Exploring the Indian summer monsoon rainfall through multifractal detrended fluctuation analysis and the principle of entropy maximization

Chakraborty, Sombit; Chattopadhyay, Surajit

doi:10.1007/s12145-021-00641-2

Cited by 14 publications

(3 citation statements)

References 41 publications

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“…Modern geoscience and environmental studies imply the application of advanced mathematical techniques focused on complex dataset analysis [28]. This is mainly due to such data features as nonstationarity, sporadic disturbances, large data sets, etc.…”

Section: Discussionmentioning

confidence: 99%

A Multiscale Approach to Geomagnetic Storm Morphology Analysis Based on DMA Activity Measures

et al. 2021

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The article is focused on the approach based on the discrete mathematical analysis conception and continues a series of studies related to the application of the previously developed methodology to geophysical data analysis. The main idea of the study is the modification of earlier conceptions regarding the interpreter’s logic that allows introducing a multiscale approach and performing the time series analysis using the activity measure plots, implying the vertical scale. This approach was used to study the morphology of several intense geomagnetic storms at the final stages of the 23rd and 24th solar activity cycles. Geomagnetic observatory data and interplanetary magnetic field parameters as well as the solar wind flux speed and proton density were analyzed for each of the studied storms using the activity measures. The developed methods, applied to geomagnetic storm morphological analysis, displayed good results in revealing the decreases and increases in various durations and intensities during storms, detecting low-amplitude disturbances, and storm sudden commencement recognition. The results provide an opportunity to analyze any physical data using a unified scale and, in particular, to implement this approach to geomagnetic activity studies.

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Section: Discussionmentioning

confidence: 99%

A Multiscale Approach to Geomagnetic Storm Morphology Analysis Based on DMA Activity Measures

et al. 2021

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“…This modified approach is applied to evaluate the long-term persistence of precipitation time series in Dongting Lake Basin, China. Also, Indian Monsoon precipitation persistence has been analyzed very recently with DFA [111] and MF-DFA algorithms [112].…”

Section: Long-term Persistence In Atmospheric and Climatic Processesmentioning

confidence: 99%

Persistence in complex systems

et al. 2022

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“…There is an abundance of literature on long-range dependence for time series data, such as biomedical data [3][4][5], stock returns [6][7][8], hydrology [9][10][11], and climatology [12][13][14]. However, only a few studies focus on traffic flow sequences [15,16] and the research on maritime traffic flow sequences are very limited.…”

Section: Introductionmentioning

confidence: 99%

Long-Range Dependence and Multifractality of Ship Flow Sequences in Container Ports: A Comparison of Shanghai, Singapore, and Rotterdam

Liu

Jayetileke

et al. 2021

Applied Sciences

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The prediction of ship traffic flow is an important fundamental preparation for layout and design of ports as well as management of ship navigation. However, until now, the temporal characteristics and accurate prediction of ship flow sequence in port are rarely studied. Therefore, in this study, we investigated the presence of long-range dependence in container ship flow sequences using the Multifractal Detrended Fluctuation Analysis (MF-DFA). We considered three representative container ports in the world—including Shanghai, Singapore, and Rotterdam container ports—as the study sample, from 1 January 2013 to 31 December 2017. Empirical results suggested that the ship flow sequences are deviated from normal distribution, and the sequences with different time scales exhibited varying degrees of long-range dependence. Furthermore, the ship flow sequences possessed a multifractal nature, where the larger the time scale of ship flow time series, the stronger the multifractal characteristics are. The weekly ship flow sequence in the port of Singapore owned the highest degree of multifractality. Furthermore, the multifractality presented in the ship flow sequences of container ports are due to the correlation properties as well as the probability density function of the ship flow sequences. The study outlines the importance of adopting these features for an accurate modeling and prediction for maritime ship flow series.

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Exploring the Indian summer monsoon rainfall through multifractal detrended fluctuation analysis and the principle of entropy maximization

Cited by 14 publications

References 41 publications

A Multiscale Approach to Geomagnetic Storm Morphology Analysis Based on DMA Activity Measures

A Multiscale Approach to Geomagnetic Storm Morphology Analysis Based on DMA Activity Measures

Persistence in complex systems

Long-Range Dependence and Multifractality of Ship Flow Sequences in Container Ports: A Comparison of Shanghai, Singapore, and Rotterdam

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