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Development of a innovative estimation algorithm for cloud and precipitation particles over land utilising satellite observation

In order to effectively prepare for weather-related natural disasters, accurate estimations of cloud and rainfall are required. Assistant Professor Rie Seto, Tokyo Institute of Technology, Japan, is leading a team that is developing a method for acquiring and assimilating terrestrial
 cloud and precipitation data from satellite microwave observations. The hope is that this new methodology could help realise optimal regional water management. In their development of the methodology, Seto and the team focused on the importance of accurately representing the land surface as
 well as assimilation of the atmosphere. Ultimately, Seto wants to produce high-quality data that can be used to gain improved understanding of cloud and precipitation events and enable more precise calculations to predict where and how much rain will fall. Due to the heterogeneous structure
 of clouds, the researchers are considering cloud volume and how the different types of individual particles can be estimated, along with the distribution of particles in the cloud. Seto and the team are also working to perform uncertainty propagation analysis of hydrological forecasts with
 a view to helping reduce flood damage and assist in the operation of reservoirs used for water utilisation. Seto also keeps an eye on the applicability of microsatellites.