Description: The data presented is a unique ten+ year data record obtained from in-situ measurements in steep bedrock permafrost in an Alpine environment on the Matterhorn Hörnligrat, Zermatt, Switzerland at 3500 m a.s.l. during the time period 2008-2018 by the PermaSense project. This data set 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 the past decade. 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 (code for generating, processing and validating this data set is published on Zenodo https://doi.org/10.5281/zenodo.2542715, 2019). This data set provides primary data products as well as derived data products: GNSS raw data: GNSS observables in the form of daily RINEX 2.11 files GNSS derived data products: Daily positions computed using double-differencing GNSS processing Timelapse images: High-resolution visible light images Timeseries data raw: Per-year and location files or raw sampled data: Weather station, ground temperature, ground resistivity, fracture displacement and inclinometer data Timeseries derived data products: Cleaned and aggregated hourly values of the above Timeseries sanity plots: Standardized plots to obtain a visual overview and check data All data contained in this data set including updates to newer data can also be retrieved using the toolset available at https://doi.org/10.5281/zenodo.2542715, 2019 from the online PermaSense data repository at http://data.permasense.ch.

Description: Here we provide in-situ measurements on debris cover thickness on Zmuttgletscher, Switzerland. It is one of the largest heavily debris-covered glaciers in the Alps. We further provide 2 DEMs based on UAV imagery and the respective orthophotos, as well as surface flow velocities derived from the orthophotos by automated feature tracking. Further information can be found in the research paper by Mölg et al. (2019) published in The Cryosphere.