대한원격탐사학회지 (Korean Journal of Remote Sensing)

  • 제32권2호
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  • Pages.155-169
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  • 2016
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  • 1225-6161(pISSN)
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  • 2287-9307(eISSN)
대한원격탐사학회 (Korean Society of Remote Sensing)
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레이더-위성자료 이용 다중센서 기반 초단기 강우예측 - 2014년 8월 부산·경남 폭우사례를 중심으로 -

A Multi-sensor basedVery Short-term Rainfall Forecasting using Radar and Satellite Data - A Case Study of the Busan and Gyeongnam Extreme Rainfall in August, 2014-

  • 장상민 (APEC기후센터, 연구본부, 기후연구변화팀) ;
  • 박경원 (APEC기후센터, 연구본부, 기후연구변화팀) ;
  • 윤선권 (APEC기후센터, 연구본부, 기후연구변화팀)
  • 투고 : 2016.03.22
  • 심사 : 2016.04.15
  • 발행 : 2016.04.30
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초록

본 연구에서는 2014년 8월 부산 경남 집중호우 사례를 대상으로 레이더와 위성결합 Multi-sensor Blending 초단기 강우예측을 실시하였다. 레이더 최적 Z-R관계는 열대형 강수 Z-R관계식($Z=32R^{1.65}$)을 적용하였으며, 20 mm/h 이상의 강한 강우에서 강수량 추정 정확도가 향상됨을 확인하였다. 또한 60 mm/h 이상 강한 폭우사상에 대하여 천리안 위성자료와 레이더자료를 합성한 결과 정량강수 추정 성능이 향상됨을 확인하였다. 지속시간별 강우예측 정확도 검증을 위하여 AWS, MAPLE 자료와 비교결과, 강우예측 1시간까지 약 50%이상의 지점강우예측 정확도를 확보하였으며, 10분 단위 예측시간별 상관계수는 0.80~0.53, 평균제곱근오차는 3.99~6.43 mm/h로 분석되었다. 본 연구 결과 레이더와 위성정보를 이용한 보다 신뢰성 있는 강우예측 정보 활용이 가능할 것으로 판단되며, 향후 지속적인 사례연구와 레이더 위성 활용 정량강수량 추정 및 예측, 그리고 위성강수 추정 알고리즘 개선의 노력이 필요하다.

In this study, we developed a multi-sensor blending short-term rainfall forecasting technique using radar and satellite data during extreme rainfall occurrences in Busan and Gyeongnam region in August 2014. The Tropical Z-R relationship ($Z=32R^{1.65}$) has applied as a optimal radar Z-R relation, which is confirmed that the accuracy is improved during 20mm/h heavy rainfall. In addition, the multi-sensor blending technique has applied using radar and COMS (Communication, Ocean and Meteorological Satellite) data for quantitative precipitation estimation. The very-short-term rainfall forecasting performance was improved in 60 mm/h or more of the strong heavy rainfall events by multi-sensor blending. AWS (Automatic Weather System) and MAPLE data were used for verification of rainfall prediction accuracy. The results have ensured about 50% or more in accuracy of heavy rainfall prediction for 1-hour before rainfall prediction, which are correlations of 10-minute lead time have 0.80 to 0.53, and root mean square errors have 3.99 mm/h to 6.43 mm/h. Through this study, utilizing of multi-sensor blending techniques using radar and satellite data are possible to provide that would be more reliable very-short-term rainfall forecasting data. Further we need ongoing case studies and prediction and estimation of quantitative precipitation by multi-sensor blending is required as well as improving the satellite rainfall estimation algorithm.

