In order to simulate a typhoon precisely, the satellite observation data has been assimilated using WRF (Weather Research and Forecasting model) three-Dimensional Variational (3DVAR) data assimilation system. The observation data used in 3DVAR was GPS Radio Occultation (GPS-RO) data which is loaded on Low-Earth Orbit (LEO) satellite. The refractivity of Earth is deduced by temperature, pressure, and water vapor. GPS-RO data can be obtained with this refractivity when the satellite passes the limb position with respect to its original orbit. In this paper, two typhoon cases were simulated to examine the characteristics of data assimilation. One had been occurred in the Western Pacific from 16 to 25 October, 2015, and the other had affected Korean Peninsula from 22 to 29 August, 2012. In the simulation results, the typhoon track between background (BGR) and assimilation (3DV) run were significantly different when the track appeared to be rapidly change. The surface wind speed showed large difference for the long forecasting time because the GPS-RO data contained much information in the upper level, and it took a time to impact on the surface wind. Along with the modified typhoon track, the differences in the horizontal distribution of accumulated rain rate was remarkable with the range of 600~500 mm. During 7 days, we estimated the characteristics between daily assimilated simulation (3DV) and initial time assimilation (3DV_7). Because 3DV_7 demonstrated the accurate track of typhoon and its meteorological variables, the differences in two experiments have found to be insignificant. Using observed rain rate data at 79 surface observatories, the statistical analysis has been carried on for the evaluation of quantitative improvement. Although all experiments showed underestimated rain amount because of low model resolution (27 km), the reduced Mean Bias and Root-Mean-Square Error were found to be 2.92 mm and 4.53 mm, respectively.

Abstract
 1. 서 론
 2. 연구방법
  2.1. 3차원 변분자료동화
  2.2. 태풍 사례와 실험설계
 3. 연구결과
 3.1. 자료동화 특성 분석
 3.2. 자료동화 간격 분석
 3.3. 통계 분석
 4. 결론 및 요약
 REFERENCES

• 박순영(부산대학교 환경연구원) | Soon-Young Park (Institute of Environmental Studies, Pusan National University)
• 유정우(부산대학교 지구환경시스템학부) | Jung-Woo Yoo (Division of Earth Environment System, Pusan National University)
• 강남영(국가태풍센터) | Nam-Young Kang (National Typhoon Center, Korea Meteorological Administration)
• 이순환(부산대학교 지구과학교육과) | Soon-Hwan Lee (Department of Earth Science Education, Pusan National University) Corresponding author