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Korean Meteorological Society (한국기상학회)
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Development and Evaluation of the High Resolution Limited Area Ensemble Prediction System in the Korea Meteorological Administration

기상청 고해상도 국지 앙상블 예측 시스템 구축 및 성능 검증

  • Kim, SeHyun (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University) ;
  • Kim, Hyun Mee (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University) ;
  • Kay, Jun Kyung (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University) ;
  • Lee, Seung-Woo (Korea Meteorological Administration)
  • 김세현 (연세대학교 대기과학과, 대기예측성 및 자료동화 연구실) ;
  • 김현미 (연세대학교 대기과학과, 대기예측성 및 자료동화 연구실) ;
  • 계준경 (연세대학교 대기과학과, 대기예측성 및 자료동화 연구실) ;
  • 이승우 (기상청 수치모델개발과)
  • Received : 2014.11.14
  • Accepted : 2015.01.22
  • Published : 2015.03.31
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Abstract

Predicting the location and intensity of precipitation still remains a main issue in numerical weather prediction (NWP). Resolution is a very important component of precipitation forecasts in NWP. Compared with a lower resolution model, a higher resolution model can predict small scale (i.e., storm scale) precipitation and depict convection structures more precisely. In addition, an ensemble technique can be used to improve the precipitation forecast because it can estimate uncertainties associated with forecasts. Therefore, NWP using both a higher resolution model and ensemble technique is expected to represent inherent uncertainties of convective scale motion better and lead to improved forecasts. In this study, the limited area ensemble prediction system for the convective-scale (i.e., high resolution) operational Unified Model (UM) in Korea Meteorological Administration (KMA) was developed and evaluated for the ensemble forecasts during August 2012. The model domain covers the limited area over the Korean Peninsula. The high resolution limited area ensemble prediction system developed showed good skill in predicting precipitation, wind, and temperature at the surface as well as meteorological variables at 500 and 850 hPa. To investigate which combination of horizontal resolution and ensemble member is most skillful, the system was run with three different horizontal resolutions (1.5, 2, and 3 km) and ensemble members (8, 12, and 16), and the forecasts from the experiments were evaluated. To assess the quantitative precipitation forecast (QPF) skill of the system, the precipitation forecasts for two heavy rainfall cases during the study period were analyzed using the Fractions Skill Score (FSS) and Probability Matching (PM) method. The PM method was effective in representing the intensity of precipitation and the FSS was effective in verifying the precipitation forecast for the high resolution limited area ensemble prediction system in KMA.

Keywords

References

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