Brief communication: Measuring and modelling the ice thickness of the Grigoriev ice cap (Kyrgyzstan) and comparison with global datasets
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 to estimate the ice thickness without direct measurement...
Published in: | The Cryosphere |
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Main Authors: | , , , |
Format: | Text |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | https://doi.org/10.5194/tc-17-4315-2023 https://tc.copernicus.org/articles/17/4315/2023/ |
Summary: | 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 to 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 six global ice thickness datasets composed without the use of our local measurements. The results highlight the limitations of these generic datasets primarily stemming from the subdivision of ice caps into distinct glaciers, the adoption of a (calibrated) creep parameter value, assumptions regarding ice mass flux, and errors regarding surface velocity observations. These shortcomings emphasize the importance of integrating local observations to calibrate models to achieve precise representations of ice thickness, particularly when dealing with smaller or slow-flowing cold ice caps, such as the Grigoriev ice cap. |
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