MEG has been a major success in its first 4 years; several model problems have been noted, brought to the attention of EMC modeling teams and users of EMC models, and thoroughly investigated by model developers. Many of the problems, such as a near surface cold/wet bias in the Global Forecast System (GFS) over the eastern United States, a warm/dry bias in the summer over the Great Plains in the GFS, the initialization of the Short Range Ensemble Forecast System (SREF) and initial model snow cover, have been corrected or at least reduced in operations. MEG has also conducted thorough post-mortems of high-impact and sometimes poorly forecast events such as Superstorm Sandy, the June 2012 Ohio Valley-Mid-Atlantic derecho, and significant winter storms. Lines of communication have been opened between EMC and the National Centers, the NWS regional and local offices, and private customers to alert them of model biases and issues and to provide a forum for model users to report problems they have seen in EMC forecast systems.
The purpose of MEG is to help EMC developers improve the models by evaluating EMC models and soliciting information from users of EMC forecast systems and to provide information to users about the performance of the models and proposed model changes. During the past year MEG worked closely with other NCEP centers and NWS regional and field offices to evaluate and understand the 2016 GFS upgrade earlier in the development and implementation process and played a central role in identifying a warm, dry bias in the 2015 GFS in the summertime Great Plains and in evaluating a change in land surface parameters that significantly reduced the warm, dry bias in the 2016 GFS.
Three groups have recently been formed consisting of MEG team members and NWS Science and Operations Officers to coordinate global model evaluation, development of a high resolution ensemble and improving communications and dissemination. A visitors’ program between EMC and the NWS forecast offices is being developed.
This talk will review the successes of MEG in its first four years and current EMC forecast system problems and discuss how MEG can most effectively be expanded to provide effective constant communication between EMC model developers and model users throughout the National Weather Service and the meteorological community.