Reconciling ice dynamics and bed topography with a versatile and fast ice thickness inversion
We present a novel thickness inversion approach that leverages globally available satellite products and state-of-the-art ice flow models to produce distributed maps of subglacial topography independent of bed observations. While the method can use any complexity of ice physics as represented in ice...
| Main Authors: | , , |
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| Format: | Text |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://doi.org/10.5194/tc-2023-43 https://tc.copernicus.org/preprints/tc-2023-43/ |
| Summary: | We present a novel thickness inversion approach that leverages globally available satellite products and state-of-the-art ice flow models to produce distributed maps of subglacial topography independent of bed observations. While the method can use any complexity of ice physics as represented in ice dynamical models, it is computationally cheap, enabling applications both on local and large scales. Using the mismatch between observed and modelled rates of surface elevation change ( dh / dt ) as the misfit functional, iterative pointwise updates to an initial guess of bed topography are made, while mismatches between observed and modelled velocities are used to simultaneously infer basal friction. The final product of the inversion is not only a map of ice thickness, but a fully spun-up glacier model representing the dynamic state of a given glacier. We here present the method, and use an artificial ice-cap built inside a numerical model to test it and conduct sensitivity experiments. Even under a range of perturbations, the method is stable and fast. Finally, we apply the approach to the tidewater glacier Kronebreen on Svalbard. Ultimately, our method shown here represents a fast way of inferring ice thickness where the final output forms a consistent picture of model physics, input observations and bed topography. |
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