A Study on Improvement of the Use and Quality Control for New GNSS RO Satellite Data in Korean Integrated Model

한국형모델의 신규 GNSS RO 자료 활용과 품질검사 개선에 관한 연구

  • Kim, Eun-Hee (Numerical Modeling Center, Korea Meteorological Administration) ;
  • Jo, Youngsoon (Numerical Modeling Center, Korea Meteorological Administration) ;
  • Lee, Eunhee (Numerical Modeling Center, Korea Meteorological Administration) ;
  • Lee, Yong Hee (High Impact Weather Research Department, National Institute of Meteorological Sciences, Korea Meteorological Administration)
  • 김은희 (수치모델링센터 수치자료응용과) ;
  • 조영순 (수치모델링센터 수치자료응용과) ;
  • 이은희 (수치모델링센터 수치자료응용과) ;
  • 이용희 (국립기상과학원 재해기상연구부)
  • Received : 2021.02.08
  • Accepted : 2021.07.16
  • Published : 2021.09.30


This study examined the impact of assimilating the bending angle (BA) obtained via the global navigation satellite system radio occultation (GNSS RO) of the three new satellites (KOMPSAT-5, FY-3C, and FY-3D) on analyses and forecasts of a numerical weather prediction model. Numerical data assimilation experiments were performed using a three-dimensional variational data assimilation system in the Korean Integrated Model (KIM) at a 25-km horizontal resolution for August 2019. Three experiments were designed to select the height and quality control thresholds using the data. A comparison of the data with an analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) integrated forecast system showed a clear positive impact of BA assimilation in the Southern Hemisphere tropospheric temperature and stratospheric wind compared with that without the assimilation of the three new satellites. The impact of new data in the upper atmosphere was compared with observations using the infrared atmospheric sounding interferometer (IASI). Overall, high volume GNSS RO data helps reduce the RMSE quantitatively in analytical and predictive fields. The analysis and forecasting performance of the upper temperature and wind were improved in the Southern and Northern Hemispheres.



  1. Anthes, R. A., 2011: Exploring earth's atmosphere with radio occultation: contributions to weather, climate and space weather. Atmos. Meas. Tech., 4, 1077-1103, doi:10.5194/amt-4-1077-2011.
  2. Bauer, P., G. Radnoti, S. Healy, and C. Cardinali, 2014: GNSS radio occultation constellation observing system experiments. Mon. Wea. Rev., 142, 555-572, doi:10.1175/MWR-D-13-00130.1.
  3. Bowler, N. E., 2019: An initial assessment of the quality of RO data from FY-3D. ROM SAF Report 35, 19 pp.
  4. Cardinali, C., and S. Healy, 2014: Impact of GPS radio occultation measurements in the ECMWF system using adjoint-based diagnostics. Q. J. R. Meteorol Soc., 140, 2315-2320, doi:10.1002/qj.2300.
  5. Collard, A. D., 2007: Selection of IASI channels for use in numerical weather prediction. Q. J. R. Meteorol. Soc., 133, 1977-1991.
  6. Cucurull, L., and R. A. Anthes, 2015: Impact of loss of U.S. microwave and radio occultation observations in operational numerical weather prediction in support of the U.S. data gap mitigation activities. Wea. Forecasting, 30, 255-269, doi:10.1175/WAF-D-14-00077.1.
  7. Dennis, J. M., J. Edwards, K. J. Evans, O. Guba, P. H. Lauritzen, A. A. Mirin, A. St-Cyr, M. A. Taylor, and P. H. Worley, 2012: CAM-SE: A scalable spectral element dynamical core for the Community Atmosphere Model. Int. J. High Perform. Comput. Appl., 26, 74-89, doi:10.1177/1094342011428142.
  8. Ha, J.-H., J.-H. Kang, and S.-J. Choi, 2018: The impact of vertical resolution in the assimilation of GPS radio occultation data. Wea. Forecasting, 33, 1033-1044, doi:10.1175/WAF-D-17-0061.1.
  9. Healy, S. B., 2008: Assimilation of GPS radio occultation measurements at ECMWF. Proc. ECMWF GRAS SAF workshop on applications of GPS Radio Occultation Measurements, Shinfield Park, Reading, UK, ECMWF, 99-109.
  10. Healy, S. B., and J.-N. Thepaut, 2006: Assimilation experiments with CHAMP GPS radio occultation measurements. Q. J. R. Meteorol. Soc., 132, 605-623.
  11. Ho, S.-P., and Coauthors, 2020: The COSMIC/FORMOSAT-3 radio occultation mission after 12 years: Accomplishments, remaining challenges, and potential impact of COSMIC-2. Bull. Amer. Meteor. Soc., 101, E1107-E1136, doi:10.1175/BAMS-D-18-0290.1.
  12. Hong, S.-Y., and Coauthors, 2018: The Korean Integrated Model (KIM) system for global weather forecasting. Asia-Pac. J. Atmos. Sci., 54, 267-292, doi:10.1007/s13143-018-0028-9.
  13. Hunt, B. R., E. J. Kostelich, and I. Szunyogh, 2007: Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter. Physica D., 230, 112-126.
  14. Jo, Y., J.-S. Kang, and H. Kwon, 2015: Optimization of the vertical localization scale for GPS-RO data assimilation within KIAPS-LETKF system. Atmosphere, 25, 529-541, doi:10.14191/Atmos.2015.25.3.529 (in Korean with English abstract).
  15. Kang, J.-H., and Coauthors, 2018: Development of an observation processing package for data assimilation in KIAPS. Asia-Pac. J. Atmos. Sci., 54, 303-318, doi:10.1007/s13143-018-0030-2.
  16. Kursinski, E. R., G. A. Hajj, J. T. Schofield, R. P. Linfield, and K. R. Hardy, 1997: Observing earth's atmosphere with radio occultation measurements using the global positioning system. J. Geophys. Res. Atmos., 102, 23429-23465.
  17. Kwon, H., J.-S. Kang, Y. Jo, and J. H. Kang, 2015: Implementation of a GPS-RO data processing system for the KIAPS-LETKF data assimilation system. Atmos. Meas. Tech., 8, 1259-1273, doi:10.5194/amt-8-1259-2015.
  18. Kwon, I.-H., and Coauthors, 2018: Development of an operational hybrid data assimilation system at KIAPS. Asia-Pac. J. Atmos. Sci., 54, 319-335, doi:10.1007/s13143-018-0029-8.
  19. Melbourne, W. G., E. S. Davis, C. B. Duncan, G. A. Haji, K. R. Hardy, E. R. Kursinski, T. K. Meehan, L. E. Young, and T. P. Yunck, 1994: The application of spaceborne GPS to atmospheric limb sounding and global change monitoring. NASA, Jet Propulsion Laboratory, JPL94-18, 147 pp.
  20. Mi, L., S. Healy, and P. Zhang, 2019: Processing and quality control of FY-3C GNOS data used in numerical weather prediction applications. Atmos. Meas. Tech., 12, 2679-2692, doi:10.5194/amt-12-2679-2019.
  21. Rennie, M., P., 2010: The impact of GPS radio occultation assimilation at the Met Office. Q. J. R. Meteorol. Soc., 136, 116-131, doi:10.1002/qj.521.