9.2 The global Ensemble Kalman Filter (EnKF) analysis for the Model for Prediction Across Scales (MPAS) on the variable-resolution meshes

Ha, Soyoung, Chris Snyder, and Bill Skamarock, National Center for Atmospheric Research/Mesoscale and Microscale Meteorology Laboratory

The Data Assimilation Research Testbed (DART) has been recently coupled to the nonhydrostatic MPAS global model using the model's unstructured mesh to take advantage of its variable-resolution capability for global numerical weather prediction (NWP) applications. With the assimilation of real observations for a month-long cycling period of June 2012, it is demonstrated that the global ensemble analyses and forecasts on the MPAS variable-resolution meshes are reliable and robust throughout the cycles and beneficial compared to the ones over the coarse uniform meshes in the local refinement area. The benefit of the variable-resolution mesh is discussed in various metrics including Fractions Skill Scores (FSS), which lasts up to 5-day forecasts from the EnKF mean analysis.