A Gaussian process subglacial drainage model emulator

«««< HEAD For this project, we constructed a fast Gaussian process emulator of the GlaDS subglacial drainage model. We explore in-depth the various architectural and experimental choices and how these impact the accuracy of the emulator. Using the emulator, which makes predictions about 1000x faster than the physics-based model, we evaluate the model’s sensitivity to eight parameters, highlighting that ~90% of the variance in model outputs is described by three of the parameters. Read the paper in GMD for more! ======= For this project, we constructed a fast Gaussian process emulator of the GlaDS subglacial drainage model. We explore in-depth the various architectural and experimental choices and how these impact the accuracy of the emulator. Using the emulator, which makes predictions about 1000x faster than the physics-based model, we evaluate the model’s sensitivity to eight parameters, highlighting that ~90% of the variance in model outputs is described by three of the parameters. Read the paper for more!

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Citation

«««< HEAD Hill, T., Bingham, D., Flowers, G. E., Hoffman, M. J. (2024). Computationally Efficient Subglacial Drainage Modeling Using Gaussian Process Emulators: GlaDS-GP v1.0. Geoscientific Model Development, 18, 4045-4074 https://doi.org/10.5194/gmd-18-4045-2025 ======= Hill, T., Bingham, D., Flowers, G. E., Hoffman, M. J. (2025). Computationally Efficient Subglacial Drainage Modeling Using Gaussian Process Emulators. Geoscientific Model Development, 18, 4045-4074. https://doi.org/10.5194/gmd-18-4045-2025

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