Tuesday, 24 January 2017
4E (Washington State Convention Center )
A wide spectrum of numerical weather prediction (NWP) innovations are under development in the research community. These new, cutting-edge developments often have the potential to positively impact operational models; however, the path from research to operations (R2O) is often arduous. The Developmental Testbed Center (DTC) continues to play a pivotal role in helping facilitate the transition of NWP advancements from R2O. In order to better assist the research community with efficiently demonstrating the merits of new NWP developments, the Mesoscale Model Evaluation Testbed (MMET) was established to provide a common testing framework. MMET provides initialization and observation data sets, configuration files, and scripts to help the research community test and evaluate a number of routine and high-impact cases. MMET also provides baseline results for select operational models that can be utilized to diagnose forecast improvement/degradation in the new NWP innovations. This presentation will describe the components of MMET and highlight how the NWP community can engage in the use of MMET. In addition, recent capabilities to run components of the end-to-end modeling system through the use of Docker containers allow users to quickly produce output without being delayed by technical issues. A brief motivation for using Docker containers to run MMET cases will be included.
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