Data Assimilation Seminar
Prof. Shunji Kotsuki (10:00 - 11:30 March 4, 2025)
Affiliation | Chiba University, Japan / RIKEN, R-CCS |
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Title | Combining ensemble data assimilation with AI-based Weather Prediction Model |
Abstract |
Artificial intelligence (AI)-based weather prediction research is growing rapidly and has shown to be competitive with the advanced dynamic numerical weather prediction models. However, research combining AI-based weather prediction models with data assimilation remains limited partially because long-term sequential data assimilation cycles are required to evaluate data assimilation systems. This study explores integrating the local ensemble transform Kalman filter (LETKF) with an AI-based weather prediction model ClimaX. Our experiments demonstrated that the ensemble data assimilation cycled stably for the AI-based weather prediction model using covariance inflation and localization techniques inside the LETKF. While ClimaX showed some limitations in capturing flow-dependent error covariance compared to dynamical models, the AI-based ensemble forecasts provided reasonable and beneficial error covariance in sparsely observed regions. This seminar talk also includes our recent studies coupling AI and data assimilation, such as generative-AI-based latent-space data assimilation. |