Atmosphere (대기)

Korean Meteorological Society (한국기상학회)
권호 표지
DOI QR코드

DOI QR Code

Changma Onset and Withdrawal Prediction Skill Using Korean Integrated Model (KIM): Focused on the Case Study of 2021 Changma

한국형앙상블모델(KIM)의 장마 시종일 예측성능 진단: 2021년 장마사례를 중심으로

  • Ju Heon Kim (Division of Earth and Environmental System Sciences, Major of Environmental Atmospheric Sciences, Pukyong National University) ;
  • Ji-Han Sim (Division of Earth and Environmental System Sciences, Major of Environmental Atmospheric Sciences, Pukyong National University) ;
  • Baek-Min Kim (Division of Earth and Environmental System Sciences, Major of Environmental Atmospheric Sciences, Pukyong National University)
  • 김주헌 (부경대학교 지구환경시스템과학부 환경대기과학전공) ;
  • 심지한 (부경대학교 지구환경시스템과학부 환경대기과학전공) ;
  • 김백민 (부경대학교 지구환경시스템과학부 환경대기과학전공)
  • Received : 2024.07.26
  • Accepted : 2024.08.23
  • Published : 2024.11.30
Download PDF
⟨ Previous Next ⟩

Abstract

The accurate prediction of Changma (Korean summer monsoon) onset and withdrawal dates is crucial for various sectors including agriculture, water resource management, and disaster prevention. This study applies 25 ensemble members from the operational Korean Integrated Model (KIM) to the Korea Meteorological Administration (KMA) Changma Index (CMI) to diagnose the forecast skill for the onset and withdrawal dates of the 2021 Changma, which marked as the third shortest period on record. The CMI, consisting of 200 hPa geopotential height and zonal wind variables around the Korean Peninsula, was used to compare reanalysis data and KIM's ensemble forecast data. While the CMI from individual ensemble members showed significant variability in predicting the Changma onset and withdrawal dates, the ensemble mean CMI accurately predicted the Changma onset date 12 days in advance with a one-day error margin, and also accurately predicted the Changma withdrawal date 9 days in advance. Detailed analysis of the variables constituting the CMI in KIM's ensemble forecast data indicated that variations in the 200 hPa geopotential height were particularly influential in determining the Changma onset and withdrawal dates. These results demonstrate that the ensemble mean forecast of KIM is more effective than individual ensemble member forecasts for predicting Changma onset and withdrawal dates, highlights the utility of KIM's ensemble forecast data and the effectiveness of using upper atmospheric variables (specifically 200 hPa geopotential height) for these predictions.

Keywords

Acknowledgement

본 연구는 국립부경대학교 자율창의학술연구비(2024년)에 의하여 연구되었음. 또한, 본 연구는 기상청 수치모델링센터에서 한국형앙상블모델(KIM) 자료를 제공받아 수행되었음.

