04 Apr 2023
 | 04 Apr 2023
Status: this preprint is currently under review for the journal TC.

Reconciling ice dynamics and bed topography with a versatile and fast ice thickness inversion

Thomas Frank, Ward J. J. van Pelt, and Jack Kohler

Abstract. 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.

Thomas Frank et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2023-43', Samuel Cook, 06 Apr 2023
  • RC2: 'Comment on tc-2023-43', Anonymous Referee #2, 17 Apr 2023

Thomas Frank et al.

Thomas Frank et al.


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Short summary
Since the ice thickness of most glaciers world-wide is unknown, and since it is not feasible to visit every glacier and observe their thickness directly, inverse modelling techniques are needed that can calculate ice thickness from abundant surface observations. Here, we present a new method for doing that. Our methodology relies on modelling the rate of surface elevation change for a given glacier, compare this with observations of the same quantity and change the bed until the two are in line.