키워드

참고문헌

  1. Atlas, D., C. Ulbrich, F.D. Jr. Marks, E. Amitai, and C.R. Williams 1999. Systematic variation of drop size and radar-rainfall relations, Journal of Geophysical Research, 104: 6155-6169. https://doi.org/10.1029/1998JD200098
  2. Blanchard, D.C. 1953. Raindrop size distribution in Hawaiian rains, Journal of Meteorology, 10: 457-473. https://doi.org/10.1175/1520-0469(1953)010<0457:RSDIHR>2.0.CO;2
  3. Calheiros, R.V. and I. Zawadzk 1987. Reflectivity-rain rate relationships for radar hydrology in Brazil, Journal of Climate Applied Meteorology, 26: 118-132. https://doi.org/10.1175/1520-0450(1987)026<0118:RRRRFR>2.0.CO;2
  4. Chandrasekhar, V. and R. Cifelli 2012. Concepts and principles of rainfall estimation from radar: Multi sensor environment and data fusion, Indian Journal of Radio and Space Physics, 41: 389-402.
  5. Fulton, R. A., Breidenbach, J. P., Seo, D. J., Miller, D. A., and O'Bannon, T. (1998). The WSR-88D rainfall algorithm, Weather and Forecasting, 13(2): 377-395. https://doi.org/10.1175/1520-0434(1998)013<0377:TWRA>2.0.CO;2
  6. Germann, U. and I. Zawadzki, 2002. Scale-Dependence of the Predictability of Precipitation from Continental Radar Images. Part I: Description of the Methodology, Monthly Weather Review, 130(12): 2859-2873. https://doi.org/10.1175/1520-0493(2002)130<2859:SDOTPO>2.0.CO;2
  7. Gochis, D., R. Schumacher, K. Friedrich, N. Doesken, M. Kelsch, J. 4 Sun, K. Ikeda, D.T. Lindsey, A. Wood, B. Dolan, S. Matrosov, A. Newman, K. Mahoney, S. Rutledge, R. Johnson, P. Kucera, P. Kennedy, D. Sempere-Torres, M. Steiner, R. Roberts, J. Wilson, W. Yu, V. Chandrasekar, R. Rasmussen, A. Anderson, B. Brown 2015. The great Colorado flood of September 2013, Bulletin of the American Meteorological Society, 96(9): 1461-1487. https://doi.org/10.1175/BAMS-D-13-00241.1
  8. Gourley, J.J. and R.A. Maddox 2002. An exploratory multisensor technique for quantitative estimation of stratiform rainfall, Journal of Hydrolometeorology, 3: 166-180. https://doi.org/10.1175/1525-7541(2002)003<0166:AEMTFQ>2.0.CO;2
  9. Jones, D.M.A. 1956. Rainfall drop size distribution and radar reflectivity, Research Report, No. 6, U.S. Army Contract DA-36-039 SC-64723, Illinois State Water Survey, Urbanba, Vol. 20, pp. 1-20.
  10. Kim J.P., S.K. Yoon, G.S. Kim, and Y.I. Moon 2015. Application of very short-term rainfall forecasting to using water simulation using TREC method, Journal of Korea Water Resources Association, 48(5): 409-423. (Korean with English abstract) https://doi.org/10.3741/JKWRA.2015.48.5.409
  11. Kitzmiller, D., D. Miller, R. Fulton, and R. Ding 2013. Radar and multisensor precipitation estimation techniques in National Weather Service hydrologic operations, Journal of Hydrologic Engineering, 18(2): 133-142. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000523
  12. Marshall, J.S., and W.M.K. Palmer 1948. The distribution of raindrops with size, Journal of Meteorology, 5(4): 165-166. https://doi.org/10.1175/1520-0469(1948)005<0165:TDORWS>2.0.CO;2
  13. Ng, C.W., and H. Y. Yeung 2013. Development of Radar-Satellite Blended QPE Technique and Application to Rainfall Nowcasting, Proc. of 27th Guangdong-Hong Kong-Macao Seminar, Reprint 1058, pp. 1-20.
  14. NMSC (National Meteorological Satellite Center), (2016). http://nmsc.kma.go.kr/, Accessed Jan. 2016.
  15. NIMS (National Institute of Meteorological Sciences)(2003). Application of the Z-R relationshiprespect with the Type of prediction using radar of Jindo, National Institute of MeteorologicalSciences in Gwangju, KMA [C1-7], pp. 1-83.(in Korean)
  16. Park, K.W. 2015. Regional Impacts of Hydrometeorological variability by extreme climate pattern changes and its heavy rainfall short-term forecast system over the Korean Peninsula. APCC Research Report, 2015-15, pp.1-86. (Korean with English abstract)
  17. Rinehart, R.E. and T. Garvey 1978. Three dimensional storm motion detection by conventional weather radar, Nature, 273: 287-289. https://doi.org/10.1038/273287a0
  18. Steiner, M., and R.A. Houze Jr., 1993. Three-dimensional validation at TRMM ground truthsites: some early results from Darwin, Australia, Proc. of 26th International Conference on Radar Meteorology, Norman, OK, May. 24-28,pp. 447-450.
  19. Vasiloff, S.V., D.J. Seo, K.W. Howard, J. Zhang, D.H.Kitzmiller, M.G. Mullusky, W. F. Krajewski,E.A. Brandes, R.M. Rabin, D Berkowitz, H.E. Brooks, J.A. McGinley, R.J. Kuligowski, and B.G. Brown (2007). Improving QPE and very short term QPF. Bulletin of the American Meteorological Society, 88(12): 1899-1911. https://doi.org/10.1175/BAMS-88-12-1899
  20. Wetchayont, P., T. Hayasaka, T. Satomura, S. Katagiri,and S. Baimoung 2013. Retrieval of rainfall by combining rain gauge, ground-based radar and satellite measurements over Phimai, Thailand, Scientific Online Letters on the Atmosphere, 9:166-169.
  21. Yoon, S.K., and Moon, Y.I. 2014. The Recent Increasing Trends of Exceedance Rainfall Thresholds Over the Korean Major Cities, Journal of the Korean Society of Civil Engineers,34(1): 117-133. (Korean with English abstract) https://doi.org/10.12652/Ksce.2014.34.1.0117
  22. Zhang, J. and Y. Qi 2010. A real-time algorithm for the correction of bright band effects in radar-derived precipitation estimation, Journal ofHydrometeorology, 11: 1157-1171. https://doi.org/10.1175/2010JHM1201.1
  23. Zhang, J., K. Howard, and co-authors 2011. National Mosaic and multi-sensor QPE (NMQ) system: description, results and future plans, Bulletin of the American Meteorological Society, 92: 1321-1338. https://doi.org/10.1175/2011BAMS-D-11-00047.1

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