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이중편파레이더 관측오차 보정에 따른 강수량 추정값 개선

Improvement of Rainfall Estimation according to the Calibration Bias of Dual-polarimetric Radar Variables

  • 김해림 (기상청 기상레이더센터 레이더분석과) ;
  • 박혜숙 (기상청 기상레이더센터 레이더분석과) ;
  • 고정석 (기상청 기상레이더센터 레이더분석과)
  • 투고 : 2014.09.03
  • 심사 : 2014.11.17
  • 발행 : 2014.12.31

초록

이중편파레이더는 강수의 형태를 구분하고 대기 중의 기상 현상뿐만 아니라 비강수에코에 대한 정보를 제공하기 때문에 보다 정확한 강수량 추정을 가능하게 한다. 그러나 수직, 수평으로 진동하는 전파를 송 수신하여 생성되는 이중편파레이더 관측변수들은 레이더 자체가 갖는 시스템적 관측오차를 포함하기 때문에 정량적 강수량 추정을 위해서는 이에 대한 보정이 필수적이다. 본 연구에서는 2차원 영상우적계(2-Dimensional Video Disdrometer, 이하 2DVD) 관측 자료를 이용하여 비슬산 이중편파레이더가 갖는 Z, $Z_{DR}$ 관측오차를 계산한 후, 관측오차 보정에 따라 강수량이 정량적으로 얼마나 개선되는지를 살펴보았다. 총 33강수사례에 대한 분석결과, Z는 약-0.3~5.5 dB, $Z_{DR}$는 -0.1~0.6 dB의 관측오차를 가지며, 대부분의 사례에서 Z와 $Z_{DR}$는 모의된 값보다 낮게 관측하였다. 관측오차를 보정한 전 후 산출된 이중편파레이더 강수량 추정값을 지상관측 강우강도와 비교한 결과, 평균 bias와 RMSE는 각각 1.54 mm/hr, 1.73 mm/hr로 보정 전의 1.69 mm/hr, 2.54 mm/hr 보다 감소함으로써 지상우량계 관측값 대비 레이더 강수량 추정값이 약 7~61% 향상되었다.

Dual-polarization can distinguish precipitation type and dual-polarization is provide not only meteorological phenomena in the atmosphere but also non-precipitation echoes. Therefore dual-polarization radar can improve radar estimates of rainfall. However polarimetric measurements by transmitting vertically vibration waves and horizontally vibrating waves simultaneously is contain systematic bias of the radar itself. Thus the calibration bias is necessary to improve quantitative precipitation estimation. In this study, the calibration bias of reflectivity (Z) and differential reflectivity ($Z_{DR}$) from the Bislsan dual-polarization radar is calculated using the 2-Dimensional Video Disdrometer (2DVD) data. And an improvement in rainfall estimation is investigated by applying derived calibration bias. A total of 33 rainfall cases occurring in Daegu from 2011 to 2012 were selected. As a results, the calibration bias of Z is about -0.3 to 5.5 dB, and $Z_{DR}$ is about -0.1 dB to 0.6 dB. In most cases, the Bislsan radar generally observes Z and $Z_{DR}$ variables lower than the simulated variables. Before and after calibration bias, compared estimated rainfall from the dual-polarization radar with AWS rain gauge in Daegu found that the mean bias has fallen by 1.69 to 1.54 mm/hr, and the RMSE has decreased by 2.54 to 1.73 mm/hr. And estimated rainfall comparing to the surface rain gauge as ground truth, rainfall estimation is improved about 7-61%.

