한국해안·해양공학회논문집 (Journal of Korean Society of Coastal and Ocean Engineers)

  • 제32권2호
  • /
  • Pages.135-145
  • /
  • 2020
  • /
  • 1976-8192(pISSN)
  • /
  • 2288-2227(eISSN)
한국해안·해양공학회 (Korean Society of Coastal and Ocean Engineers)
권호 표지
DOI QR코드

DOI QR Code

독도 MIROS Wave Radar를 이용한 파랑관측 및 품질관리

Measurement and Quality Control of MIROS Wave Radar Data at Dokdo

  • 전현정 (한국해양대학교 해양과학기술융합학과) ;
  • 민용침 (한국해양과학기술원 해양재난.재해연구센터) ;
  • 정진용 (한국해양과학기술원 해양재난.재해연구센터) ;
  • 도기덕 (한국해양대학교 해양과학기술융합학과)
  • Jun, Hyunjung (Department of Convergence Study on the Ocean Science and Technology, Korea Maritime and Ocean University) ;
  • Min, Yongchim (Marine Disaster Research Center, Korea Institute of Ocean Science and Technology) ;
  • Jeong, Jin-Yong (Marine Disaster Research Center, Korea Institute of Ocean Science and Technology) ;
  • Do, Kideok (Department of Convergence Study on the Ocean Science and Technology, Korea Maritime and Ocean University)
  • 투고 : 2020.03.23
  • 심사 : 2020.04.24
  • 발행 : 2020.04.29
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

해양에서의 파랑관측은 부이나 압력계 등을 이용하여 수면변위를 관측하는 직접관측방법과 Radar를 이용하여 관측하는 원격관측방법으로 구분된다. 직접관측방법은 정확도가 높지만, 악기상 시 파손 및 유실 위험이 크며 외해 설치 시 많은 유지 보수비용이 필요하다는 단점을 가지고 있다. 반면 Radar와 같은 원격관측방법은 장비를 육지에 계류하여 유지관리가 용이하지만 직접관측방법과 비교하면 정확도가 다소 낮은 단점이 있다. 본 연구에서는 원격파랑관측자료의 품질을 개선하기 위해 독도에 설치되어 운영 중인 MIROS Wave and Current Radar(MWR) 관측자료의 수집 및 분석을 하였으며, 이를 기상청에서 운영 중인 해양파고부이(CWB)의 관측자료와 비교하였다. 그리고 MWR 관측자료의 품질을 개선하기 위해 1) MIROS사에서 개발한 필터(Reduce Noise Frequency, Phillips Check, Energy Level Check)의 복합적인 사용(최적필터; Optimal Filter), 2) OOI(Ocean Observatories Initiative)에서 개발한 Spike Test 알고리즘(Spike Test) 그리고 3) 유의파고-주기 관계식을 이용한 새로운 필터(H-Ts QC)를 사용하여 신뢰도가 낮은 이상자료(Noise; 시계열 자료 중 급격하게 자료가 발산하여 정상자료가 아닌 것으로 판단되는 자료)의 제거 및 보정을 수행하였다. 결과적으로 3가지의 품질관리기법을 적용한 MWR의 파랑관측자료는 유의파고에 대해서는 일정 부분 신뢰도를 가지지만 유의파주기에서는 여전히 오차가 존재하며 이에 대한 개선이 요구된다. 또한, MWR의 파랑관측자료는 3 m 이상의 고파랑에서는 CWB와 다소 양상이 달라지는 한계가 발생하므로 이를 위한 장기간의 원격파랑관측 자료의 수집과 분석, 그리고 필터 개발 등에 관한 지속적인 연구가 필요하다.

Wave observation is widely used to direct observation method for observing the water surface elevation using wave buoy or pressure gauge and remote-sensing wave observation method. The wave buoy and pressure gauge can produce high-quality wave data but have disadvantages of the high risk of damage and loss of the instrument, and high maintenance cost in the offshore area. On the other hand, remote observation method such as radar is easy to maintain by installing the equipment on the land, but the accuracy is somewhat lower than the direct observation method. This study investigates the data quality of MIROS Wave and Current Radar (MWR) installed at Dokdo and improve the data quality of remote wave observation data using the wave buoy (CWB) observation data operated by the Korea Meteorological Administration. We applied and developed the three types of wave data quality control; 1) the combined use (Optimal Filter) of the filter designed by MIROS (Reduce Noise Frequency, Phillips Check, Energy Level Check), 2) Spike Test Algorithm (Spike Test) developed by OOI (Ocean Observatories Initiative) and 3) a new filter (H-Ts QC) using the significant wave height-period relationship. As a result, the wave observation data of MWR using three quality control have some reliability about the significant wave height. On the other hand, there are still some errors in the significant wave period, so improvements are required. Also, since the wave observation data of MWR is different somewhat from the CWB data in high waves of over 3 m, further research such as collection and analysis of long-term remote wave observation data and filter development is necessary.

