The scattering mechanism of squall lines with C-Band dual polarization radar. Part I: echo characteristics and particles phase recognition

Abstract

Squall line is a kind of common mesoscale disaster weather. At present, there are few studies on the elaborate detection of squall line by dual polarization radar. With the dual polarization upgrade of weather radar network, we need to study the relationship between squall line echoes of base data and polarization data to reveal new echo phenomena and formation mechanisms. The relationship between radar parameters and atmospheric physical processes also need to be examined. Based on the NUIST CDP radar, a squall line in the Yangtze and Huaihe River basin that occurred from July 30 to 31, 2014 is analyzed. The results show that polarization parameters have obvious advantages in the characteristics analysis of size, phase state, shape and orientation of the water condensate particles. The phase states of water condensate particles in convection cell can be distinguished through comparative discussion. Several phase states exist in the squall line, including small, medium and large raindrops, melting hails, dry hails and ice crystal particles and the Z_DR column can be used to identify the location of the main updraft. In addition, the polarization parameters are more sensitive to the melting layer. The gust front is presented as a narrow linear echo in Z affected by strong turbulence. It is an obvious velocity convergence line in V and approximately 0.70 in r_HV. The Z_DR can be used as a criterion to distinguish the horizontal and vertical scale of turbulence. The deforming turbulence, which is affected by environmental airflow, will cause an abnormally high Z_DR in the gust front and a negative Z_DR before and after the gust front. The variation of Z_DR depends on the turbulence arrangement, orientation and relative position between turbulence and radar. These dual polarization parameter characteristics offer insights into understanding the structure and evolution of the squall line.

Keywords

dual polarization Doppler radar / RHI / squall line / gust front / turbulence

References

[1] Bringi V N, Chandrasekar V (2001). Polarimetric Doppler Weather Radar: Principles and Applications. Cambridge: Cambridge University Press

[2] Bukovcic P, Ryzhkov A V, Zrnić D, Zhang G (2018). Polarimetric radar relations for quantification of snow based on disdrometer data. J Appl Meteorol Climatol, 57(1): 103–120

[3] Bluestein H B, French M M, Tanamachi R L, Frasier S, Hardwick K, Junyent F, Pazmany A L (2007). Close-range observations of tornadoes in supercells made with a dual-polarization, X-band, mobile Doppler radar. Mon Weather Rev, 135(4): 1522–1543

[4] Cimini D, Nelson M, Guldner J, Ware R (2015). Forecast indices from a ground-based microwave radiometer for operational meteorology. Atmos Meas Tech, 8(1): 315–333

[5] 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

[6] Gallus W A Jr, Snook N A, Johnson E V (2008). Spring and summer severe weather reports over the midwest as a function of convective mode: a preliminary study. Weather Forecast, 23(1): 101–113

[7] Gaviola E, Fuertes A F (2010). Hail formation, vertical currents, and icing of aircraft. J Atmos Sci, 4(4): 116–120

[8] Geerts B (1998). Mesoscale convective systems in the southeast United States during 1994–95: a survey. Weather Forecast, 13(3): 860–869

[9] Giangrande S E, Krause J M, Ryzhkov A V (2008). Automatic designation of the melting layer with a polarimetric prototype of the WSR-88D Radar. J Appl Meteorol Climatol, 47(5): 1354–1364

[10] He Y, Xiao H, Lv D (2010). Analysis of hydrometeor distribution characteristics in stratiform clouds using polarization Radar. Chin J Atmos Sci, 34(1): 23–34

[11] Houze R A Jr, Biggerstaff M I, Rutledge S A, Smull B F (1989). Interpretation of doppler weather radar display of midlatitude mesoscale convective systems. Bull Am Meteorol Soc, 70(6): 608–619

[12] 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

[13] Huang H, Zhang G, Zhao K, Giangrande S (2017). A hybrid method to estimate specific differential phase and rainfall with linear programming and physics constraints. IEEE Trans Geosci Remote Sens, 55(1): 96–111

[14] 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

[15] Huang Z, Xu G, Wang X, Tang Y (2014). Analysis on two hailstorm events in Xianning based on observations of ground-based microwave radiometer. Meteorological Monthly, 40(2): 216–222

