Multifractal features and dynamical thresholds of temperature extremes in Bangladesh
Beijing Normal University
University of Bedfordshire
University of Chittagong
MetadataShow full item record
AbstractMultifractal 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.
CitationLiu A, Zhang Z, Crabbe MJC, Das LC (2023) 'Multifractal features and dynamical thresholds of temperature extremes in Bangladesh', Fractal and Fractional, 7 (7) 540
JournalFractal and Fractional
SponsorsEuropean Commission Horizon 2020 Framework Program No. 861584 and the Taishan Distinguished Professor Fund No. 20190910.
The following license files are associated with this item:
- Creative Commons