Multifractal Characteristics of Cloud-to-Ground Lightning Intensity Observed in AMMA-CATCH Station (Northern Benin)

Agbazo, Médard Noukpo; N’Gobi, Gabin Koto; Adechinan, Adebiyi Joseph; Kounouhéwa, Basile; Houngninou, B. E.; Afouda, Abel

doi:10.1007/s42865-020-00004-7

Cited by 3 publications

(2 citation statements)

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“…According to [9,13,27,[43][44][45], using the Legendre transform, the relationship between the multifractal spectrum f(α) and the generalized Hurst index h(q) can be obtained and written as…”

Section: Multifractal Spectra Analysis (Mfs)mentioning

confidence: 99%

Assessing Nonlinear Dynamics and Trends in Precipitation by Ensemble Empirical Mode Decomposition (EEMD) and Fractal Approach in Benin Republic (West Africa)

et al. 2021

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Climate dynamics and trends have significant environmental and socioeconomic impacts; however, in the Benin Republic, they are generally studied with diverse statistical methods ignoring the nonstationarity, nonlinearity, and self-similarity characteristics contained in precipitation time series. This can lead to erroneous conclusions and an unclear understanding of climatic dynamics. Based on daily precipitation data observed in the six synoptic stations of Benin Republic, in the period from 1951 to 2010, we have proposed (i) determining the local trends of precipitations, (ii) investigating precipitation nonlinear dynamics, and (iii) assessing climatic shift in the study period by Ensemble Empirical Mode Decomposition (EEMD) and Multifractal Detrended Fluctuation Analysis (MFDFA) method. To overcome the detrending issue in the standard MFDFA method, the EEMD algorithm is embedded into the MFDFA. The study period is subdivided into three subperiods: 1951–1970, 1971–1990, and 1991–2010. Intrinsic Mode Functions (IMFs) are obtained according to the climatic region in which the stations are located. Results show that precipitation variation is significantly governed by the five first IMFs, in which oscillation periods vary from 1 to 25 days. The trend curves decrease at all the synoptic stations, and their slope values vary accordingly to the subperiods. Referring to the values of the multifractal spectrum parameters, α 0 , and the width of the spectrum w , consistent changes are observed regardless of the subperiods and the concerned stations. The spatial and temporal variability of precipitation indicates that the multifractal properties are good indicators for assessing changes in precipitation dynamics, and the changes in their features could be explained by the global change than by the local climate variation (climatic zones). Despite the observed differences in multifractal spectra properties from the three subperiods, it is not possible to verify the subdivision of 1951–2010 in three subperiods as it is done by previous studies in West Africa. Our findings can be used in the validation of global and regional climate models since a valid model should explain empirically detected scaling properties in observed data.

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Section: Multifractal Spectra Analysis (Mfs)mentioning

confidence: 99%

Assessing Nonlinear Dynamics and Trends in Precipitation by Ensemble Empirical Mode Decomposition (EEMD) and Fractal Approach in Benin Republic (West Africa)

et al. 2021

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“…It is important to note that all the data collected by both the disdrometer and the LINET are of very good quality and have already been used in several works [5,[24][25][26][27][28].…”

Section: Datamentioning

confidence: 99%

Drop Size Distribution and Lightning Manifestations in AMMA-CATH Area

Joseph

Moumouni²,

François

et al. 2021

JAP

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This paper analyses for the first time in tropical area, the relationship between lightning and DSD (Drop Size Distribution) parameters on rainy events that occurred during the monsoon period. The Lightning data used are collected by the LINET (Lightning Detection Network) while the DSD data were recorded by a distrometer. The correlation was computed within five circles of radius varying between to with a step of . These consecutive areas are centered on the position of the disdrometer. By taking into account only the convective spectra and remove out of the data the cases where there is rain without any lightning and vice versa, all data was computed with a time scale of one minute during each of the rainy events .The results showed that the exponential and polynomial laws fit better our data than the power and linear laws. The highest correlation coefficients are obtained within a radius of about 20 km around the distrometer location. The correlation between the parameter and is the most stable with a correlation coefficient equal to .

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Multifractal analysis of malaria cases in India in a global warming scenario

Dwivedi

Chaturvedi

2023

Journal of Water and Climate Change

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An effort is made to evaluate the multifractal properties of malaria cases in India from 1980 to 2014. The possible changes in these properties in a global warming scenario (during 2014–2049) are also quantified. The malaria cases for this purpose are derived from the VECTRI dynamical malaria model, which uses rainfall and temperature data of Coupled Model Intercomparison Project Phase 6 models for the historical and SSP5–8.5 projection scenario, respectively. It is found that the generalized Hurst exponent h (q) and multifractal spectrum width Δα are strongly nonlinear decreasing functions of order q, thus confirming the multifractal nature (and heterogeneous distribution) of the malaria cases in India. The multifractal spectrum of the malaria cases exhibits right-tailed nature along with high inter-model variability, suggesting that the time series under consideration are fine scale and highly complex in nature. The multifractal spectrum width and change in singularity dimension are used to quantify the strength of multifractality for the historical and future projection scenario. It is demonstrated that the strength of multifractality of malaria cases is likely to decrease with an increase in greenhouse gas concentration, which may be happening due to a persistent increase in malaria cases in India as a result of global warming.

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Multifractal Characteristics of Cloud-to-Ground Lightning Intensity Observed in AMMA-CATCH Station (Northern Benin)

Cited by 3 publications

References 44 publications

Assessing Nonlinear Dynamics and Trends in Precipitation by Ensemble Empirical Mode Decomposition (EEMD) and Fractal Approach in Benin Republic (West Africa)

Assessing Nonlinear Dynamics and Trends in Precipitation by Ensemble Empirical Mode Decomposition (EEMD) and Fractal Approach in Benin Republic (West Africa)

Drop Size Distribution and Lightning Manifestations in AMMA-CATH Area

Multifractal analysis of malaria cases in India in a global warming scenario

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