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  1. 213901

    TIE‐GCM ROPE ‐ Dimensionality Reduction: Part I by Piyush M. Mehta, Richard J. Licata

    Published 2025-01-01
    “…This work focuses on the dimensionality reduction step of the ROPE development process and addresses three limitations of the proof‐of‐concept: (a) extending the altitude upper boundary from 450 km to nearly 1000 km, (b) employing deep learning for nonlinear dimensionality reduction over principal component analysis (PCA) for improved performance during storm periods, and (c) maintaining the spatial resolution of the physical TIE‐GCM model, without down‐sampling, to preserve the spatial scales and variations. …”
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