Journal of the Korean Society for Aviation and Aeronautics (한국항공운항학회지)

The Korean Society for Aviation and Aeronautics (한국항공운항학회)
권호 표지
DOI QR코드

DOI QR Code

Performance Evaluation and Improvement of Operational Aviation Turbulence Prediction Model for Middle- and Upper- Levels

중·상층 항공난류 예측모델의 성능 평가와 개선

  • 강유정 (국립기상과학원 기상응용연구부) ;
  • 최희욱 (국립기상과학원 기상응용연구부) ;
  • 최유나 (국립기상과학원 기상응용연구부) ;
  • 이상삼 (국립기상과학원 기상응용연구부) ;
  • 황혜원 (항공기상청 예보과) ;
  • 이혁제 (항공기상청 예보과) ;
  • 이용희 (국립기상과학원 기상응용연구부)
  • Received : 2023.07.04
  • Accepted : 2023.07.31
  • Published : 2023.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

Aviation turbulence, caused by atmospheric eddies, is a disruptive phenomenon that leads to abrupt aircraft movements during flight. To minimize the damages caused by such aviation turbulence, the Aviation Meteorological Office provides turbulence information through the Korea aviation Turbulence Guidance (KTG) and the Global-Korean aviation Turbulence Guidance (GKTG). In this study, we evaluated the performance of the KTG and GKTG models by comparing the in-situ EDR observation data and the generated aviation turbulence prediction data collected from the mid-level Korean Peninsula region from January 2019 to December 2021. Through objective validation, we confirmed the level of prediction performance and proposed improvement measures based on it. As a result of the improvements, the KTG model showed minimal difference in performance before and after the changes, while the GKTG model exhibited an increase of TSS after the improvements.

Keywords

Acknowledgement

이 연구는 기상청 국립기상과학원 「수요자 맞춤형 기상정보 산출기술 개발 연구」(KMA2018-00622)의 지원으로 수행되었습니다.

