[ACG51-18] Ensemble-Based Data Assimilation of GPM/DPR Reflectivity into the Nonhydrostatic Icosahedral Atmospheric Model NICAM
Keywords:GPM DPR, NICAM-LETKF, Data Assimilation, Cloud Microphysics
This study pioneers to assimilate radar reflectivity measured by the Dual-frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM) core satellite into the NICAM. We conduct the NICAM-LETKF experiments at 28-km horizontal resolution with explicit cloud microphysics of a single-moment 6-class bulk microphysics scheme. To simulate GPM/DPR reflectivity from NICAM model outputs, the Joint-Simulator (Hashino et al. 2013; JGR) is used. Our initial tests showed a better match with the observed reflectivity by assimilating GPM/DPR reflectivity into NICAM forecasts. However, the results from a 1-month data assimilation cycle experiment showed general degradation by assimilating GPM/DPR reflectivity. For better use of GPM/DPR reflectivity data, we are exploring to estimate model cloud physics parameters for terminal velocity by data assimilation. Parameter sensitivity experiments revealed that using a parameter of slower snowfall made contoured frequency by altitude diagrams (CFADs) closer to GPM/DPR observations. The parameter of slower snowfall also improved temperature and humidity fields in the mid- to lower troposphere. This presentation will include the most recent progress up to the time of the conference.