[16] Illingworth A J, Goddard J W F, Cherry S M (1987). Polarization radar studies of precipitation development in convective storms. Q J R Meteorol Soc, 113(476): 469–489

[17] Islam T, Rico-Ramirez M A, Han D, Srivastava P K (2014). Sensitivity associated with bright band/melting layer location on radar reflectivity correction for attenuation at C-band using differential propagation phase measurements. Atmos Res, 135–136(1): 143–158

[18] Kumjian M R, Khain A P, Benmoshe N, Ilotoviz E, Ryzhkov A V, Phillips V T J (2014). The anatomy and physics of Z_DR columns: investigating a polarimetric radar signature with a spectral bin microphysical mode. J Appl Meteorol Climatol, 53(7): 1820–1843

[19] Langston C, Zhang J, Howard K (2007). Four-dimensional dynamic radar mosaic. J Atmos Ocean Technol, 24(5): 776–790

[20] Levi L, Lubart L, Lassig J (1994). Study of a convective storm series and of precipitated hail in south Argentina. Atmos Res, 33(1–4): 75–91

[21] Ma L (2018). Data quality control for weather radar reflectivity ractor and its application in regional radar composite. Dissertation for Master’s Degree. Nanjing: Nanjing University of Information Science & Technology

[22] Meischner P F, Bringi V N, Heimann D, Holler H (1991). A squall line in Southern Germany: kinematics and precipitation formation as deduced by advanced polarimetric and doppler radar measurements. Mon Weather Rev, 119(3): 678–701

[23] Meng Z, Yan D, Zhang Y (2013). General features of squall lines in East China. Mon Weather Rev, 141(5): 1629–1647

[24] Oliveira F P, Oyama M D (2009). Radiosounding-derived convective parameters for the alcantara launch center. J Aerosp Technol Manag, 1(2): 211–216

[25] Pan J, Jiang L, Wei M, Luo C, Gao L, Zheng X, Peng J (2020). Analysis of a high precipitation supercell based on dual polarization radar observations. Acta Meteorol Sin, 78(1): 86–100

[26] Park H S, Ryzhkov A V, Zrnic D S, Kim K (2009). The hydrometeor classification algorithm for the polarimetric WSR-88D: description and application to an MCS. Weather Forecast, 24(3): 730–748

[27] Parker M D, Johnson R H (2000). Organizational modes of midlatitude mesoscale convective systems. Mon Weather Rev, 128(10): 3413–3436

[28] Rasmussen R M, Heymsfield A J (1987). Melting and shedding of graupel and hail. Part I: model physics. J Atmos Sci, 44(19): 2754–2763

[29] Romine G S, Burgess D W, Wilhelmson R B (2008). A dual-polarization-radar-based assessment of the 8 May 2003 Oklahoma City area tornadic supercell. Mon Weather Rev, 136(8): 2849–2870

[30] Straka J M, Zrnic D S, Ryzhkov A V (2000). Bulk hydrometeor classification and quantification using polarimetric radar data: synthesis of relations. J Appl Meteorol, 39(8): 1341–1372

[31] Tatarski V I (1971). The effects of the turbulent atmosphere on wave propagation. National Technical Information, TT-68–50464

[32] Wakimoto R A, Bringi V N (1988). Dual-polarization observations of microbursts associated with intense convection: the 20 July storm during the MIST Project. Mon Weather Rev, 116(8): 1521–1539

[33] Wang Y, Chandrasekar V (2009). Algorithm for estimation of the specific differential phase. J Atmos Ocean Technol, 26(12): 2565–2578

[34] 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

[35] Zhang G, Vivekanandan J, Brandes E (2001). A method for estimating rain rate and drop size distribution from polarimetric radar measurements. Geoscience & Remote Sensing IEEE Transactions on, 39(4): 830–841

[36] Zhang L, Guo R, He N, Liao X (2013). Characteristic analusis of a hail event in Beijing. Meteorol Sci Technol, 41(1): 114–120

Acknowledgments

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).

RIGHTS & PERMISSIONS

2021 Higher Education Press