Four dimensional variational assimilation of Microwave Remote-sensing data for a Baiu frontal case in 1999.

The Baiu front is a sub-tropical convergence zone that is formed over East Asia in early summer. Meso-scale ( 200 km) precipitation disturbances around the Baiu front often cause very heavy rainfall events (> 100 mm/day). Because of the coarser resolution (500km) of the operational sonde network, it is difficult to resolve those disturbances with the operational observation system. Recent development in microwave remote-sensing technology has provided us with new types of ground-based observations (radar, GPS, wind profilers) and space-based observations (microwave radiometers and radar) that are available even in cloudy areas. As the advanced technique to assimilate those new, asynoptic data sets into MM5, a four-dimensional variational data assimilation (4DVAR) method has been developed by NCAR. The purpose of this study is to retrieve the meso-scale evolution of water vapor and related circulation for a Baiu frontal case in July 1999, using the microwave remote-sensing data (GPS, satellite microwave radiometers, radar, and wind profilers) in addition to the operational data. To this end, we use the MM5 4DVAR system with horizontal resolution of 30 km. To see data impacts, we execute some experiments, in which one of the remote-sensing data sets is excluded. Impacts of changes in temporal and spatial resolutions of the remote-sensing data are also examined.