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Korean Meteorological Society (한국기상학회)
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A Study on the Effect of Ground-based GPS Data Assimilation into Very-short-range Prediction Model

초단기 예측모델에서 지상 GPS 자료동화의 영향 연구

  • Kim, Eun-Hee (Numerical Data Application Division, National Institute of Meteorological Sciences, KMA) ;
  • Ahn, Kwang-Deuk (Numerical Data Application Division, National Institute of Meteorological Sciences, KMA) ;
  • Lee, Hee-Choon (Environmental Meteorology Research Division, National Institute of Meteorological Sciences, KMA) ;
  • Ha, Jong-Chul (Observation Research Division, National Institute of Meteorological Sciences, KMA) ;
  • Lim, Eunha (Observation Research Division, National Institute of Meteorological Sciences, KMA)
  • 김은희 (국립기상과학원 관측예보연구과) ;
  • 안광득 (국립기상과학원 관측예보연구과) ;
  • 이희춘 (국립기상과학원 황사연구과) ;
  • 하종철 (국립기상과학원 관측기반연구과) ;
  • 임은하 (국립기상과학원 관측기반연구과)
  • Received : 2015.07.30
  • Accepted : 2015.11.19
  • Published : 2015.12.31
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Abstract

The accurate analysis of water vapor in initial of numerical weather prediction (NWP) model is required as one of the necessary conditions for the improvement of heavy rainfall prediction and reduction of spin-up time on a very-short-range forecast. To study this effect, the impact of a ground-based Global Positioning System (GPS)-Precipitable Water Vapor (PWV) on very-short-range forecast are examined. Data assimilation experiments of GPS-PWV data from 19 sites over the Korean Peninsula were conducted with Advanced Storm-scale Analysis and Prediction System (ASAPS) based on the Korea Meteorological Administration's Korea Local Analysis and Prediction System (KLAPS) included "Hot Start" as very-short-range forecast system. The GPS total water vapor was used as constraint for integrated water vapor in a variational humidity analysis in KLAPS. Two simulations of heavy rainfall events show that the precipitation forecast have improved in terms of ETS score compared to the simulation without GPS-PWV data. In the first case, the ETS for 0.5 mm of rainfall accumulated during 3 hrs over the Seoul-Gyeonggi area shows an improvement of 0.059 for initial forecast time. In other cases, the ETS improved 0.082 for late forecast time. According to a qualitative analysis, the assimilation of GPS-PWV improved on the intensity of precipitation in the strong rain band, and reduced overestimated small amounts of precipitation on the out of rain band. In the case of heavy rainfall during the rainy season in Gyeonggi province, 8 mm accompanied by the typhoon in the case was shown to increase to 15 mm of precipitation in the southern metropolitan area. The GPS-PWV assimilation was extremely beneficial to improving the initial moisture analysis and heavy rainfall forecast within 3 hrs. The GPS-PWV data on variational data assimilation have provided more useful information to improve the predictability of precipitation for very short range forecasts.

Keywords

References

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