ALBERT

Beschreibung: The present dataset is the basis for the article from Marcer et al. (in review) "Rock glaciers throughout the French Alps accelerated and destabilised since 1990 as air temperatures increased". The dataset describes displacement rates and destabilisation for all the rock glaciers in the region of the French Alps during the years 1945-2018. The methodology used is manual feature tracking of moving boulders on rock glaciers surfaces observed on time lapsed orthoimagery. Most of the orthoimagery we used is already made freely accessible by the the French National Institute of Geography (IGN) through the online portal www.geoportail.com. We computed additional orthoimages on landforms of particular interest, i.e. presenting destabilisation evidence. In this dataset we provide raw feature tracking observations, measured displacement rates and additional orthoimages we computed. All geodata are readable on a GIS software and referenced in EPSG:2154. Other data are provided as CSV spreadsheets.

Beschreibung: This dataset collates data of continuously acquired kinematic observations obtained through in-situ Global Navigation Satellite Systems (GNSS) instruments that have been designed and implemented in a large-scale multi field-site monitoring campaign across the whole Swiss Alps. The landforms covered include rock glaciers, high-alpine steep bedrock bedrock as well as landslide sites, most of which are situated in permafrost areas. The dataset was acquired at 54 different stations situated at locations from 2304 to 4003 meter a.s.l and comprises 209'948 daily positions derived through double-differential GNSS post-processing. Apart from these, the dataset contains down-sampled and cleaned time series of weather station and inclinometer data as well as the full set of GNSS observables in RINEX format. Furthermore the dataset is accompanied by tools for processing and data management in order to facilitate reuse, open alternate usage opportunities and support the life-long living data process with updates.

Beschreibung: This dataset collates data of continuously acquired kinematic observations obtained through in-situ Global Navigation Satellite Systems (GNSS) instruments that have been designed and implemented in a large-scale multi field-site monitoring campaign across the whole Swiss Alps. The landforms covered include rock glaciers, high-alpine steep bedrock bedrock as well as landslide sites, most of which are situated in permafrost areas. The dataset was acquired at 54 different stations situated at locations from 2304 to 4003 meter a.s.l and comprises 229'669 daily positions derived through double-differential GNSS post-processing. Apart from these, the dataset contains down-sampled and cleaned time series of weather station and inclinometer data as well as the full set of GNSS observables in RINEX format. Furthermore the dataset is accompanied by tools for processing and data management in order to facilitate reuse, open alternate usage opportunities and support the life-long living data process with updates. All data contained in this data set including updates to newer data can also be retrieved using the toolset available at https://git.uibk.ac.at/informatik/neslab/public/permasense/permasense_datamgr from the online PermaSense data repository at http://data.permasense.ch.

Beschreibung: 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 2008-2021 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 154.1 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. 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://gitlab.ethz.ch/tec/public/permasense/permasense_datamgr from the online PermaSense data repository at http://data.permasense.ch. The version/tag used for the 2022 edition of the Matterhorn data is https://gitlab.ethz.ch/tec/public/permasense/permasense_datamgr/tree/matterhorn_data_2022.

Beschreibung: In recent years, observations have highlighted seasonal and interannual variability in rock glacier flow. Temperature forcing, through heat conduction, has been proposed as one of the key processes to explain these variations in kinematics. However, this mechanism has not yet been quantitatively assessed against real-world data. We present a 1-D numerical modelling approach that couples heat conduction to an empirically derived creep model for ice-rich frozen soils. We use this model to investigate the effect of thermal heat conduction on seasonal and interannual variability in rock glacier flow velocity. We compare the model results with borehole temperature data and surface velocity measurements from the PERMOS and PermaSense monitoring network available for the Swiss Alps. We further conduct a model sensitivity analysis in order to resolve the importance of the different model parameters. Using the prescribed empirically derived rheology and observed near-surface temperatures, we are able to model the correct order of magnitude of creep. However, both interannual and seasonal variability are underestimated by an order of magnitude, implying that heat conduction alone cannot explain the observed variations. Therefore, we conclude that non-conductive processes, likely linked to water availability, must dominate the short-term velocity signal.

Beschreibung: In recent years, observations have highlighted seasonal and inter-annual variability in rockglacier flow. Temperature forcing, through heat conduction, has been proposed as one of the key processes to explain these variations in kinematics. However, this mechanism has not yet been quantitatively assessed against real-world data. We present a 1-D numerical modelling approach that couples heat conduction to an empirically derived creep model for ice-rich frozen soils. We use this model to investigate the effect of thermal heat conduction on seasonal and inter-annual variability in rockglacier flow. We compare the model results with borehole temperature data and surface velocity measurements from the PERMOS and PermaSense monitoring network in the Swiss Alps. We further conduct a model sensitivity analysis in order to resolve the importance of the different model parameters. Using the prescribed empirically derived rheology and observed near-surface temperatures, we are able to model the right order of magnitude of creep flow. However, both inter-annual and seasonal variability are underestimated by an order of magnitude, implying that heat conduction alone can not explain the observed variations. Therefore, non-conductive processes, likely linked to water availability, dominate the short-term velocity signal.