Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-25T09:13:40.388Z Has data issue: false hasContentIssue false

Drop deformation estimate with multi-polarization radar

Published online by Cambridge University Press:  10 June 2020

Yuliya Averyanova*
Affiliation:
National Aviation University, Prospect Lubomyra Guzara, 1, Kyiv03058, Ukraine
Anna Rudiakova
Affiliation:
National Aviation University, Prospect Lubomyra Guzara, 1, Kyiv03058, Ukraine
Felix Yanovsky
Affiliation:
National Aviation University, Prospect Lubomyra Guzara, 1, Kyiv03058, Ukraine
*
Author for correspondence: Yuliya Averyanova, E-mail: [email protected]

Abstract

This paper considers the ability of polarization measurements for microwave remote sensing of clouds and precipitation. The simulation of reflections from liquid hydrometeors with a multi-polarization radar system is presented. The mathematical expression of energy received by a radar antenna with arbitrary polarization is obtained. The simulation of the energy redistribution of the signal reflected from liquid hydrometeors assembled over the antennas of multi-polarimetric radar for different wind conditions and different drop-size distributions is obtained and analyzed. The simulation results demonstrate the possibility to register wind and wind-related phenomena by polarimetric radar. The results of the paper can also be used to exclude an impact of drop vibration or oscillation into the radar signal to eliminate errors and underestimation during parameter measurements. The approach to segregate the reflected signal magnitude variations due to the wind-related phenomena from other factors is discussed.