References

  1. Chevuturi, A., A. G. Turner, S. J. Woolnough, G. M. Martin, and C. MacLachlan, 2019: Indian summer monsoon onset forecast skill in the UK Met Office initialized coupled seasonal forecasting system (GloSea5-GC2). Climate Dyn., 52, 6599-6617, doi:10.1007/s00382-018-4536-1.
  2. Chevuturi, A., A. G. Turner, S. Johnson, A. Weisheimer, J. K. P. Shonk, T. N. Stockdale, and R. Senan, 2021: Forecast skill of the Indian monsoon and its onset in the ECMWF seasonal forecasting system 5 (SEAS5). Climate Dyn., 56, 2941-2957, doi:10.1007/s00382-020-05624-5.
  3. Choi, S.-J., and S.-Y. Hong, 2016: A global non-hydrostatic dynamical core using the spectral element method on a cubed-sphere grid. Asia-Pac. J. Atmos. Sci., 52, 291-307, doi:10.1007/s13143-016-0005-0.
  4. Chu, J.-E., S. N. Hameed, and K.-J. Ha, 2012: Nonlinear, intraseasonal phases of the East Asian summer monsoon: Extraction and analysis using self-organizing maps. J. Climate, 25, 6975-6988, doi:10.1175/JCLID-11-00512.1.
  5. Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553-597, doi:10.1002/qj.828.
  6. Dong, G., H. Zhang, A. Moise, L. Hanson, P. Liang, and H. Ye, 2015: CMIP5 model-simulated onset, duration and intensity of the Asian summer monsoon in current and future climate. Climate Dyn., 46, 355-382, doi:10.1007/s00382-015-2588-z.
  7. Ha, K.-J., K.-S. Yun, J.-G. Jhun, and C.-K. Park, 2005: Definition of onset/retreat and intensity of Changma during the boreal summer monsoon season. J. Korean Meteor. Soc., 41, 927-942 (in Korean with English abstract).
  8. Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146, 1999-2049, doi:10.1002/qj.3803.
  9. Ho, C.-H., J.-Y. Lee, M.-H. Ahn, and H.-S. Lee, 2003: A sudden change in summer rainfall characteristics in Korea during the late 1970s. Int. J. Climatol., 23, 117-128, doi:10.1002/joc.864.
  10. 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.
  11. Huffman, G. J., D. T. Bolvin, and E. J. Nelkin, 2015: Day 1 IMERG final run release notes. NASA/GSFC: Greenbelt, MD, USA, 9 pp.
  12. 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.
  13. KMA, 2011: 2011 White Paper on Changma. Korea Meteorological Administration, 266 pp (in Korean).
  14. KMA, 2012: Handheld forecasting; Stationary Fronts. Korea Meteorological Administration, 15, 12 pp (in Korean).
  15. KMA, 2021: 2021 Abnormal Climate Report. Korea Meteorological Administration, 234 pp (in Korean).
  16. KMA, 2022: 2022 White Paper on Changma. Korea Meteorological Administration, 394 pp (in Korean).
  17. KMA NMC, 2022: Verification of numerical weather forecasting system. Korea Meteorological Administration Numerical Modeling Center (in Korean).
  18. Kwon, S.-H., K.-O. Boo, S. Shim, and Y.-H. Byun, 2017: Evaluation of the East Asian summer monsoon season simulated in CMIP5 models and the future change. Atmosphere, 27, 133-150, doi:10.14191/Atmos.2017.27.2.133.
  19. Lau, K.-M., and M.-T. Li, 1984: The monsoon of East Asia and its global associations-A survey. Bull. Amer. Meteor. Soc., 65, 114-125, doi:10.1175/1520-0477(1984)065<0114:TMOEAA>2.0.CO;2.
  20. Lee, S.-E., and K.-H. Seo, 2013: The development of a statistical forecast model for Changma. Wea. Forecasting, 28, 1304-1321, doi:10.1175/WAF-D-13-00003.1.
  21. Seo, K.-H., J.-H. Son, and J.-Y. Lee, 2011: A new look at Changma. Atmosphere, 21, 109-121, doi:10.14191/Atmos.2011.21.1.109.
  22. Wang, B., J.-G. Jhun, and B.-K. Moon, 2007: Variability and singularity of Seoul, South Korea, rainy season (1778~2004). J. Climate, 20, 2572-2580, doi:10.1175/JCLI4123.1.
  23. Wang, B., and LinHo, 2002: Rainy season of the Asian Pacific summer monsoon. J. Climate, 15, 386-398, doi:10.1175/1520-0442(2002)015<0386:RSOTAP>2.0.CO;2.
  24. Yong, B., D. Liu, J. J. Gourley, Y. Tian, G. J. Huffman, L. Ren, and Y. Hong, 2015: Global view of real-time TRMM multisatellite precipitation analysis: Implications for its successor global precipitation measurement mission. Bull. Amer. Meteor. Soc., 96, 283-296, doi:10.1175/BAMS-D-14-00017.1.