When dealing with the general problem of turbulence there are several theoretical and practical related problems: the generation (origin) of fluid fluctuations (real eddies and mathematical vorticity), the turbulent transfer of kinetic energy, heat and mass, drag resistance, clean-air fluctuations, hurricanes and tornadoes, atmospheric circulation and plumes, and other natural or human-induced phenomena. We are tempted by the intent to formulate a unified approach, where turbulence is the general feature of these problems. We attempt here to draw some connections between the theoretical turbulence modeling and the experimental results interpreted using such models and the reality of large-scale natural events strongly related to anthropogenic climate changes, such as heatwaves and the cooling effect of aerosols. In fact we believe that more sophisticated practical results could be drawn from connecting theoretical turbulence studies to natural real phenomena, especially those under the influence of climate change. The mathematical modeling aimed at increasing predictability did not produce yet a fundamental breakthrough in the understanding of turbulence. In dealing with real turbulent flows we constantly rely on phenomenological approaches. To date, the large-scale spatio-temporal characteristics of turbulence has yet to be fully understood, due to the lack of sufficient in situ detection instruments in the atmosphere. As such, there is much room for improvement in turbulence-related parameterizations in global weather and climate prediction models. Short presentations of the heatwaves and cooling effect of aerosols are considered from the point of view that the study of weather data and the use of statistical modeling should be coupled with the fundamental studies on the fluid dynamics features of turbulence which play the primary role in the atmospheric circulation and thus in weather and climate changes.
Published in | International Journal of Environmental Monitoring and Analysis (Volume 12, Issue 3) |
DOI | 10.11648/j.ijema.20241203.11 |
Page(s) | 36-47 |
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2024. Published by Science Publishing Group |
Turbulence, Randomness, Vorticity, Heat Transfer, Mass Transfer, Atmosphere Circulation, Heatwaves, Arosols
Condition | Monin-Obukhov Length [m] |
---|---|
Extremely Unstable | |
Unstable | |
Neutral | |L| > 500 |
Stable | |
Extremely Stable |
[1] | Walter Krämer. (2010). The Cult of Statistical Significance. CESifo Network, Working Paper No. 3246, November 2010. |
[2] | Jé Wilson. (2024). Ducks in the Drawing Room. New York Review of Books. March 7. 2024. |
[3] | Werner Heisenberg. (1962). Physics and Philosophy: The Revolution in Modern Science. New York: Harper & Row Publishers, 1962, pag. 58. |
[4] | Edward Lorenz. (1963). Deterministic nonperiodic flow. Journal of Atmospheric Sciences, 1963, pp. 131-141. |
[5] | Kolmogorov, A. N. (1941). The local structure of turbulence in incompressible viscous fluid for very large Reynolds numbers. Doklady Akademii Nauk SSSR. vol. 30, no. 301. 1941. |
[6] | Jörg Schumacher, Janet D. Scheel, Dmitry Krasnov & Katepalli R. Sreenivasan. (2014). Small-scale universality in fluid turbulence. Proceedings National Academy of Sciences. |
[7] | J. S. Turner. (1973). Buoyancy Effects in Fluids. Cambridge University Press, 1973, pag. 335. |
[8] | Robert Ecke. (2005). The Turbulence Problem: An Experimentalist's Perspective. Los Alamos Science, No. 29, 2005, pp. 124-141. |
[9] | U. Frisch. (1985). Turbulence and Predictability in Geophysical Fluid Dynamics and Climate Dynamics. Corso Società Italiana di Fisica. LXXXVIII. 1985, pp. 71-88. |
