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Assessment of Assimilation Impact of Argo Float Observations in Marginal Seas around Korean Peninsula through Observing System Experiments

관측시스템 실험을 통한 한반도 근해 Argo 플로트 관측자료의 자료동화 효과 평가

  • Choo, Sung-Ho (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Chang, Pil-Hun (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Hwang, Seung-On (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Jo, Hyeong-Jun (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Lee, Johan (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Lee, Sang-Min (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Hyun, Yu-Kyung (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Moon, Jae-Hong (Department of Earth and Marine Sciences, College of Ocean Sciences, Jeju National University)
  • 추성호 (국립기상과학원 현업운영개발부) ;
  • 장필훈 (국립기상과학원 현업운영개발부) ;
  • 황승언 (국립기상과학원 현업운영개발부) ;
  • 조형준 (국립기상과학원 현업운영개발부) ;
  • 이조한 (국립기상과학원 현업운영개발부) ;
  • 이상민 (국립기상과학원 현업운영개발부) ;
  • 현유경 (국립기상과학원 현업운영개발부) ;
  • 문재홍 (제주대학교 해양과학대학 지구해양과학과)
  • Received : 2021.06.28
  • Accepted : 2021.08.20
  • Published : 2021.09.30

Abstract

An Observing System Experiment (OSE) using Global Ocean Data Assimilation and Prediction System (GODAPS) was conducted to evaluate the assimilation impact of Argo floats, deployed by National Institute of Meteorological Sciences/Korea Meteorological Administration (NIMS/KMA), in marginal seas around Korean peninsula. A data denial experiment was run by removing Argo floats in the Yellow Sea and the East Sea from an operational run. The assimilation results show that Argo floats bring the positive impact on the analysis of ocean internal structure in both Yellow Sea and East Sea. In the East Sea, overall positive impact in the water temperature and salinity context is found, especially outstanding improvement from 300 to 500 m depth. In the Yellow sea, the assimilation impact on water temperature and salinity is also large within 50 m depth, especially greater impact than the East Sea in salinity. However, in the Yellow Sea, the influence of Argo floats tends to be restricted to the vicinity of Argo floats, because there was only one Argo float in the middle of the Yellow Sea during the experiment period. Given that the only limited number of Argo floats generally contribute in a positive way to the improvement of the GODAPS, further progress could be expected with adding more observations from Argo floats to current observing systems.

