A decade of detailed observations (2008–2018) in steep bedrock permafrost at Matterhorn Hörnligrat (Zermatt, CH)
The PermaSense project is an ongoing interdisciplinary effort between geo-science and engineering disciplines started in 2006 with the goals to make observations possible that previously have not been possible. Specifically the aims are to obtain measurements data in unprecedented quantity and quali...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Report |
| Language: | English |
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Copernicus
2019
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| Subjects: | |
| Online Access: | https://hdl.handle.net/20.500.11850/323342 https://doi.org/10.3929/ethz-b-000323342 |
| Summary: | The PermaSense project is an ongoing interdisciplinary effort between geo-science and engineering disciplines started in 2006 with the goals to make observations possible that previously have not been possible. Specifically the aims are to obtain measurements data in unprecedented quantity and quality based on technological advances. This paper describes a unique ten+ year data record obtained from in-situ measurements in steep bedrock permafrost in an Alpine environment 5 on the Matterhorn Hörnligrat, Zermatt Switzerland at 3500 m a.s.l. Through the utilization of state-of-the-art wireless sensor technology it was possible to obtain more data of higher quality, make this data available in near real-time and tightly monitor and control the running experiments. This data set (DOI: doi.pangaea.de/10.1594/PANGAEA.897640, Weber et al., 2019a) constitutes the longest, densest and most diverse data record in the history of mountain permafrost research worldwide with 17 different sensor types used at 29 distinct sensor locations consisting of over 114.5 million data points captured over a period 10 of ten+ years. By documenting and sharing this data in this form we contribute to making our past research reproducible and facilitate future research based on this data e.g. in the area of analysis methodology, comparative studies, assessment of change in the environment, natural hazard warning and the development of process models. ISSN:1866-3591 |
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