Optimization of the Vertical Localization Scale for GPS-RO Data Assimilation within KIAPS-LETKF System

Korea Institute of Atmospheric Prediction System (KIAPS) has been developing a global numerial prediction model and data assimilation system. We has implemented LETKF (Local Ensemble Transform Kalman Filter, Hunt et al., 2007) data assimilation system to NCAR CAM-SE (National Center for Atmospheric Research Community Atmosphere Model with Spectral Element dynamical core, Dennis et al., 2012) that has cubed-sphere grid, known as the same grid system of KIAPS Integrated Model (KIM) now developing. In this study, we have assimilated Global Positioning System Radio Occultation (GPS-RO) bending angle measurements in addition to conventional data within ensemble-based data assimilation system. Before assimilating bending angle data, we performed a vertical unit conversion. The information of vertical localization for GPS-RO data is given by the unit of meter, but the vertical localization method in the LETKF system is based on pressure unit. Therefore, with a clever conversion of the vertical information, we have conducted experiments to search for the best vertical localization scale on GPS-RO data under the Observing System Simulation Experiments (OSSEs). As a result, we found the optimal setting of vertical localization for the GPSRO bending angle data assimilation. We plan to apply the selected localization strategy to the LETKF system implemented to KIM which is expected to give better analysis of GPS-RO data assimilation due to much higher model top.