesh. Compared with widely-used percentile thresholds, the extreme climate events captured in our algorithm are more reliable since they are determined dynamically by the climate system itself.Citation
Liu A, Zhang Z, Crabbe MJC, Das LC (2023) 'Multifractal features and dynamical thresholds of temperature extremes in Bangladesh', Fractal and Fractional, 7 (7) 540Publisher
MDPIJournal
Fractal and FractionalAdditional Links
https://www.mdpi.com/2504-3110/7/7/540Type
ArticleLanguage
enISSN
2504-3110Sponsors
European Commission Horizon 2020 Framework Program No. 861584 and the Taishan Distinguished Professor Fund No. 20190910.ae974a485f413a2113503eed53cd6c53
10.3390/ fractalfract7070540
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