키워드

참고문헌

  1. Ahn, K., Chun, J. and Cheon, S.H. (2014). New calibration method applicable to significant wave heights obtained by X-band radar. Proceedings of 34th International Conference on Coastal Engineering, ASCE.
  2. Hauser, D., Kahma, K., Krogstad, H.E., Lehner, S., Monbaliu, J.A.J. and Wyatt, L.R., Eds. (2005). Measuring and analysing the directional spectrum of ocean waves. COST Office, Brussels.
  3. Bushnell, M., Bouchard, R. and Worthington, H. (2015). Manual for Real-Time Quality Control of In-Situ Surface Wave Data. Integrated Ocean Observing System., United States.
  4. Ocean Observatories Initiative (2012). Data Product Specification for Spike Test., Ocean Leadership., United States.
  5. Goda, Y. (2003). Revisiting Wilson's formulas for simplified windwave prediction. Journal of Waterway, Port, Coastal, and Ocean Engineering, 129(2), 93-95. https://doi.org/10.1061/(ASCE)0733-950X(2003)129:2(93)
  6. Goda, Y. (2010). Random seas and design of maritime structures. World scientific., Singapore.
  7. Gomez, R., Helzel, T., Petersen, L., Kniephoff, M., Merz, C.R., Liu, Y. and Weisberg, R.H. (2014). Real-time quality control of current velocity data on individual grid cells in WERA HF radar. Oceans 2014-Taipei, IEEE, 1-7.
  8. Gurgel, K.W., Schlick, T., Voulgaris, G., Seemann, J. and Ziemer, F. (2011). HF radar observations in the German Bight: Measurements and quality control. IEEE, 51-56.
  9. Hisaki, Y. (2009). Quality control of surface wave data estimated from low signal-to-noise ratio HF radar doppler spectra. Journal of Atmospheric and Oceanic Technology, 26(11), 2444-2461. https://doi.org/10.1175/2009JTECHO653.1
  10. Kim, Y.B. (2019). Physical Marine Environment near Dokdo and Satisfaction Improvement of Dokdo Tourism by enhancing the Awareness of Marine Territory. The Journal of Korean Island, 31(3), 55-75 (in Korean). https://doi.org/10.26840/JKI.31.3.55
  11. Min, Y.C., Jeong, J.Y., Min, I.K., Kim, Y.S., Shim, J.S. and Do, K.D. (2018). Enhancement of wave radar observation data quality at the socheongcho ocean research station. Journal of Coastal Research, SI, 85, 571-575. https://doi.org/10.2112/SI85-115.1
  12. Min, Y.C., Jeong, J.Y., Shim, J.S. and Do, K.D. (2017). Quality enhancement of wave data observed by radar at the socheongcho ocean research station. Korea Society of Coastal Disaster Prevention, 4(4), 189-196 (in Korean). https://doi.org/10.20481/kscdp.2017.4.4.189
  13. MIROS (2011). Wave and Current Radar System System Handbook. MIROS, Norway.
  14. Shore Protection Manual (1977). Coastal Engineering Research Center, U.S. Government Printing Office, Washington, D.C.
  15. Suh, K.D., Kwon, H.D. and Lee, D.Y. (2008). Statistical characteristics of deepwater waves along the Korean Coast. Korean Society of Coastal and Ocean Engineers, 20(4), 342-354 (in Korean).
  16. KMA (2019a). Monthly meteorological report. Korea Meteorological Administration (in Korean).
  17. KMA (2019b). Annual report on the quality analysis of national climate data for 2018. Korea Meteorological Administration (in Korean).
  18. Park, C.K. (2005). Ocean Resources and Strategic value around Dokdo area. Military Forum, Korea Association of Military Studies, 44, 6-27 (in Korean).