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Stochastic method to determine the scale and anomalous diffusion of gusts in a windy atmospheric boundary layer

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  • Atmospheric Science
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Chinese Science Bulletin

Abstract

In the atmospheric boundary layer, especially during strong wind period, the coherent structures are obvious and related to the direct interaction of the air masses with the ground. In this paper, we used the observation data during dust weather in Northwest Gansu to study the coherent structure and their “anomalous diffusion”. The structures in the atmospheric boundary layer included turbulent fluctuations and gusty wind disturbances, and could be denoted as “critical events”. Their fractal dimensions were expressed by the complex index μ of waiting times. Although the complex index can indicate the ability of the system to generate coherent structures, it has a strong dependence on the threshold marking the “critical events”. Hence, the continuous time random walk method was used to analyze the coherent structures. The scaling law of anomalous diffusion of coherent structures was obtained, and the diffusion scaling exponent H that indicated the ability of diffusion of different structures was analyzed. The exponents changed with structure scales which were affected by velocities and heights. At small scales, it was almost isotropic, and at large scales, the coherent structures were obvious and the diffusion was anomalous.

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References

  1. Zhang Q, Zeng J, Yao T et al (2011) Relationship of atmospheric boundary layer depth with thermodynamic processes at the land surface in arid regions of China. Sci China Earth Sci 57:1586–1594

    Article  Google Scholar 

  2. Zhang Q, Zeng J, Yao T (2012) Interaction of aerodynamic roughness length and windflow conditions and its parameterization over vegetation surface. Chin Sci Bull 57:1559–1567

    Article  Google Scholar 

  3. Kaimal JC, Finnigan JJ (1994) Atmospheric boundary layer flows: their structure and measurement. Oxford University Press, New York

    Google Scholar 

  4. Katul G, Hsieh C, Kuhn G et al (1997) Turbulent eddy motion at the forest-atmosphere interface. J Geophys Res 102:13409–13421

    Article  Google Scholar 

  5. Zeng QC, Cheng XL, Hu F et al (2010) Gustiness and coherent structure of strong wind and their role in the dust emission and entrainment. Adv Atmos Sci 27:1–13

    Article  Google Scholar 

  6. Cheng XL, Zeng QC, Hu F (2011) Characteristics of gusty wind disturbances and turbulent fluctuations in windy atmospheric boundary layer behind cold fronts. J Geophys Res 116:D06101

    Google Scholar 

  7. Cheng XL, Zeng QC, Hu F (2012) Parameterizations of some important characteristics of turbulences and gusts in the atmospheric boundary layer. J Geophys Res 117:D08113

    Google Scholar 

  8. Cheng XL, Zeng QC, Hu F (2012) Stochastic modeling the effect of wind gust on dust entrainment during sand storm. Chin Sci Bull 57:3595–3602

    Article  Google Scholar 

  9. Paradisi P, Cesari R, Donateo A et al (2012) Scaling laws of diffusion and time intermittency generated by coherent structures in atmospheric turbulence. Nonlinear Proc Geophys 19:113–126

    Article  Google Scholar 

  10. WMO (2008) Guide to meteorological instruments and methods of observation, 7th edn. World Meteorological Organization, Geneva

    Google Scholar 

  11. Stathopoulos T (2007) Introduction to wind engineering, wind structure, wind-building interaction. CISM Int Centre Mech Sci 493:1–30

    Article  Google Scholar 

  12. Montroll EW (1964) Random walks on lattices. Proc Symp Appl Math 16:193–220

    Article  Google Scholar 

  13. Kenkre VM, Montroll EW, Shlesinger MF (1973) Generalized master equations for continuous-time random walks. J Stat Phys 9:45–50

    Article  Google Scholar 

  14. Weiss GH, Rubin RJ (1983) Random walks: theory and selected applications. Adv Chem Phys 52:363–505

    Google Scholar 

  15. Grigolini P, Leddon D, Scafetta N (2002) Diffusion entropy and waiting time statistics of hard X-ray solar flares. Phys Rev E 65:046203

    Article  Google Scholar 

  16. Allegrini P, Barbi F, Grigolini P et al (2006) Renewal, modulation, and superstatistics in times series. Phys Rev E 73:046136

    Article  Google Scholar 

  17. Allegrini P, Bologna M, Grigolini P et al (2007) Fluctuation-dissipation theorem for event dominated processes. Phys Rev Lett 99:010603

    Article  Google Scholar 

  18. Grigolini P, Palatella L, Raffaelli G (2001) Asymmetric anomalous diffusion: an efficient way to detect memory in time series. Fractals 9:439

    Article  Google Scholar 

  19. Allegrini P, Menicucci D, Bedini R et al (2009) Spontaneous brain activity as a source of ideal 1/f noise. Phys Rev E 80:061914

    Article  Google Scholar 

  20. Schmitt F, Vannitsem S, Barbosa A (1998) Modeling of rainfall time series using two-state renewal processes and multifractals. J Geophys Res 103:23181–23193

    Article  Google Scholar 

  21. Peng CK, Buldyrev SV, Havlin S et al (1994) Mosaic organization of DNA nucleotides. Phys Rev E 49:1685–1689

    Article  Google Scholar 

  22. Zhao M, Zhan KJ, Yang ZH et al (2010) Characteristics of the lower layer of sandstorms in the Minqin desert-oasis zone. Sci China Earth Sci 40:1–9 (in Chinese)

    Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (40830103 and 41375018), the National Basic Research Program of China (2010CB951804), the strategy guide for the specific task of the Chinese Academy of Sciences (XDA05000000, XDA05040301), and Special Finance from China Meteorological Administration (GYHY200706034). The authors are very grateful to Y. J. Zhao and W. D. Luo from the Institute of Atmospheric Physics, Chinese Academy of Sciences for their help.

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The authors declare that they have no conflict of interest.

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Correspondence to Fei Hu.

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Cheng, X., Hu, F. & Zeng, Q. Stochastic method to determine the scale and anomalous diffusion of gusts in a windy atmospheric boundary layer. Chin. Sci. Bull. 59, 4890–4898 (2014). https://doi.org/10.1007/s11434-014-0550-9

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  • DOI: https://doi.org/10.1007/s11434-014-0550-9

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