Preprints
https://doi.org/10.5194/egusphere-2023-473
https://doi.org/10.5194/egusphere-2023-473
18 Apr 2023
 | 18 Apr 2023
Status: this preprint is open for discussion.

Brief communication: Measuring and modelling the ice thickness of the Grigoriev ice cap (Kyrgyzstan) and comparison with global datasets

Lander Van Tricht, Chloë Marie Paice, Oleg Rybak, and Philippe Huybrechts

Abstract. An accurate ice thickness distribution is crucial for correct projections of the future state of an ice mass. However, measuring the ice thickness with an in-situ system is time-consuming and not scalable. Therefore, models have been developed that estimate the ice thickness without direct measurements. In this study, we reconstruct the ice thickness of the Grigoriev ice cap, Kyrgyzstan, from in-situ observations and the yield stress method. We compare the results with data from 6 global ice thickness datasets composed without the use of our local measurements. The results highlight shortcomings of these generic datasets and demonstrate the importance of local observations for accurate representations of the ice thickness.

Lander Van Tricht et al.

Status: open (until 06 Jul 2023)

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Lander Van Tricht et al.

Data sets

Measurements and datasets of the ice thickness of the Grigoriev ice cap Lander Van Tricht https://zenodo.org/badge/latestdoi/614248752

Lander Van Tricht et al.

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Short summary
We performed a field campaign to measure the ice thickness of the Grigoriev ice cap (Central Asia). We interpolated the ice thickness data to obtain an ice thickness distribution representing the state of the ice cap in 2021, with a total volume of ca. 0.4 km3. We then compared our results with global ice thickness datasets composed without our local measurements. The main take-away hereof is that these datasets do not perform well enough yet for ice caps such as the Grigoriev ice cap.