대기 (Atmosphere)

  • 제26권3호
  • /
  • Pages.461-471
  • /
  • 2016
  • /
  • 1598-3560(pISSN)
  • /
  • 2288-3266(eISSN)
한국기상학회 (Korean Meteorological Society)
권호 표지
DOI QR코드

DOI QR Code

WISE 펄스 도플러 윈드라이다 품질관리 알고리즘 개발

Development of a Quality Check Algorithm for the WISE Pulsed Doppler Wind Lidar

  • 박문수 (한국외국어대학교 차세대도시농림융합기상사업단) ;
  • 최민혁 (한국외국어대학교 차세대도시농림융합기상사업단)
  • Park, Moon-Soo (Weather Information Service Engine, Hankuk University of Foreign Studies) ;
  • Choi, Min-Hyeok (Weather Information Service Engine, Hankuk University of Foreign Studies)
  • 투고 : 2016.07.18
  • 심사 : 2016.08.27
  • 발행 : 2016.09.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

A quality check algorithm for the Weather Information Service Engine pulsed Doppler wind lidar is developed from a view point of spatial and temporal consistencies of observed wind speed. Threshold values for quality check are determined by statistical analysis on the standard deviation of 3-component of wind speed obtained by a wind lidar, and the vertical gradient of horizontal wind speed obtained by a radiosonde system. The algorithm includes carrier-to-noise ratio (CNR) check, data availability check, and vertical gradient of horizontal wind speed check. That is, data sets whose CNR is less than -29 dB, data availability is less than 90%, or vertical gradient of horizontal wind speed is less than $-0.028s^{-1}$ or larger than $0.032s^{-1}$ are classified as 'doubtful', and flagged. The developed quality check algorithm is applied to data obtained at Bucheon station for the period from 1 to 30 September 2015. It is found that the number of 'doubtful' data shows maxima around 2000 m high, but the ratio of 'doubtful' to height-total data increases with increasing height due to atmospheric boundary height, cloud, or rainfall, etc. It is also found that the quality check by data availability is more effective than those by carrier to noise ratio or vertical gradient of horizontal wind speed to remove an erroneous noise data.

키워드

참고문헌

  1. Arya, S. P., 1999: Air pollution meteorology and dispersion. Oxford University Press, 310 pp.
  2. Chae, J.-H., M.-S. Park, and Y.-J. Choi, 2014: The WISE quality control system for integrated meteorological sensor data. Atmosphere, 24, 445-456 (in Korean with English abstract). https://doi.org/10.14191/Atmos.2014.24.3.445
  3. Choi, Y., S.-L. Kang, J. Hong, S. Grimmond, and K. J. Davis, 2013: A next-generation weather information service engine (WISE) customized for urban and surrounding rural areas. Bull. Amer. Meteor. Soc., 94, ES114-117.
  4. Frehlich, R. G., S. M. Hannon, and S. W. Henderson, 1994: Performance of a $2-{\mu}m$ coherent Doppler lidar for wind measurements. J. Atmos. Oceanic Technol., 11, 1517-1528. https://doi.org/10.1175/1520-0426(1994)011<1517:POACDL>2.0.CO;2
  5. Grund, C. J., B. M. Banta, J. L. George, J. N. Howell, M. J. Post, R. A. Richter, and A. M. Weickmann, 2001: High-resolution Doppler lidar for boundary layer and cloud research. J. Atmos. Oceanic Technol., 18, 376-393. https://doi.org/10.1175/1520-0426(2001)018<0376:HRDLFB>2.0.CO;2
  6. Hong, J. S., 2015: A study on the characteristics of heavy rainfall on the west coastal using a wind profilerfocused on Gunsan case analysis. Master Thesis, Chosun University, 49 pp.
  7. Huffaker, R. M., and R. M. Hardestry, 1996: Remote sensing of atmospheric wind velocities using solid state and $CO_2$ coherent laser systems. Proc. IEEE, 84, 181-204.
  8. Jeong, J.-H., S. Lo, S.-K. Song, and Y.-K. Kim, 2010: The application of wind profiler data and its effects on wind distributions in two different coastal areas. J. Environ. Sci., 19, 689-701.
  9. Kwon, T. H., M.-S. Park, C. Yi, and Y. J. Choi, 2014: Effects of different averaging operators on the urban turbulent fluxes. Atmosphere, 24, 197-206 (in Korean with English abstract). https://doi.org/10.14191/Atmos.2014.24.2.197
  10. Lang, S., and E. McKeogh, 2011: LIDAR and SODAR measurements of wind speed and direction in upland terrain for wind energy purpose. Remote Sens., 3, 1871-1901. https://doi.org/10.3390/rs3091871
  11. Leosphere, 2012: Windcube 200TM user manual (version 2), 47 pp.
  12. Lim, Y.-K., S.-K. Song, and S.-O. Han, 2014: Data assimilation effect of mobile rawinsonde observation using unified model observing system experiment during the summer intensive observation period in 2013. J. Korean Earth Sci. Soc., 35, 215-224. https://doi.org/10.5467/JKESS.2014.35.4.215
  13. Panofsky, H. A., and J. A. Dutton, 1984: Atmospheric Turbulence - Models and Methods for engineering applications. John Wiley & Sons, 397 pp.
  14. Pappalardo, G., and Coauthors, 2004: Aerosol lidar intercomparison in the framework of the EARLINET project 3. Raman lidar algorithm for aerosol extinction, backscatter, and lidar ratio. Appl. Opt., 43, 5370-5385. https://doi.org/10.1364/AO.43.005370
  15. Park, M.-S., S.-H. Park, J.-H. Chae, M.-H. Choi, Y. Song, and M. Kang, 2016: High-resolution urban meteorological observation network for user-specific meteorological information service in Seoul Metropolitan Area, Korea. Atmos. Meas. Tech. Discuss, doi:10.5194/amt-2016-278.
  16. Paschke, E., R. Leinweber, and V. Lehmann, 2015: An assessment of the performance of a 1.5 mm Doppler lidar for operational vertical wind profiling based on a 1-year trial. Atmos. Meas. Tech., 8, 2251-2266. https://doi.org/10.5194/amt-8-2251-2015
  17. Pielke, R. A., 2002: Mesoscale Meteorological Modeling. Academic Press, 676 pp.
  18. Simmons, A. J., and A. Hollingsworth, 2002: Some respects of the improvement in skill of numerical weather prediction. Quart. J. Roy. Meteor. Soc., 128, 647-677. https://doi.org/10.1256/003590002321042135
  19. Son, D. S., 2005: The wind shear experiments with the wind profiler. Master Thesis, Kookmin University, 34 pp.
  20. Soreide, D. C., R. K. Bogue, J. Seidel, and L. J. Ehernberger, 1997: The use of a lidar forward-looking turbulence sensor for mixed-compression inlet ustart avoidance and gross weight reduction on a high speed civil transport. NASA Technical Memorandum, 104332.
  21. Strangeways, I., 2003: Measuring the Natural Environment. Cambridge University Press, 534 pp.
  22. Stull, R. B., 1988: An Introduction to the Boundary Layer Meteorology. Kluwer Academic Publishers, 666 pp.

피인용 문헌

  1. High-resolution urban observation network for user-specific meteorological information service in the Seoul Metropolitan Area, South Korea vol.10, pp.4, 2017, https://doi.org/10.5194/amt-10-1575-2017
  2. Features of sea–land-breeze circulation over the Seoul Metropolitan Area vol.5, pp.1, 2018, https://doi.org/10.1186/s40562-018-0127-6