Abstract
In part I, the clear air echo in front of the squall line is caused by turbulence diffraction, which makes the ZDR echo characteristics different from particle scattering. To study the turbulence deformation phenomenon that is affected by environmental wind, the turbulence-related method is used to analyze the characteristics of three-dimensional turbulence energy spectrum density, and the parametric model of turbulence integral length scale and environmental wind speed is established. The results show that the horizontal scale of turbulence is generally larger than the vertical scale. The turbulence is nearly isotropic in the horizontal direction, presenting a flat ellipsoid with the vertical orientation of the rotation axis when there is no horizontal wind or the horizontal velocity is small. When horizontal wind exists, the turbulence scale increases along the dominant wind direction. The turbulence scale is positively correlated with the wind speed. The power function is used to fit the relationships of turbulence integral length scale and horizontal wind speed, which obtains the best fitting effect, and the goodness of fit (GF) is above 0.99 in each direction. The deforming turbulence can cause 8–9 dB ZDR anomalies in the echo of dual polarization radar, which the ratio of scales in the dominant wind and the vertical direction of deforming turbulence (Lu/Lw) is around 4.3. The variation in ZDR depends on the turbulence shape, orientation and the relative position between turbulence and radar. The shape of turbulence derived from radar detection results is consistent with that of the parametric model, which can provide a parametric scheme for turbulence research. The results reveal the mechanism of abnormal ZDR echo caused by deforming turbulence.
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References
Bian J, Qiao J, Lv D (2002). Reanalysis of the turbulent spectra in the atmospheric surface layer. Chin J Atmos Sci, 26(4): 474–480
Bragg W L (1913). The structure of some crystals as indicated by their diffraction of X-rays. Proc R Soc Lond, 89(610): 248–277
Businger J A, Wyngaard J C, Izumi Y, Bradley E F (1971). Flux-profile relationships in the atmospheric surface layer. J Atmos Sci, 28(2): 181–189
Doviak R J, Zrnic D S, Schotland R M (1994). Doppler Radar and weather observations. Appl Opt, 33(21): 4531
Du M, Liu L, Hu Z, Yu R (2012). Quality control of differential propagation phase shift for dual linear polarization radar. Journal of Applied Meteorological Science, 23(6): 710–720
Frank J M, Massman W J, Ewers B E (2013). Underestimates of sensible heat flux due to vertical velocity measurement errors in nonorthogonal sonic anemometers. Agric Meteorol, 171–172: 72–81
Guo J, Bian L, Dai Y (2007). Measured CO2 concentration and flux at 16 m height during corn growing period on the North China Plain. Chin J Atmos Sci, 31(4): 695–707
Hu Z, Liu L, Chu R, Jin R (2008). Comparison of different attenuation correction methods and their effects on estimated rainfall using X-band dual linear polarimetric radar. Acta Meteorol Sin, 66(2): 251–261
Huang Q, Wei M, Hu H, Abro M I (2018). Analysis of atmospheric wind, temperature and humidity structure and dual-polarization radar parameters of clear air echo. Meteorological monthly, 44(4): 526–537
Kaimal J C, Finnigan J J (1994). Atmospheric Boundary Layer Flows: Their Structure and Measurement. New York: Oxford University Press
Kanda M, Inagaki A, Letzel M O, Raasch S, Watanabe T (2004). LES study of the energy imbalance problem with eddy covariance fluxes. Boundary-Layer Meteorol, 110(3): 381–404
Knight C A, Miller L J (1993). First radar echoes from cumulus clouds. Bull Am Meteorol Soc, 74(2): 179–188
Kolmogorov A N (1962). A refinement of previous hypotheses concerning the local structure of turbulence in a viscous incompressible fluid at high reynolds number. J Fluid Mech, 13(1): 82–85
Kolmogorov A N (1941a). Energy dissipation in locally isotropic turbulence. Proceedings of the Royal Society a Mathematical Physical & Engineering Sciences, 434(1890): 16–18
