Impacts of Assimilating Vertical Velocity, Latent Heating, or Hydrometeor Water Contents Retrieved From a Single Reflectivity Data Set Journal of Geophysical Research: Atmospheres

Assimilation of observation data in cloudy regions has been challenging due to the unknown properties of clouds such as cloud depth or cloud drop size distributions (DSD). Attempts to assimilate data in cloudy regions generally assume a DSD, but most assimilation systems fail to maintain consistencybetween models and the observation data, as each has its own set of assumptions. This study tries to retain the consistency between the forecast model and the retrieved data by developing a Bayesian retrieval scheme that uses the forecast model itself for the a priori database. Through the retrieval algorithm, verticalprofiles of three variables related to the development of tropical cyclones, including vertical velocity (VV), latent heating (LH), and hydrometeor water contents (HYDRO), are derived from the same re flectivity observation. Each retrieved variable is assimilated in the data assimilation system using a flow-dependent Grant no. NA14OAR4830122