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The KMA Global Seasonal Forecasting System (GloSea6) - Part 1: Operational System and Improvements

기상청 기후예측시스템(GloSea6) - Part 1: 운영 체계 및 개선 사항

  • Kim, Hyeri (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Lee, Johan (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Hyun, Yu-Kyung (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Hwang, Seung-On (Operational Systems Development Department, National Institute of Meteorological Sciences)
  • 김혜리 (국립기상과학원 현업운영개발부) ;
  • 이조한 (국립기상과학원 현업운영개발부) ;
  • 현유경 (국립기상과학원 현업운영개발부) ;
  • 황승언 (국립기상과학원 현업운영개발부)
  • Received : 2021.08.11
  • Accepted : 2021.09.14
  • Published : 2021.09.30

Abstract

This technical note introduces the new Korea Meteorological Administration (KMA) Global Seasonal forecasting system version 6 (GloSea6) to provide a reference for future scientific works on GloSea6. We describe the main areas of progress and improvements to the current GloSea5 in the scientific and technical aspects of all the GloSea6 components - atmosphere, land, ocean, and sea-ice models. Also, the operational architectures of GloSea6 installed on the new KMA supercomputer are presented. It includes (1) pre-processes for atmospheric and ocean initial conditions with the quasi-real-time land surface initialization system, (2) the configurations for model runs to produce sets of forecasts and hindcasts, (3) the ensemble statistical prediction system, and (4) the verification system. The changes of operational frameworks and computing systems are also reported, including Rose/Cylc - a new framework equipped with suite configurations and workflows for operationally managing and running Glosea6. In addition, we conduct the first-ever run with GloSea6 and evaluate the potential of GloSea6 compared to GloSea5 in terms of verification against reanalysis and observations, using a one-month case of June 2020. The GloSea6 yields improvements in model performance for some variables in some regions; for example, the root mean squared error of 500 hPa geopotential height over the tropics is reduced by about 52%. These experimental results show that GloSea6 is a promising system for improved seasonal forecasts.

Keywords

Acknowledgement

이 연구는 기상청 국립기상과학원 「기후예측 현업 시스템 개발」 (KMA2018-00322)의 지원으로 수행되었습니다.

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