Multifractality via Stochasticity in Atmospheric Dynamics Description Validated through Remote Sensing Data

Dragos-Constantin Nica, Mirela Voiculescu, Daniel-Eduard Constantin, Manuela Gîrțu, Liliana Topliceanu, Decebal Vasincu, Iulian-Alin Roșu and Maricel Agop
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Dragos-Constantin Nica: Department of Geography, Faculty of Geography and Geology, “Alexandru Ioan Cuza” University of Iaşi, 700505 Iaşi, Romania
Mirela Voiculescu: Faculty of Sciences and Environment, “Dunărea de Jos” University of Galati, 800008 Galati, Romania
Daniel-Eduard Constantin: Faculty of Sciences and Environment, “Dunărea de Jos” University of Galati, 800008 Galati, Romania
Manuela Gîrțu: Department of Mathematics and Informatics, “Vasile Alecsandri” University of Bacău, 600115 Bacău, Romania
Liliana Topliceanu: Faculty of Engineering, “Vasile Alecsandri” University of Bacău, 600115 Bacău, Romania
Decebal Vasincu: Department of Biophysics, Faculty of Dental Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iaşi, Romania
Iulian-Alin Roșu: Faculty of Physics, “Alexandru Ioan Cuza” University of Iaşi, 700505 Iaşi, Romania
Maricel Agop: Department of Physics, “Gheorghe Asachi” Technical University of Iaşi, 700050 Iaşi, Romania

Mathematics, 2022, vol. 10, issue 6, 1-21

Abstract: In the present paper, correlations between multifractality and stochasticity in atmospheric dynamics are investigated. Starting with two descriptions of atmospheric scenarios, one based on scale relativity theory and another based on stochastic theory, correspondences between parameters and variables belonging to both scenarios are found. In such a context, by replacing an atmospheric conservative passive additive with a non-differentiable component of the atmospheric multifractal velocity, stochastic evolution equations are found for this component, which reveal the multifractal variational transport coefficient and the multifractal molecular diffusion coefficient, along with the multifractal inhomogeneity variation. Furthermore, equations which describe a multifractal Reynolds number and singularity spectrum are also found. Finally, these theoretical results are validated through remote sensing data obtained with the aid of a ceilometer platform.

Keywords: atmosphere; multifractal; stochastic; laminarity; turbulence; ceilometer (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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