Kolmogorov A N (1941b). The local structure of turbulence in incompressible viscous fluid for very large reynolds numbers. Sov Phys Usp, 30(4): 301–305
Liao S, Jiang D (2003). Method to extract turbulent characteristic parameters based on wavelet analysis. Journal of Combustion Science and Technology, 9(1): 21–28
Ma Z (1986). Information and Principle of Weather Radar Echo. Beijing: Science Press (in Chinese)
Melnikov V M, Doviak R J, Zrnic D S, Stensrud D J (2013). Structures of bragg scatter observed with the polarimetric WSR-88D. J Atmos Ocean Technol, 30(7): 1253–1258
Monin A S, Obukhov A M (1954). Basic laws of turbulent mixing in the surface layer of the atmosphere. Trudy Geofizicheskogo Instituta. Akademiya Nauk SSSR, 24(151): 163–187
Richardson L M, Cunningham J G, Zittel W D, Lee R R, Ice R L, Melnikov V M, Hoban N P, Gebauer J (2017). Bragg scatter detection by the WSR-88D. Part I: algorithm development. J Atmos Ocean Technol, 34(3): 465–478
Sheng P, Mao J, Li J, Zhang A, Sang J, Pan N (2003). Atmospheric Physics. Beijing: Peking University Press (in Chinese)
Tang Y (2014). The scattering mechanism and analysis of clear-air echo. Dissertation for Master’s Degree. Nanjing: Nanjing University of Information Science & Technology (in Chinese)
Tatarski V I (1971). The effects of the turbulent atmosphere on wave propagation. National Technical Information, TT-68-50464
Tatarski V I, Silverman R A, Chako N (1961). Wave propagation in a turbulent medium. Phys Today, 14(12): 46–51
Taylor G I (1938). The Spectrum of turbulence. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 919: 476–490
Vickers D, Mahrt L (1997). Quality control and flux sampling problems for tower and aircraft data. J Atmos Ocean Technol, 14(3): 512–526
Wang J, Wang W, Ao Y, Sun F, Shu G (2007). Turbulence flux measurements under complicated conditions. Advances in Earth Science, 22(8): 791–797 (in Chinese)
Wang J, Wang W, Liu S, Ma M, Li X (2009). The problems of surface energy balance closure—an overview and case study. Advances in Earth Science, 24(7): 705–713 (in Chinese)
Wang Y, Chandrasekar V (2009). Algorithm for estimation of the specific differential phase. J Atmos Ocean Technol, 26(12): 2565–2578
Wilczak J M, Oncley S P, Stage S A (2001). Sonic anemometer tilt correction algorithms. Boundary-Layer Meteorol, 99(1): 127–150
Wilson J W, Weckwerth T M, Vivekanandan J, Wakimoto R M, Russell R W (1994). Boundary layer clear-air radar echoes: origin of echoes and accuracy of derived winds. J Atmos Ocean Technol, 11(5): 1184–1206
Wu B, Zhang H, Wang Z, Zhu H, Xie Y (2011). Study on turbulent structures and energy transfer during an advective fog period. Acta Scientiarum Naturalium Universitatis Pekinensis, 47(2): 295–301
Wyngaard J C (1990). Scalar fluxes in the planetary boundary layer—theory, modeling and measurement. Boundary-Layer Meteorol, 50(1–4): 49–75
Xu Z, Liu S, Gong L, Wang J, Li X (2008). A study on the data processing and quality assessment of the eddy covariance system. Advances in Earth Science, 23(4): 357–370
Yao X (2016). Data quality control and echo characteristics analysis of NUIST-C Band dual linear polarimetric doppler radar. Dissertation for Master’s Degree. Nanjing: Nanjing University of Information Science & Technology (in Chinese)
Acknowledgements
Prof. Lv Jingjing, in School of Atmospheric Physics, Nanjing University of Information Science & Technology, assisted in field observation and data acquisition. This work was supported by the National Natural Science Foundation of China (Grant No. 41675029), the Natural Science Foundation of Shandong Province (Nos. ZR2020MD052 and ZR2020MD053), and the Shanghai Aerospace Science and Technology Innovation Fund Project (No. SAST2019-097).
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Zhu, J., Wei, M., Gao, S. et al. The scattering mechanism of squall lines with C-Band dual polarization radar. Part II: the mechanism of an abnormal ZDR echo in clear air based on the parameterization of turbulence deformation. Front. Earth Sci. 16, 236–247 (2022). https://doi.org/10.1007/s11707-021-0870-4
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DOI: https://doi.org/10.1007/s11707-021-0870-4