References

  1. Lester, P., "Understanding turbulence through the analysis of DFDR information", In 32nd Aerospace Sciences Meeting and Exhibit, 1994, p.269.
  2. Sharman, R. D., and Lane, T., "Aviation Turbulence: Processes, Detection, Prediction", Springer International Publishing, Switzerland, 2016, p.523.
  3. Sharman, R. D., and Pearson, J. M., "Prediction of energy dissipation rates for aviation turbulence. Part I: Forecasting non convective turbulence", Journal of Applied Meteorology and Climatology, 56(2), 2017, pp.317-337. https://doi.org/10.1175/JAMC-D-16-0205.1
  4. Sharman, R. D., Tebaldi, C., Wiener, G., and Wolff, J., "An integrated approach to mid and upper-level turbulence forecasting", Weather and Forecasting, 21(3), 2006, pp.268-287. https://doi.org/10.1175/WAF924.1
  5. Storer, L. N., Williams, P. D., and Gill, P. G, "Aviation turbulence: Dynamics, forecasting, and response to climate change", Pure and Applied Geophysics, 176, 2019, pp.2081-2095. https://doi.org/10.1007/s00024-018-1822-0
  6. Lee, D. B., Chun, H. Y., Kim, S. H., Sharman, R. D., and Kim, J. H., "Development and evaluation of global Korean aviation turbulence forecast systems based on an operational numerical weather prediction model and in situ flight turbulence observation data", Weather and Forecasting, 37(3), 2022, pp.371-392. https://doi.org/10.1175/WAF-D-21-0095.1
  7. Kim, J. H., and Chun, H. Y., "Statistics and possible sources of aviation turbulence over South Korea", Journal of Applied Meteorology and Climatology, 50(2), 2011, pp.311-324. https://doi.org/10.1175/2010JAMC2492.1
  8. Kim, J. H., and Chun, H. Y., "A numerical simulation of convectively induced turbulence above deep convection", Journal of Applied Meteorology and Climatology, 51(6), 2012, pp.1180-1200. https://doi.org/10.1175/JAMC-D-11-0140.1
  9. Kim, J. H., and Chun, H. Y., "Development of the Korean aviation turbulence guidance (KTG) system using the operational unified model (UM) of the Korea meteorological administration (KMA) and pilot reports (PIREPs)", J. Korean Soc. Aviat. Aeronaut., 20(4), 2012, pp.76-83. https://doi.org/10.12985/ksaa.2012.20.4.076
  10. Lee, D. B., and Chun, H. Y., "Development of the Global-Korean aviation turbulence guidance (Global-KTG) system using the global data assimilation and prediction system (GDAPS) of the Korea meteorological administration (KMA)", Atmosphere, 28(2), 2018, pp.223-232. https://doi.org/10.14191/ATMOS.2018.28.2.223
  11. Dutton, J. A., and Panofsky, H. A., "Clear air turbulence: A mystery may be unfolding: High altitude turbulence poses serious problems for aviation and atmospheric science", Science, 167(3920), 1970, pp.937-944. https://doi.org/10.1126/science.167.3920.937
  12. Cho, John, Y. N., and Lindborg, E., "Horizontal velocity structure functions in the upper troposphere and lower stratosphere: 1. Obser- vations", Journal of Geophysical Research: Atmospheres", 106(D10), 2001, pp. 10223- 10232. https://doi.org/10.1029/2000JD900814
  13. Tung, K. K. and Orlando, W. W., "The k -3 and k -5/3 energy spectrum of atmospheric tur- bulence: Quasigeostrophic two-level model simulation", Journal of the Atmospheric Sciences, 60(6), 2003, pp.824-835. https://doi.org/10.1175/1520-0469(2003)060<0824:TKAKES>2.0.CO;2
  14. Sharman, R. D., Cornman, L. B., Meymaris, G., Pearson, J., and Farrar, T., "Description and derived climatologies of automated in situ eddy-dissipation-rate reports of atmospheric turbulence", Journal of Applied Meteorology and Climatology, 53(6), 2014, pp. 1416-1432. https://doi.org/10.1175/JAMC-D-13-0329.1
  15. Storer, L. N., Williams, P. D. and Joshi, M. M., "Global response of clear-air turbulence to climate change", Geophysical Research Letters, 44, 2017, pp.9976-9984. https://doi.org/10.1002/2017GL074618
  16. Williams, P. D., "Increased light, moderate, and severe clear-air turbulence in response to climate change", Advances in Atmospheric Sciences, 34, 2017, pp.576-586. https://doi.org/10.1007/s00376-017-6268-2
  17. Lee, S. H., Williams, P. D. and Frame, T. H. A., "Increased shear in the north Atlantic upper-level jet stream over the past four decades", Nature, 572, 2019, pp.639-642. https://doi.org/10.1038/s41586-019-1465-z
  18. Tenenbaum, J., Williams, P. D., Turp, D., Buchanan, P., Coulson, R., Gill, P. G., and Rukhovets, L., "Aircraft observations and reanalysis depictions of trends in the North Atlantic winter jet stream wind speeds and turbulence", Quarterly Journal of the Royal Meteorological Society, 148(747), 2022, pp. 2927-2941. https://doi.org/10.1002/qj.4342
  19. Kim, J. H., Chun, H. Y., Jang, W., and Sharman, R. D., "A study of forecast system for clear-air turbulence in Korea, Part II: Graphical Turbulence Guidance (GTG) system", Atmosphere, 19(3), 2009, pp.269-287.
  20. Mason, S. F., "Molecular Optical Activity and the Chiral Discriminations", Cambridge University Press, 1982.
  21. Fielding, A. H. and Bell, J. F., "A review of methods for the assessment of prediction errors in conservation presence/absence models", Environmental Conservation, 24(1), 1997, pp.38-49. https://doi.org/10.1017/S0376892997000088
  22. Allouche, O., Tsoar, A., and Kadmon, R., "Assessing the accuracy of species distribution models: Prevalence, kappa and the true skill statistic (TSS)", Journal of Applied Ecology, 43(6), 2006, pp.1223-1232. https://doi.org/10.1111/j.1365-2664.2006.01214.x
  23. Lee, D. B., and Chun, H. Y., "Development of the Korean Peninsula-Korean aviation turbulence guidance (KP-KTG) system using the local data assimilation and prediction system (LDAPS) of the Korea Meteorological Administration (KMA)", Atmosphere, 25(2), 2015, pp.367-374. https://doi.org/10.14191/ATMOS.2015.25.2.367
  24. Wandishin, M. S., Paulik, L. A., Hart, J., Etherton, B. J., and Petty, M. A., "Assessment of the Graphical Turbulence Guidance, Version 3 (GTG3)", NOAA Technical Memorandum OAR GSD-53, 2014.