抄録
Cloud Microphysics Data Assimilation System (CMDAS) was developed to improve water vapor and cloud liquid water content in numerical weather prediction model by assimilating brightness temperature data observed by satellite-mounted microwave radiometer. In the optimization scheme in CMDAS, cloud bottom height (CBH) information is used to define vertical profiles of water vapor and cloud liquid water content which are necessary in a microphysics parameterization scheme. Cloud bottom height varies with atmospheric conditions, however, a constant value is used in CMDAS. In this study, effects of different CBHs on assimilation and numerical weather prediction with assimilated initial conditions are examined.
