Handling Hydrometeor-impacted Satellite Data in an Inversion and Data Assimilation System by Accounting for Optical Properties

Satellite data assimilation is one of the major forces to drive the progress of modern weather prediction. In recent two decades, the observation from spaceborne instruments has increased dramatically, though the utilization of these data is mostly confined to the clear sky condition due to the difficulty in the parameterization of cloud, precipitation and associated optical properties. Nevertheless, assimilation of the observations in cloudy condition is kept being pursued by major NWP centers for it profound potential impact on the improvement of weather forecasting. In this study, in order to circumvent the uncertainties caused by the assumptions in cloud particle size distribution and the shape of individual ice particles and other microphysical properties, we added the cloud optical properties to replace the cloud physical properties in the state variable vector of the MIIDAPS 1DVar preprocessing system, with the aim of obtaining more accurate temperature and water vapor profiles in cloudy and precipitating conditions, as the information about these profiles are the key factors for forecasting beyond 24 hours. Detailed implementation method and preliminary results will be presented, and future development will be discussed.