| 08 Oct 2025
Ice thickness of Comox and Kokanee Glaciers, British Columbia, determined through relative gravity surveys
Abstract. Ice thickness data are sparse or lacking for many glaciers worldwide, making it difficult to track changes in ice volume due to ongoing climate change. In this study, we collect and model relative gravity survey data, to provide the first estimate of ice thickness for the retreating Comox Glacier, a historically important source of freshwater for eastern Vancouver Island, British Columbia. We validate our approach by carrying out a similar analysis across the Kokanee Glacier, for comparison with recent ice penetrating radar results. Modelling of the Bouguer gravity anomaly across each glacier provides an average inferred ice thickness of 42 ± 4 m across a 450 m transect of Comox Glacier, and 50 ± 3 m across a 220 m transect of Kokanee Glacier, consistent with previous measurements. Future repeat surveys will enable monitoring of ice thickness changes over time. Compared to other methods, gravity surveying offers a lower cost and logistically simpler alternative for the collection of ice thickness data on glaciers worldwide.
This manuscript presents an interesting and clearly written study applying gravimetric methods to estimate glacier ice thickness. The approach is generally well explained, and the results appear reasonable. The paper is concise and direct, which is appreciated. However, I find that the manuscript is currently too limited in scientific depth to warrant publication in its present form. With targeted additions, it has the potential to become a valuable contribution.
To increase scientific relevance, I recommend strengthening the manuscript by expanding the analysis beyond the current two-site application. Options could include adding a comparison with existing model-derived ice thickness estimates (e.g., those from Farinotti et al.) to contextualize their results. Given that Comox Glacier (e.g., GLIMS ID G234649E49550N; RGI ID RGI2000-v7.0-G-02-07858) is likely included in global modelling datasets, this comparison could help quantify the method’s performance and assess any bias. For example, if the measured thickness is much lower than estimated by other modelling approaches, what are the implications for retreat and disappearance of this glacier (which can also be obtained from global estimates such as Rounce et al., 2023)? Additionally, incorporating a discussion of methodological uncertainty (is the varying density of crevasses/melt pockets likely to cause a big shift in the results? Is the grid size a big influence?), including potential sources of divergence between gravimetric and radar measurements and whether measurement year might influence results, would significantly enhance the scientific contribution. These are just initial thoughts on how this manuscript would be expanded, but I am certain there are other avenues as well.
Minor comments
Please include the GLIMS and/or RGI glacier identifiers in the study site description to facilitate spatial reference.
In the introduction, the Scott citation focuses on the Hindu Kush region only; consider incorporating a broader reference such as Viviroli et al. (2020) for global or multi-mountain context.
Figure 4: clarify the distinction between your measurements and those from Pelto (2020) in the figure itself, not just the caption.
References:
Viviroli, D., Kummu, M., Meybeck, M., Kallio, M. & Wada, Y. (2020). Increasing dependence of lowland populations on mountain water resources. Nature Sustainability, 3(11), 917–928. https://doi.org/10.1038/s41893-020-0559-9
Rounce, D. R., et al. (2023). Global glacier change in the 21st century: Every increase in temperature matters. Science, 379(6627), 78-83.