Sample and Modelling Data for Cosmogenic 10Be in Medial Moraine Debris of Glacier d’Otemma, Switzerland
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This data publication is supplementary to the study on headwall erosion rates at Glacier d'Otemma in Switzerland, by Wetterauer et al. (2022). Debris on glacier surfaces stems from steep bedrock hillslopes that tower above the ice, so-called headwalls. Recently, rock walls in high-alpine glacial environments experience increased destabilization due to climate warming. Since supraglacial debris alters the melt behaviour of the ice underneath, increased headwall erosion and debris delivery to glacier surfaces will modify glacial mass balances. Therefore, we expect that the response of glaciers to climate change is likely linked to how headwall erosion responds to climate change. As headwall debris is deposited on the ice surface of valley glaciers it is passively transported downglacier, both supra- and englacially. Where two glaciers join, debris along their margins is merged to form medial moraines. Since medial moraine debris tends to be older downglacier, systematic downglacier-sampling of medial moraine debris and the measurement of in situ-produced cosmogenic 10Be concentrations ([10Be]) hold the potential to assess long-term (>10^2-10^4 yrs) headwall erosion rates through time. However, to obtain the cosmogenic signals of headwall erosion, [10Be] within supraglacial debris need to be corrected for glacial transport time, as cosmogenic nuclides continue to accumulate during exposure and transport. This additional 10Be accumulation during debris transport can be accounted for by simple downglacier debris trajectory modelling. Providing our 10Be dataset together with detailed information on our 1-D modelling approach is the main objective of this data publication. The data is presented as one single xlsx-file with three different tables. A detailed description of the sample processing and the debris trajectory model are provided in the data description file of this data publication. For more information see our study Wetterauer et al. (2022).
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GFZ Data Services
创建时间:
2022-04-15



