- 1School of Geosciences, University of Aberdeen, Aberdeen, United Kingdom
- 2School of Natural and Built Environment, Queen's University Belfast, Belfast, United Kingdom
Extensive databases of satellite imagery are now available and can be used to undertake assessments of the mass balance of glaciers. Previous studies have mapped the end-of-season snowlines (ESS) on glaciers from satellite imagery to find their snowline altitudes (SLA) and used these as proxies for the glacier equilibrium-li ne altitudes (ELA). This approach is advantageous because it can be implemented at a large scale and may employ automated methods. The veracity of using remotely measured SLAs as a proxy for in-situ measured ELAs however, has not yet been robustly demonstrated.
We have undertaken a systematic mapping of ESSs on 20 glaciers with existing measured mass balance records to determine the errors associated with remotely measured SLAs. Glaciers are selected from the World Glacier Monitoring Service (WGMS) Fluctuations of Glacier (FoG) database. For each ELA record, we identify the Landsat image closest in date to the original ELA measurement (where cloud cover is minimal) and the image with the highest altitude snowline for the year. For each image, the snowline is mapped, and its corresponding SLA is extracted from the ASTER Global Digital Elevation Map (ASTERGDEM). We find that the reliability of this method is variable, as it is often limited by satellite revisit periods, cloud cover, and late-summer snowfall events. We specifically investigate further the complexities associated with distilling the range of elevation values comprising a mapped snowline into a single elevation value, for example, taking the mean and median elevations along the full width of the glacier and within a fixed buffer of the central flowline and the effect patchy and irregular snowline segments might have on the calculations. Where snow cover is patchy, a greater length of snowline is mapped in order to trace the boundary than is required for smoother segments. This is regardless of whether it contributes a larger area of snow cover or not. Consequently, the SLA calculations are prone to oversampling from areas of irregular snow cover. These results highlight a need to better define the end-of-season SLA and how best to calculate it.
How to cite: Hallford, M., Rea, B. R., Mullan, D., Spagnolo, M., Sam, L., and Singh, S.: Complexities of Using Satellite Imagery for Defining Snowline Altitudes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19578, https://doi.org/10.5194/egusphere-egu25-19578, 2025.
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