Objective

The project sponsored by DTRA is to enhance the capability of FDDA in the Community WRF model by implementing observational and analysis nudging data assimilation, then to establish a complete multi–scale end–to–end FDDA system. In addition, advanced hybrid data assimilation techniques will be explored to assimilate hydro–meteorological fields.

Description

Data assimilation has become an integral component of the community WRF model. The continuous observational nudging FDDA has advantages of efficiency and accuracy over other DA techniques, particularly within the atmospheric boundary layer, and for real–time operations. In response to community needs, new nudging algorithms developed at NCAR and The Pennsylvania State University, which have been well tested with MM5, will be implemented into the community WRF model. The new WRF FDDA system has the goal of establishing a complete multi–scale, end–to–end mesoscale modeling system. The process starts with data decoding, preprocessing and quality control. This is followed by an objective analysis process to produce the data sets for observational and grid nudging. The WRF model is then run with FDDA to produce the model initial conditions. After the model simulation, post–processing and verification take place. The system will undergo extensive testing on selected real-data cases, and will be released to the community as a part of the WRF releases. The project will also explore advanced hybrid data assimilation techniques to assimilate hydrometeorological fields.