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Impact of GPS-RO Data Assimilation in 3DVAR System on the Typhoon Event

태풍 수치모의에서 GPS-RO 인공위성을 사용한 관측 자료동화 효과

  • Park, Soon-Young (Institute of Environmental Studies, Pusan National University) ;
  • Yoo, Jung-Woo (Division of Earth Environment System, Pusan National University) ;
  • Kang, Nam-Young (National Typhoon Center, Korea Meteorological Administration) ;
  • Lee, Soon-Hwan (Department of Earth Science Education, Pusan National University)
  • Received : 2017.01.23
  • Accepted : 2017.05.12
  • Published : 2017.05.31

Abstract

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.

Keywords

References

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