Objective
The Israeli Air Force (IAF) has been sponsoring NCAR to construct a state-of-the-art numerical weather prediction system to improve its weather forecast support through development and applications of new technologies.
Description
The NWP system is based on RAL's Real-Time Four-Dimensional Data Assimilation (RTFDDA) system, which uses the community Weather Research and Forecasting (WRF) model as its core engine. The geographical area of interest for the modeling system is primarily over the Middle-East, where there are sparse conventional weather observation networks. To mitigate the adverse effect of inadequate weather reports on the NWP performance, the RAL research team has developed a new capability and added to its existing RTFDDA system. This new, key feature takes advantage of the vast amount of satellite radiances, which are processed through the WRF 3DVAR initialization, which is then coupled with RTFDDA's conventional observational nudging to complete a new hybrid data assimilation system, dubbed MAGEN (Model for Advanced GENeration of 4-D weather). The MAGEN system also takes advantage of the Atmospheric Motion Vectors (AMV) data from satellite retrievals. The RAL team has dedicated a great effort in the AMV data quality control and assimilation strategies.
On the technology front, the IAF MAGEN project showcases the advanced web portal technology, which is applied to provide the IAF a web interface that is easy to navigate for the purpose of starting/stopping a model run, as well as viewing the MAGEN modeling system products.
