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Korean Meteorological Society (한국기상학회)
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A Monitoring System of Ensemble Forecast Sensitivity to Observation Based on the LETKF Framework Implemented to a Global NWP Model

앙상블 기반 관측 자료에 따른 예측 민감도 모니터링 시스템 구축 및 평가

  • Lee, Youngsu (Korea Institute of Atmospheric Prediction Systems) ;
  • Shin, Seoleun (Korea Institute of Atmospheric Prediction Systems) ;
  • Kim, Junghan (Korea Institute of Atmospheric Prediction Systems)
  • 이영수 ((재) 한국형예보모델개발사업단) ;
  • 신설은 ((재) 한국형예보모델개발사업단) ;
  • 김정한 ((재) 한국형예보모델개발사업단)
  • Received : 2019.12.30
  • Accepted : 2020.05.10
  • Published : 2020.06.30
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Abstract

In this study, we analyzed and developed the monitoring system in order to confirm the effect of observations on forecast sensitivity on ensemble-based data assimilation. For this purpose, we developed the Ensemble Forecast Sensitivity to observation (EFSO) monitoring system based on Local Ensemble Transform Kalman Filter (LETKF) system coupled with Korean Integrated Model (KIM). We calculated 24 h error variance of each of observations and then classified as beneficial or detrimental effects. In details, the relative rankings were according to their magnitude and analyzed the forecast sensitivity by region for north, south hemisphere and tropics. We performed cycle experiment in order to confirm the EFSO result whether reliable or not. According to the evaluation of the EFSO monitoring, GPSRO was classified as detrimental observation during the specified period and reanalyzed by data-denial experiment. Data-denial experiment means that we detect detrimental observation using the EFSO and then repeat the analysis and forecast without using the detrimental observations. The accuracy of forecast in the denial of detrimental GPSRO observation is better than that in the default experiment using all of the GPSRO observation. It means that forecast skill score can be improved by not assimilating observation classified as detrimental one by the EFSO monitoring system.

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References

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