R-CCS Cafe 第219回 第1部

The Dual-frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM) core satellite has been providing valuable information about the global precipitation since its operations in 2014. DPR is a satellite-borne phase-array radar that can provide a 3D structure of precipitation events with fine spatial resolution of about 5 km in the horizontal and 250 m in the vertical. To understand its value in aiding global precipitation forecast, we implemented the capability to directly assimilate DPR reflectivity into a global data assimilation system that couples the Non-hydrostatic Icosahedral Atmospheric Model (NICAM) with the Local Ensemble Transform Kalman Filter (LETKF), namely the NICAM-LETKF. To address the representativeness error, we superobbed the DPR reflectivity profiles onto the NICAM grid, which is configured at grid-level 8 with an equivalent grid spacing of 28 km. Before the direct assimilation, a one-month evaluation experiment is carried out to study the performance of the NICAM-LETKF system on simulating DPR reflectivity using the Joint Simulator as the observation operator. The observation minus first guess (OmG) statistics are examined to understand the bias and its sources. In this talk, I will present results from the evaluation experiment and discuss plans toward direct assimilation of DPR reflectivity into the NICAM-LETKF system.