Performance of KIAPS-LETKF data assimilation system

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Tuesday, 6 January 2015: 11:00 AM
131AB (Phoenix Convention Center - West and North Buildings)
Ji-Sun Kang, KIAPS, Seoul, Korea; and B. J. Jung, Y. Jo, S. Shin, J. H. Kim, H. W. Chun, and H. Kwon

Korea Institute of Atmospheric Prediction Systems (KIAPS) has successfully implemented Local Ensemble Transform Kalman Filter (LETKF; Hunt et al. 2007) data assimilation system to KIAPS-GM (Global Model) which has fully unstructured quadrilateral meshes based on the cubed-sphere grid that has a strong advantage on the flexibility and scalability in the future high performance computing environment without any singularity. Following a successful evaluation of KIAPS-LETKF data assimilation system with various OSSEs, assimilation of real observations has been performed. As a preliminary experiment, we have assimilated surface and radiosonde observations from NCEP preprocessed data, AMSU-A, IASI, and GPS RO data preprocessed by KPOP (KIAPS Package for Observation Processing), for a month of November 2012. Also, several vertical localization strategies will be evaluated for radiance observations with RTTOV as a forward operator. We will present a current state of KIAPS-LETKF data assimilation system with real observations, and discuss how we further improve the system.