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Korean Meteorological Society (한국기상학회)
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A Study on Improvement of the Observation Error for Optimal Utilization of COSMIC-2 GNSS RO Data

COSMIC-2 GNSS RO 자료 활용을 위한 관측오차 개선 연구

  • Eun-Hee Kim (Numerical Modeling Center, Korea Meteorological Administration) ;
  • Youngsoon Jo (Numerical Modeling Center, Korea Meteorological Administration) ;
  • Hyoung-Wook Chun (Numerical Modeling Center, Korea Meteorological Administration) ;
  • Ji-Hyun Ha (Numerical Modeling Center, Korea Meteorological Administration) ;
  • Seungbum Kim (Numerical Modeling Center, Korea Meteorological Administration)
  • 김은희 (수치모델링센터 수치자료응용과) ;
  • 조영순 (수치모델링센터 수치자료응용과) ;
  • 전형욱 (수치모델링센터 수치자료응용과) ;
  • 하지현 (수치모델링센터 수치자료응용과) ;
  • 김승범 (수치모델링센터 수치자료응용과)
  • Received : 2022.12.26
  • Accepted : 2023.02.15
  • Published : 2023.02.28
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Abstract

In this study, for the application of observation errors to the Korean Integrated Model (KIM) to utilize the Constellation Observing System for Meteorology, Ionosphere & Climate-2 (COSMIC-2) new satellites, the observation errors were diagnosed based on the Desroziers method using the cost function in the process of variational data assimilation. We calculated observation errors for all observational species being utilized for KIM and compared with their relative values. The observation error of the calculated the Global Navigation Satellite System Radio Occultation (GNSS RO) was about six times smaller than that of other satellites. In order to balance with other satellites, we conducted two experiments in which the GNSS RO data expanded by about twice the observation error. The performance of the analysis field was significantly improved in the tropics, where the COSMIC-2 data are more available, and in the Southern Hemisphere, where the influence of GNSS RO data is significantly greater. In particular, the prediction performance of the Southern Hemisphere was improved by doubling the observation error in global region, rather than doubling the COSMIC-2 data only in areas with high density, which seems to have been balanced with other observations.

Keywords

Acknowledgement

본 논문의 완성도를 높이기 위해 좋은 의견을 제시해 주신 두 분의 심사위원께 감사를 드립니다. 이 연구는 수치모델링센터 『수치예보 및 자료응용 기술개발(KMA2018-00721)』 과제의 일환으로 수행되었습니다.

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