Type
Research Paper
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Lhermitte, RM (1973) Meteorological Doppler radar. Science. 1982: N 4109, pp. 258262.CrossRefGoogle Scholar
Doviak, RJ and Zrnic, DS (1993) Doppler Radar and Weather Observations. San Diego: Academic Press, Inc.Google Scholar
Ryzhkov, AV and Zrnic, DS (2019) Radar Polarimetry for Weather Observations. Cham: Springer.CrossRefGoogle Scholar
Rayleigh, JWS (1879) On the capillary phenomena of jets. Proceedings of the Royal Society of London 19, 7197.Google Scholar
Pruppacher, HR and Beard, KV (1970) A wind tunnel investigation of the internal circulation and shape of water drops falling at terminal velocity in air. Quarterly Journal of the Royal Meteorological Society 96, 247256.CrossRefGoogle Scholar
Pruppacher, HR and Pitter, RL (1971) A semi-empirical determination of the shape of cloud and rain drops. Journal of Atmospheric Sciences 28, 8694.2.0.CO;2>CrossRefGoogle Scholar
Beard, KH and Chuang, C (1987) A new model for equilibrium shape of rain drops. Journal of Atmospheric Sciences 28, 15091524.2.0.CO;2>CrossRefGoogle Scholar
Tokay, A and Beard, KV (1996) A field study of raindrop oscillations. Part I: observation of size spectra and evaluation of oscillation causes. Journal of Applied Meteorology 35, 16711687.2.0.CO;2>CrossRefGoogle Scholar
Szakall, M, Diehl, K and Mitra, SK (2009) A wind tunnel study on the shape, oscillation and internal circulation of large raindrops with sized between 2.5 and 7.5 mm. Journal of Atmospheric Research 66, 755765.CrossRefGoogle Scholar
Szakall, M, Mitra, SK, Diehl, K and Borrmann, S (2010) Shapes and oscillations of falling raindrops. Journal of Atmospheric Research 97, 416425.CrossRefGoogle Scholar
Kubesh, RJ and Beard, KV (1993) Laboratory measurements of spontaneous oscillations for moderate-size raindrops. Journal of Atmospheric Sciences 50, 10891098.2.0.CO;2>CrossRefGoogle Scholar
Goddard, JWF and Cherry, SM and Bringi, VN (1982) Comparison of Dual-Polarization Radar Measurements of Rain with Ground-Based Disdrometer Measurement. Journal of Applied Meteorology 21, 252256.2.0.CO;2>CrossRefGoogle Scholar
Averyanova, Y, Yanovsky, F and Averyanov, A (2011) Connection of reflected radar signal with liquid-hydrometeor deformation rate. Proceedings of the 3rd Symposium on Microwaves, Radar and Remote Sensing, Kiev, Ukraine, August 25–27, 2011, pp. 217219.CrossRefGoogle Scholar
Averyanova, YA, Rudiakova, AN and Yanovsky, FJ (2017) Multi-polarization approach to operative dangerous atmospheric phenomena detection. Proceedings of the 5th Symposium on Microwaves, Radar and Remote Sensing, Kiev, Ukraine, August 29–31, 2017, pp. 245248.CrossRefGoogle Scholar
Averyanova, YA, Braun, I, Rudiakova, AN and Yanovsky, FJ (2018) Reflected signal variations simulation and estimation when multi polarization measurements. Proceedings of 22nd Microwave and Radar Conference (MIKON 2018), May 15–17, 2018, Poznan, Poland, pp. 14.CrossRefGoogle Scholar
Averyanova, YA, Rudiakova, AN and Yanovsky, FJ (2017) Segregating deformation of scattering rain-drops using several receive antennas with different polarization angles. Proceedings of International Radar Symposium (IRS 2017), June 28–30, 2017, Prague, Czech Republic. pp. 14.CrossRefGoogle Scholar
Averyanova, YA, Rudiakova, AN and Yanovsky, FJ (2017) Multi-polarization approach to liquid hydrometeors’ vibration discrimination in presence of turbulence. Proceedings of Signal Processing Symposium SPS-2017, 12–14 September 2017, Debe near Warsaw, Poland. pp. 14.CrossRefGoogle Scholar
Gorelik, AG (1989) Influence of raindrops vibration on polarization characteristics of radar echo. Physics of Atmosphere and Ocean 25, 960968 (in Russian).Google Scholar
Marshall, JS and Mc K. Palmer, W (1948) The distribution of raindrops with size. Journal of Meteorology 5, 165166.2.0.CO;2>CrossRefGoogle Scholar
Fog, NI (2004) The representation of rainfall distribution and kinetic energy. Hydrology and Earth System Sciences 8, 10011007.Google Scholar
Averyanova, YA, Rudiakova, AN and Yanovsky, FJ (2018) Drop oscillation estimate with multi-polarization radar. Proc. of 17th International Conference on Mathematical Methods in Electromagnetic Theory, Kyiv, Ukraine. pp. 342345.CrossRefGoogle Scholar
Averyanova, YA, Averyanov, A and Yanovsky, FJ (2007) Analysis of the possibility to determine wind parameters ahead the aircraft by using polarimetric airborne radar. Telecommunications and Radioengineering 66, 11031112.CrossRefGoogle Scholar
Averyanova, YA, Averyanov, AA and Yanovsky, FJ (2002) Wind condition model of flight. Proceedings of International Conference on Mathematical Methods in Electromagnetic Theory, Kiev 2002, Ukraine, vol. 1, pp. 275277.CrossRefGoogle Scholar
Russchenberg, HWJ (1992) Ground-based Remote Sensing of Precipitation Using a Multi-Polarized FM-CW Doppler Radar. Delft: Delft University Press.Google Scholar
Averyanova, YA, Rudiakova, AN, Braun, I and Yanovsky, FJ (2018) Simulations of multi polarization measurements and reflected signal magnitude variations caused by turbulence. Proceedings of International Radar Symposium (IRS 2018), June 19–22, 2018, Bonn, Germany, pp. 15.CrossRefGoogle Scholar
Mazin, IP (1989) Microstructure of Clouds. In Mazin, IP and Hrgian, AH (eds), Clouds and Cloudy Atmosphere. Leningrad: Gidrometeoizdat, pp. 297344.Google Scholar