Convective-scale ensemble data assimilation using unstructured meshes

In an effort to enhance storm-scale data assimilation and prediction, we have recently updated the atmospheric Model for Prediction Across Scales (MPAS-A; Skamarock et al. 2012), coupled to the Ensemble Kalman Filter (EnKF) Data Assimilation Research Testbed (DART) system (Ha et al., 2017), for regional analysis using variable-resolution capabilities. In this talk, we will introduce unique features of the interface, leveraging the model's native coordinate both horizontally (e.g., unstructured meshes) and vertically (e.g., terrain-following height), and demonstrate its suitability for storm-scale DA. As its robustness was demonstrated in the U. S. National Severe Storms Laboratory (NSSL)'s Warn-On-Forecast framework during tornado watches in 2024, the performance of regional ensemble analysis incorporating storm-scale data assimilation using radars and cloud water path from the GOES-R satellite will be presented.