Articles | Volume 32, issue 3
https://doi.org/10.5194/npg-32-293-2025
https://doi.org/10.5194/npg-32-293-2025
Research article
 | 
08 Sep 2025
Research article |  | 08 Sep 2025

Ensemble-based model predictive control using data assimilation techniques

Kenta Kurosawa, Atsushi Okazaki, Fumitoshi Kawasaki, and Shunji Kotsuki

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Short summary
We propose ensemble-based model predictive control (EnMPC), a novel method that improves the control of complex systems like the atmosphere by integrating control theory with data assimilation. Unlike traditional methods, which are computationally expensive, EnMPC uses ensemble simulations to efficiently handle uncertainties and optimize solutions. This approach reduces computational cost while maintaining accuracy, making it a promising step toward real-world applications in dynamic system control.
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