31 May 2024
 | 31 May 2024
Status: this preprint is open for discussion.

A new glacier thickness and bed map for Svalbard

Ward van Pelt and Thomas Frank

Abstract. Knowledge of the thickness, volume and sub-glacial topography of glaciers is crucial for a range of glaciological, hydrological and societal issues, including, e.g., studies on climate-warming induced glacier retreat and associated sea-level rise. This is not the least true for Svalbard, one of the fastest-warming places in the world. Here, we present a new map of ice thickness and sub-glacial topography for every glacier on Svalbard. Using remotely-sensed observations of surface height, ice velocity, rate of surface elevation change, and glacier boundaries in combination with a modeled mass balance product, we apply an inverse method that leverages state-of-the-art ice flow models to obtain the shape of the glacier bed. Specifically, we model large glaciers with the Parallel Ice Sheet Model (PISM) at 500 m resolution, while we resolve smaller mountain glaciers at 100 m resolution using the physics-informed deep learning-based Instructed Glacier Model (IGM). Actively surging glaciers are modeled using a perfect-plasticity model. We find a total glacier volume (excluding Kvitøya) of 6,800 km±238 km3, and a mean ice thickness of 205±7 m. Validation against thickness observations shows high statistical agreement, and combining the three methods is found to reduce uncertainties. We discuss remaining sources of errors, differences to previous ice thickness maps of the region, and future applications of our results.

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Ward van Pelt and Thomas Frank

Status: open (until 19 Jul 2024)

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Ward van Pelt and Thomas Frank

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A new glacier thickness and bed map for Svalbard - Dataset Ward van Pelt and Thomas Frank

Ward van Pelt and Thomas Frank


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Short summary
Accurate information on the ice thickness of Svalbard’s glaciers is important for assessing the contribution to sea level rise in a present and future climate. However, direct observations of the glacier bed are scarce. Here, we use an inverse approach and high-resolution surface observations, to infer basal conditions. We present and analyze the new bed and thickness maps, quantify the ice volume (6,800 km3), and compare against radar data and previous studies.