Keywords

References

  1. AST, 1998: On the design and implementation of Argo: An initial plan for a global array of profiling floats. The Argo Science Team, International CLIVAR Project Office Rep. 21, GODAE Rep. 5. GODAE International Project Office, 32 pp.
  2. AST, 2001: Argo: The global array for profiling floats. In C. J. Koblinsky et al. Eds., Observing the Oceans in the 21st Century, GODAE Project Office and Bureau of Meteorology, 248-258.
  3. Balmaseda, M., D. Anderson, and A. Vidard, 2007: Impact of Argo on analyses of the global ocean. Geophys. Res. Lett., 34, L16605.
  4. Chang, P.-H., S.-O. Hwang, S.-H. Choo, J. Lee, S.-M. Lee, and K.-O. Boo, 2021: Global Ocean Data Assimilation and Prediction System in KMA: Description and assessment. Atmosphere, 31, 229-240, doi:10.14191/Atmos.2021.31.2.229 (in Korean with English abstract).
  5. Fu, H., P. C. Chu, G. Han, Z. He, W. Li, and X. Zhang, 2013: Improvement of short-term forecasting in the northwest Pacific through assimilating Argo data into initial fields. Acta Oceanol. Sin., 32, 57-65, doi:10.1007/s13131-013-0332-2.
  6. Grayek, S., E. V. Stanev, and J. Schulz-Stellenfleth, 2015: Assessment of the Black Sea observing system. A focus on 2005-2012 Argo campaigns. Ocean Dyn., 65, 1665-1684, doi:10.1007/s10236-015-0889-8.
  7. Huang, B., Y. Xue, and D. W. Behringer, 2008: Impacts of Argo salinity in NCEP Global Ocean Data Assimilation System: The tropical Indian Ocean. J. Geophys. Res. Oceans, 113, C08002, doi:10.1029/2007JC004388.
  8. Hyun, Y.-K., J. Park, J. Lee, S. Lim, S.-I. Heo, H. Ham, S.-M. Lee, H.-S. Ji, and Y. Kim, 2020: Reliability assessment of temperature and precipitation seasonal predictability in current climate prediction systems. Atmosphere, 30, 141-154, doi:10.14191/Atmos.2020.30.2.141 (in Korean with English abstract).
  9. Jeong, Y. Y., I.-J. Moon, and S.-H. Kim, 2013: A study on upper ocean response to typhoon Ewiniar (0603) and its impact. Atmosphere, 23, 205-220, doi:10.14191/Atmos.2013.23.2.205 (in Korean with English abstract).
  10. Jeong, Y. Y., I.-J. Moon, and P.-H. Chang, 2016: Accuracy of short-term ocean prediction and the effect of atmosphere-ocean coupling on KMA Global Seasonal Forecast System (GloSea5) during the development of ocean stratification. Atmosphere, 26, 599-615, doi:10.14191/Atmos.2016.26.4.599 (in Korean with English abstract).
  11. Kim, D.-K., Y.-H. Kim, and C. Yoo, 2019: Predictability of Northern Hemisphere teleconnection patterns in GloSea5 hindcast experiments up to 6 weeks. Atmosphere, 29, 295-309, doi:10.14191/Atmos.2019.29.3.295 (in Korean with English abstract).
  12. Lee, H., P.-H. Chang, K. Kang, H.-S. Kang, and Y. Kim, 2018: Assessment of ocean surface current forecasts from high resolution Global Seasonal Forecast System version 5. Ocean Polar Res., 40, 99-114, doi:10.4217/OPR.2018.40.3.099 (in Korean with English abstract).
  13. Lee, H., Y.-S. Chang, T.-H. Kim, J.-H. Kim, Y.-H. Youn, J.-W. Seo, and T.-G. Seo, 2004: Global ocean observation with ARGO floats: Introduction to ARGO program. Atmosphere, 14, 4-23 (in Korean with English abstract).
  14. Lee, J.-H., I.-C. Pang, and J.-H. Moon, 2016: Contribution of the Yellow Sea bottom cold water to the abnormal cooling of sea surface temperature in the summer of 2011. J. Geophys. Res. Oceans, 121, 3777-3789, doi: 10.1002/2016JC011658.
  15. Lee, S.-J., Y.-K. Hyun, S.-M. Lee, S.-O. Hwang, J. Lee, and K.-O. Boo, 2020: Prediction skill for East Asian summer monsoon indices in a KMA Global Seasonal Forecasting System (GloSea5). Atmosphere, 30, 293-309, doi:10.14191/Atmos.2020.30.3.293 (in Korean with English abstract).
  16. Lim, S.-M., Y.-K., Hyun, H.-S., Kang, and S.-W. Yeh, 2018: Prediction skill of East Asian precipitation and temperature associated with El Nino in GloSea5 hindcast data. Atmosphere, 28, 37-51, doi:10.14191/Atmos.2018.28.1.037 (in Korean with English abstract).
  17. Moon, I.-J., and S. J. Kwon, 2011: Impact of upper-ocean thermal structure on the intensity of Korean peninsular landfall typhoons. Prog. Oceanogr., 105, 61-66, doi:10.1016/j.pocean.2012.04.008.
  18. Moon, J.-H., N. Hirose, and J.-H. Yoon, 2009: Comparison of wind and tidal contributions to seasonal circulation of the Yellow Sea. J. Geophys. Res. Oceans, 114, C08016, doi:10.1029/2009JC005314.
  19. Moon, J.-H., T. Kim, Y. B. Son, J.-S. Hong, J.-H. Lee, P.-H Chang, and S.-K. Kim, 2019: Contribution of low-salinity water to sea surface warming of the East China Sea in the summer of 2016. Prog. Oceanogr., 175, 68-80, doi:10.1016/j.pocean.2019.03.012.
  20. NIMS, 2020: Research and Development for KMA Weather, Climate, and Earth system Services: Development of Marine Meteorology Monitoring and Next-generation Ocean Forecasting System (VII). National Institute of Meteorological Sciences, ISBN 11-136020-000121-10, 83 pp (in Korean).
  21. Oke, P. R., and A. Schiller, 2007: Impact of Argo, SST, and altimeter data on an eddy-resolving ocean reanalysis. Geophys. Res. Lett., 34, L19601. https://doi.org/10.1029/2007GL031549
  22. Park, S., P. C. Chu, and J.-H. Lee, 2011a: Interannual-to-interdecadal variability of the Yellow Sea Cold Water Mass in 1967-2008: Characteristics and seasonal forcings. J. Mar. Syst., 87, 177-193, doi:10.1016/j.jmarsys.2011.03.012.
  23. Park, T., C. J. Jang, J. H. Jungclaus, H. Haak, W. Park, and I. S. Oh, 2011b: Effects of the Changjiang river discharge on sea surface warming in the Yellow and East China Seas in summer. Cont. Shelf Res., 31, 15-22, doi:10.1016/j.csr.2010.10.012.
  24. Roemmich, D., G. C. Johnson, S. Riser, R. Davis, J. Gilson, W. B. Owens, S. L. Garzoli, C. Schmid, and M. Ignaszewski, 2009: The Argo Program: Observing the global ocean with profiling floats. Oceanography, 22, 34-43.
  25. Shao, C., L. Xuan, Y. Cao, X. Cui, and S. Gao, 2015: Impact of Argo observation on the regional ocean reanalysis of China coastal waters and adjacent seas: A twin-experiment study. Adv. Meteorol., 2015, 793825, doi:10.1155/2015/793825.
  26. Wang, B., N. Hirose, B. Kang, and K. Takayama, 2014: Seasonal migration of the Yellow Sea Bottom Cold Water. J. Geophys. Res. Oceans, 119, 4430-4443, doi: 10.1002/2014JC009873.
  27. Yan, C., J. Zhu, and G. Zhou, 2007: Impacts of XBT, TAO, altimetry and ARGO observations on the tropical Pacific Ocean data assimilation. Adv. Atmos. Sci., 24, 383-398. https://doi.org/10.1007/s00376-007-0383-4
  28. Youn, Y.-H., Y.-H. Park, and J.-H. Bong, 1991: Enlightenment of the characteristics of the Yellow Sea Bottom Cold Water and its southward extension. J. Korean Earth Sci. Soc., 12, 25-37 (in Korean with English abstract).
  29. Youn, Y.-H., Y.-S. Chang, Y.-K. Hyun, C.-W. Cho, J.-O. Ku, M.-K. Cho, Y.-S. Ban, S.-J. Park, and S.-J. Kim, 2006: Variability of ocean status around Ulleung Basin and Dok-do by using ARGO data. Atmosphere, 16, 379-385 (in Korean with English abstract).