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Mathematics
Volume 10
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10.3390/math10061004
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Article

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

by
Dragos-Constantin Nica
1,
Mirela Voiculescu
2,
Daniel-Eduard Constantin
2,
Manuela Gîrțu
3,
Liliana Topliceanu
4,
Decebal Vasincu
5,
Iulian-Alin Roșu
6,7,* and
Maricel Agop
7,8
1
Department of Geography, Faculty of Geography and Geology, “Alexandru Ioan Cuza” University of Iaşi, 700505 Iaşi, Romania
2
Faculty of Sciences and Environment, “Dunărea de Jos” University of Galati, 800008 Galati, Romania
3
Department of Mathematics and Informatics, “Vasile Alecsandri” University of Bacău, 600115 Bacău, Romania
4
Faculty of Engineering, “Vasile Alecsandri” University of Bacău, 600115 Bacău, Romania
5
Department of Biophysics, Faculty of Dental Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iaşi, Romania
6
Faculty of Physics, “Alexandru Ioan Cuza” University of Iaşi, 700505 Iaşi, Romania
7
Department of Physics, “Gheorghe Asachi” Technical University of Iaşi, 700050 Iaşi, Romania
8
Romanian Scientists Academy, 010071 Bucharest, Romania
*
Author to whom correspondence should be addressed.
Mathematics 2022, 10(6), 1004; https://doi.org/10.3390/math10061004
Submission received: 17 February 2022 / Revised: 14 March 2022 / Accepted: 16 March 2022 / Published: 21 March 2022
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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 atmosphere; multifractal; stochastic; laminarity; turbulence; ceilometer

Share and Cite

MDPI and ACS Style

Nica, D.-C.; Voiculescu, M.; Constantin, D.-E.; Gîrțu, M.; Topliceanu, L.; Vasincu, D.; Roșu, I.-A.; Agop, M. Multifractality via Stochasticity in Atmospheric Dynamics Description Validated through Remote Sensing Data. Mathematics 2022, 10, 1004. https://doi.org/10.3390/math10061004

AMA Style

Nica D-C, Voiculescu M, Constantin D-E, Gîrțu M, Topliceanu L, Vasincu D, Roșu I-A, Agop M. Multifractality via Stochasticity in Atmospheric Dynamics Description Validated through Remote Sensing Data. Mathematics. 2022; 10(6):1004. https://doi.org/10.3390/math10061004

Chicago/Turabian Style

Nica, Dragos-Constantin, Mirela Voiculescu, Daniel-Eduard Constantin, Manuela Gîrțu, Liliana Topliceanu, Decebal Vasincu, Iulian-Alin Roșu, and Maricel Agop. 2022. "Multifractality via Stochasticity in Atmospheric Dynamics Description Validated through Remote Sensing Data" Mathematics 10, no. 6: 1004. https://doi.org/10.3390/math10061004

APA Style

Nica, D.-C., Voiculescu, M., Constantin, D.-E., Gîrțu, M., Topliceanu, L., Vasincu, D., Roșu, I.-A., & Agop, M. (2022). Multifractality via Stochasticity in Atmospheric Dynamics Description Validated through Remote Sensing Data. Mathematics, 10(6), 1004. https://doi.org/10.3390/math10061004

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