[10] | A. Arnèodo et al. (2008). Universal Intermittent Properties of Particle Trajectories in Highly Turbulent Flows. International Collaboration for Turbulence Research. Phys. Rev. Lett. |
[11] | P. Bergé, Y. Pomeau & C. Vidal. (1984). Order within Chaos: Towards a Deterministic Approach to Turbulence. John Wiley & Sons, New York, 1984. |
[12] | Ruelle, D., Takens, F. (1971). On the nature of turbulence. Commun. Math. Phys. |
[13] | B. Malraison, P. Atten, P. Berge & M. Dubois. (1983). Dimension of strange attractors: an experimental determination for the chaotic regime of two convective systems. Journal de Physique Lettres. |
[14] | Alberto Vela-Martin. (2021). The synchronization of intense vorticity in isotropic turbulence. Journal of Fluid Mechanics. |
[15] | Absi, R. (2019). Eddy Viscosity and Velocity Profiles in Fully-Developed Turbulent Channel Flows. Fluid Dynamics. |
[16] | S. Lovato, G. H. Keetels, S. L. Toxopeus & J. W. Settels. (2021). An eddy-viscosity model for turbulent flows of Herschel-Bulkley fluids. Journal of Non-Newtonian Fluid Mechanics. |
[17] | P. Roman. (1974). Natural aeration of free surface flows. PhD thesis. University Paul Sabatier. 1974, order no. 417. Toulouse. France. |
[18] | Benoit Mandelbrot. (1967). Sur l'épistémologie du hasard dans les sciences sociales. Vol. Logique et connaissance scientifique, Editions Gallimard, 1967, p. 1112. |
[19] | Hendry J. Breedta, Ken J. Craigs & Venkatesh D.Jothiprakasam. (2018). Monin-Obukhov similarity theory and its application to wind flow modeling over complex terrain. Journal of Wind Engineering and Industrial Aerodynamics. |
[20] | Keith McNaughton. (2009). The rise and fall of Monin-Obukhov theory. AsiaFlux Newsletter. No. 30, September, 2009. |
[21] | L. A. Zadeh. (1978). Fuzzy Sets as a Basis for a Theory of Possibility. Fuzzy Sets and Systems. Vol. 1, pp. 3-28. |
[22] | Prateek Pandey, Shishir Kumar&Sandeep Shrivastava. (2017). An Efficient Time Series Forecasting Method Exploiting Fuzziness and Turbulence in Data. International Journal of FuzzySystemApplications. |
[23] | Landau and Lifschitz. (1971). Fluid Mechanics. Pergamon Press. 1971, pp. 145-155. |
[24] | P. Manneville. (1988). Systèmes dynamiques a grand nombre de degrés de liberté et turbulence. Commissariat a L’Energie Atomique. Vol. Le Chaos. Ch. VII. 1988, pag. 328. |
[25] | J. O. Hinze. (1959). Turbulence. McGraw-Hill, 1959, pag. 402. |
[26] | B. B. Hicks. (1988). Some Introductory Notes to an Issue of Boundary-Layer Meteorology Dedicated to Arthur James Dyer. Boundary-Layer Meteorology, vol. 42, 1988, pp. 1-8. |
[27] | Bruce B. Hicks, William J. Callahan, William R. Pendergrass II, Ronald J. Dobosy & Elena Novakovskaia. (2012). Urban Turbulence in Space and in Time. Journal of Applied Meteorology and Climatology. |
[28] | Jian Zhang, Shao Dong Zhang, Chun Ming Huang, Kai Ming Huang, Yun Gong, Quan Gan & Ye Hui Zhang. (2019). Statistical Study of Atmospheric Turbulence by Thorpe Analysis. Journal of Geophysical Research. |
[29] | Yanmin Lu, Jianping Guo, Jian Li, Lijuan Cao, Tianmeng Chen, Ding Wang, Dandan Chen, Yi Han, Xiaoran Guo & Hui Xu. (2021). Spatiotemporal characteristics of atmospheric turbulence over China estimated using operational high-resolution soundings. Environmental Research Letters. |
[30] | Victor Nosov, Vladimir Lukin, Eugene Nosov, Andrei Torgaev & Aleksandr Bogushevich. (2021). Measurement of Atmospheric Turbulence Characteristics by the Ultrasonic Anemometers and the Calibration Processes. Atmosphere. |
