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Maximizing Ensemble Forecasting Performance: Strategies and Future Trends

Explore optimal configurations, testing processes, computational resource optimization, and future trends in ensemble forecasting. Delve into probabilistic guidance development, visualization tools, and collaboration between EMC and downstream users for enhanced forecasting accuracy. Investigate the role of virtual labs, cloud technologies, and the evolution of ensemble systems.

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Maximizing Ensemble Forecasting Performance: Strategies and Future Trends

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  1. Discussion: Ensemble System Configuration (Hogsett/Bright) • How to determine the optimal configuration (resolution, size, ICs/LBCs, physics, etc.)? • Testing by EMC, DTC, and/or research community? • How to optimize use of computational resources? • Global, mesoscale, and cloud-permitting ensembles? • Time-lagged ensembles? • Future of multi-center ensembles? • New “NAEFS” including ECMWF ensemble?

  2. Discussion: Ensemble Forecasting and Probabilistic Guidance (Hogsett/Jirak) • How do we make best use of ensemble guidance? • NDFD remains deterministic • Ensemble visualization tools are underdeveloped • Filling the training gap for ensemble-based DSS • Division of labor between EMC and downstream users for probabilistic guidance development. • Is there a dividing line? • How to avoid duplication of effort? • Do users prioritize a high-quality underlying system or advanced post-processed products? • Role of virtual labs and cloud for development and data dissemination?

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