키워드

참고문헌

  1. Atlas, D. (2002). "Radar calibrations: Some simple approaches." Bull. Amer. Meteor. Soc., Vol. 83, pp. 1313-1316. https://doi.org/10.1175/1520-0477(2002)083<1313:RCSSA>2.3.CO;2
  2. Atlas, D., and Ulbrich, C.W. (1977). "Path and area integrated rainfall measurement by microwave attenuation in the 1-3 cm band." J. Appl. Meteor., Vol. 16, pp. 327-332. https://doi.org/10.1175/1520-0450(1977)016<0327:SNAIHS>2.0.CO;2
  3. Atlas, D., Srivastava, R.C., and Sekkon, R.S. (1973). "Doppler radar characteristics of precipitation at vertical incidence." Rev. Geophys. Space Phys., Vol. 2, pp. 1-35.
  4. Brandes, E.A., Zhang, G., and Vivekanandan, J. (2002). "Experiments in rainfall estimation with a polarimetric radar in a subtropical environment." J. Appl. meteor., Vol. 41, pp. 674-685. https://doi.org/10.1175/1520-0450(2002)041<0674:EIREWA>2.0.CO;2
  5. Bringi, V.N., and Chandrasekar, V. (2001). "Polarimetric Doppler Weather Radar: Principles and Applications." Cambridge University Press, p. 636.
  6. Gwon, S.H., Lee, G.W., and Lee, C.G. (2010). "Calibration of differential reflectivity from the Bislsan S-Band dual-polarization radar." Proceedings of the spring meeting of KMS, pp 458-459.
  7. Hagen, M., and Yuter, S. (2003). "Relations between radar reflectivity, liquid water content, and rainfall rate during the MAPSOP." Q. J. Roy. Meteor. Soc., Vol. 129, pp. 477-493. https://doi.org/10.1256/qj.02.23
  8. Huang, G.J., Bringi, V.N., and Thurai, M. (2008). "Orientation angle disdributions of drops after 80-m fall using a 2D video disdrometer." J. Atmos. Oceanic Technol., Vol. 25, pp. 1717-1723. https://doi.org/10.1175/2008JTECHA1075.1
  9. Joss, J., Thams, J.C., and Waldvogel, A. (1968). "The accuracy of daily rainfall measurements by radar." Preprints, 13th Conf. on Radar Meteorology, Montreal, QC, Canada, Amer. Meteor. Soc., pp. 448-451.
  10. Jung. Y., Xue, M., and Zhang, G. (2010). "Simulations of polarimetric radar signatures of a supercell storm using a two-moment bulk microphysics scheme." J. Appl. Meteor. Climatol., Vol. 49, pp. 146-163. https://doi.org/10.1175/2009JAMC2178.1
  11. Kim, H.-L., Park, H.-S., Park, H.-S., and Park, J.-S. (2014). "Study on the Application of 2D Video Disdrometer to Develope the Polarimetric Radar Data Simulator." Atmos., KMS. Vol. 24, pp. 173-188. https://doi.org/10.14191/Atmos.2014.24.2.173
  12. Kruger, A., and Krajewski, W.F. (2002). "Two-dimensional video disdrometer." J. Atmos. Sci., Vol. 19, pp. 602-617.
  13. Lee, G.W., Gwon, S.-H., Lee, C.-G., and Nam, G.-Y. (2012). "Application of dual-polarization radar." Magazine of Korea Water Resources, Vol. 45, pp. 28-39.
  14. McFarquhar, G.M., and List, R. (1993). "The effect of curve fits for the disdrometer calibration on raindrop spectra, rainfall rate, and radar reflectivity." J. Appl. Meteor., Vol. 32, pp. 774-782. https://doi.org/10.1175/1520-0450(1993)032<0774:TEOCFF>2.0.CO;2
  15. Park, S.-G., and Lee, G.W. (2010). "Calibration of Radar Reflectivity measurements from the KMA Operational Radar Network." Asian-Pacific J. Atmos, Sci., Vol. 46, No. 3, pp. 243-259. https://doi.org/10.1007/s13143-010-1010-3
  16. Pruppacher, H., and Beard, K.V. (1970). "A wind tunnel investigation of the internal circulation and shape of water drops falling at terminal velocity in air." Q. J. Roy. Meteor. Soc., Vol. 96, pp. 247-256. https://doi.org/10.1002/qj.49709640807
  17. Ryzhkov, A.V., Giangrande, S.E., and Schuur, T.J. (2005). "Rainfall Estimation with a Polarimetric Prototype of WSR-88D." J. Appl. Meteor., Vol. 34, pp. 2121-2134.
  18. Sheppard, B.E., and Joe, P.I. (1994). "Comparison of raindrop size distribution measurements by a Joss-Waldvogel disdrometer, a PMS 2DG spectrometer, and a POSS Doppler radar." J. Atmos. Oceanic Technol., Vol. 11, pp. 874-887. https://doi.org/10.1175/1520-0426(1994)011<0874:CORSDM>2.0.CO;2
  19. Thurai, M., and Bringi, V.N. (2005). "Drop Axis Ratios from a 2D Video Disdrometer." J. Atmos. Oceanic Technol., Vol. 22, pp. 966-978. https://doi.org/10.1175/JTECH1767.1
  20. Tokay, A., Wolff, D.B., Wolff, K.R., and Bashor, P. (2003). "Rain gauge and disdrometer measurements during the keys Area Microphysics Project (KAMP)." J. Atmos. Oceanic Technol., Vol. 20, pp. 1460-1477. https://doi.org/10.1175/1520-0426(2003)020<1460:RGADMD>2.0.CO;2
  21. Ulbrich, C.W., and Lee, L.G. (1999). "Rainfall measurement error by WSR-88D radars due to variations in Z-R law parameters and the radar constant." J. Atmos. Oceanic Technol., Vol. 16, pp. 1017-1024. https://doi.org/10.1175/1520-0426(1999)016<1017:RMEBWR>2.0.CO;2
  22. Zhang, G., Vivekananda, J., and Brandes, E. (2001). "A method for estimating rain rate and drop size distribution from polarimetric radar measurements." IEEE Trans. Geosci. Remote Sens., Vol. 39, pp. 830-841. https://doi.org/10.1109/36.917906