[31] | Salvo Rizzo & Andrea Rapisarda. (2004). Application of Superstatistics to Atmospheric Turbulence. Proceedings of the 8th Experimental Chaos Conference, Florence. |
[32] | C. Beck, E. G. D. Cohen & S. Rizzo. (2005). Atmospheric turbulence and superstatistics. Europhysics News. |
[33] | J. C. R. Hunt & J. C. Vassilicos. (1991). Kolmogorov's Contributions to the Physical and Geometrical Understanding of Small-Scale Turbulence and Recent Developments. Proceedings: Mathematical and Physical Sciences, Vol. 434, No.1890, 1991, pp. 183-210. |
[34] | Michel Talagrand. (2021). Upper and Lower Bounds for StochasticProcesses. SpringerVerlag. |
[35] | Giorgio Parisi. (2024). Mathematician wins 2024 Abel prize for making sense of randomness. New Scientist, 20 March 2024. |
[36] | Herbert Riehl. (1962). Jet Streams of the Atmosphere. Technical Report No. 32, Department of Atmospheric Science, Colorado State University, Fort Collins. Colorado, 1962. |
[37] | Kai Kornhuber, Scott McManus Osprey, Dim Coumo&Stefan Petri. (2019). Extreme weather events in early summer 2018 connected by a recurrent hemispheric wave-7 pattern. Environmental Research Letters. |
[38] | D. Barriopedro, R. García-Herrera, C. Ordóñez, D. G. Miralles & S. Salcedo-Sanz. (2023). Heat Waves: Physical Understanding and Scientific Challenges. Review of Geophysics. |
[39] | Haina Gong, Kangjie Ma, Zhiyuan Hu, Zizhen Dong, Yuanyuan Ma, Wen Chen, Renguang Wu & Lin Wang. (2024). Attribution of the August 2022 Extreme Heatwave in Southern China: Role of Dynamical and Thermodynamic Processes. American Meteorological Society. |
[40] | Solomon Marcus. (2008). The loneliness of the mathematician. Romanian Academy of Sciences. Acceptance lecture. Spandugino. |
[41] | Akshay Bhatnagar, K. Gustavsson & Dhrubaditya Mitra. (2017). Statistics of the relative velocity of particles in turbulent flows: monodisperse particles”. American Physical Society. |
[42] | J. Bec, L. Biferale, M. Cencini, A. Lanotte, S. Musacchio & F. Toschi. (2007). Heavy Particle Concentration in Turbulence at Dissipative and Inertial Scales. Physical Review Letters. |
[43] | M. Wacławczyk, J. L. Nowak & S. P. Malinowski. (2022). Non-equilibrium dissipation scaling in atmospheric turbulence. Journal of Physics: Conference Series. |
[44] | G. Myhre, C. E. L. Myhre, B. H. Samset & Sisi Chen, Lulin Xue, Man-Kong Yau, T. Storelvmo. (2013). Aerosols and their Relation to Global Climate and Climate Sensitivity. Nature Education Knowledge. |
[45] | Hiroyuki Murakami. (2022). Substantial global influence of anthropogenic aerosols on tropical cyclones over the past 40 years. Science Advances. |
[46] | P. Duru, D. L. Koch & C. Cohen. (2007). Experimental study of turbulence-induced coalescence in aerosols. International Journal of Multiphase Flow. |
[47] | Arkadi Zilberman, Ephim Golbraikh, Norman S. Kopeika, Alexander Virtser, Igor Kupershmidt&Yuri Shtemler. (2008). Lidar study of aerosol turbulence characteristics in the troposphere: Kolmogorov and non-Kolmogorov turbulence. Atmospheric Research. |
[48] | Sisi Chen, Lulin Xue&Man-Kong Yau. (2020). Impact of aerosols and turbulence on cloud droplet growth: an in-cloud seeding case study using a parcel–DNS (direct numerical simulation) approach. Atmospheric Chemistry and Physics. |
[49] | Kay McMonigal. (2024). Aerosols hold the key to recent and future Pacific warming patterns. Proceedings of the Academy of Sciences. |
[50] |
Yen-Ting Hwanga, Shang-Ping Xieb, Po-Ju Chena, Hung-Yi Tsenga&Clara Dese. (2024). Contribution of anthropogenic aerosoles to persistent La Niña-like conditions in the early 21st century. PNAS, Earth, Atmospheric, and Planetary Sciences.
https://doi.org/10.1073/pnas.2315124121 Corpus ID: 267093806 |
APA Style
Roman, P. (2024). Multiple Consequences Related to Atmospheric Turbulence Induced by the Climate Change in the Heatwaves Emergence and in the Cooling Effect of Aerosols. International Journal of Environmental Monitoring and Analysis, 12(3), 36-47. https://doi.org/10.11648/j.ijema.20241203.11
ACS Style
Roman, P. Multiple Consequences Related to Atmospheric Turbulence Induced by the Climate Change in the Heatwaves Emergence and in the Cooling Effect of Aerosols. Int. J. Environ. Monit. Anal. 2024, 12(3), 36-47. doi: 10.11648/j.ijema.20241203.11
AMA Style
Roman P. Multiple Consequences Related to Atmospheric Turbulence Induced by the Climate Change in the Heatwaves Emergence and in the Cooling Effect of Aerosols. Int J Environ Monit Anal. 2024;12(3):36-47. doi: 10.11648/j.ijema.20241203.11
@article{10.11648/j.ijema.20241203.11, author = {Petre Roman}, title = {Multiple Consequences Related to Atmospheric Turbulence Induced by the Climate Change in the Heatwaves Emergence and in the Cooling Effect of Aerosols }, journal = {International Journal of Environmental Monitoring and Analysis}, volume = {12}, number = {3}, pages = {36-47}, doi = {10.11648/j.ijema.20241203.11}, url = {https://doi.org/10.11648/j.ijema.20241203.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20241203.11}, abstract = {When dealing with the general problem of turbulence there are several theoretical and practical related problems: the generation (origin) of fluid fluctuations (real eddies and mathematical vorticity), the turbulent transfer of kinetic energy, heat and mass, drag resistance, clean-air fluctuations, hurricanes and tornadoes, atmospheric circulation and plumes, and other natural or human-induced phenomena. We are tempted by the intent to formulate a unified approach, where turbulence is the general feature of these problems. We attempt here to draw some connections between the theoretical turbulence modeling and the experimental results interpreted using such models and the reality of large-scale natural events strongly related to anthropogenic climate changes, such as heatwaves and the cooling effect of aerosols. In fact we believe that more sophisticated practical results could be drawn from connecting theoretical turbulence studies to natural real phenomena, especially those under the influence of climate change. The mathematical modeling aimed at increasing predictability did not produce yet a fundamental breakthrough in the understanding of turbulence. In dealing with real turbulent flows we constantly rely on phenomenological approaches. To date, the large-scale spatio-temporal characteristics of turbulence has yet to be fully understood, due to the lack of sufficient in situ detection instruments in the atmosphere. As such, there is much room for improvement in turbulence-related parameterizations in global weather and climate prediction models. Short presentations of the heatwaves and cooling effect of aerosols are considered from the point of view that the study of weather data and the use of statistical modeling should be coupled with the fundamental studies on the fluid dynamics features of turbulence which play the primary role in the atmospheric circulation and thus in weather and climate changes. }, year = {2024} }
TY - JOUR T1 - Multiple Consequences Related to Atmospheric Turbulence Induced by the Climate Change in the Heatwaves Emergence and in the Cooling Effect of Aerosols AU - Petre Roman Y1 - 2024/05/17 PY - 2024 N1 - https://doi.org/10.11648/j.ijema.20241203.11 DO - 10.11648/j.ijema.20241203.11 T2 - International Journal of Environmental Monitoring and Analysis JF - International Journal of Environmental Monitoring and Analysis JO - International Journal of Environmental Monitoring and Analysis SP - 36 EP - 47 PB - Science Publishing Group SN - 2328-7667 UR - https://doi.org/10.11648/j.ijema.20241203.11 AB - When dealing with the general problem of turbulence there are several theoretical and practical related problems: the generation (origin) of fluid fluctuations (real eddies and mathematical vorticity), the turbulent transfer of kinetic energy, heat and mass, drag resistance, clean-air fluctuations, hurricanes and tornadoes, atmospheric circulation and plumes, and other natural or human-induced phenomena. We are tempted by the intent to formulate a unified approach, where turbulence is the general feature of these problems. We attempt here to draw some connections between the theoretical turbulence modeling and the experimental results interpreted using such models and the reality of large-scale natural events strongly related to anthropogenic climate changes, such as heatwaves and the cooling effect of aerosols. In fact we believe that more sophisticated practical results could be drawn from connecting theoretical turbulence studies to natural real phenomena, especially those under the influence of climate change. The mathematical modeling aimed at increasing predictability did not produce yet a fundamental breakthrough in the understanding of turbulence. In dealing with real turbulent flows we constantly rely on phenomenological approaches. To date, the large-scale spatio-temporal characteristics of turbulence has yet to be fully understood, due to the lack of sufficient in situ detection instruments in the atmosphere. As such, there is much room for improvement in turbulence-related parameterizations in global weather and climate prediction models. Short presentations of the heatwaves and cooling effect of aerosols are considered from the point of view that the study of weather data and the use of statistical modeling should be coupled with the fundamental studies on the fluid dynamics features of turbulence which play the primary role in the atmospheric circulation and thus in weather and climate changes. VL - 12 IS - 3 ER -