11 Jun 2021

11 Jun 2021

Review status: this preprint is currently under review for the journal ESSD.

Kinematic observations of the mountain cryosphere using in-situ GNSS instruments

Jan Beutel1,2, Andreas Biri2, Ben Buchli2, Alessandro Cicoira3,4, Reynald Delaloye4, Reto Da Forno2, Isabelle Gaertner-Roer3, Stephan Gruber5, Tonio Gsell2, Andreas Hasler6, Roman Lim2, Phillipe Limpach7, Raphael Mayoraz8, Matthias Meyer2, Jeannette Noetzli9, Marcia Phillips9, Eric Pointner10, Hugo Raetzo11, Cristian Scapoza12, Tazio Strozzi13, Lothar Thiele2, Andreas Vieli3, Daniel Vonder Mühll14, Samuel Weber2,3,15, and Vanessa Wirz3 Jan Beutel et al.
  • 1Department of Computer Science, University of Innsbruck, Austria
  • 2Computer Engineering and Networks Laboratory, ETH Zurich, Switzerland
  • 3Department of Geography, University of Zurich, Switzerland
  • 4Department of Geosciences, University of Fribourg, Switzerland
  • 5Carleton University, Ottawa, Canada
  • 6SensAlpin GmbH, Davos, Switzerland
  • 7Terradata AG, Zurich, Switzerland
  • 8Ct. Valais, Sion, Switzerland
  • 9WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
  • 10Rovina und Partner AG, Visp, Switzerland
  • 11Federal Office for the Environment FOEN, Ittigen, Switzerland
  • 12Institute of Earth Sciences, University of Applied Sciences and Arts of Southern Switzerland (SUPSI), Switzerland
  • 13GAMMA Remote Sensing and Consulting AG, Gümlingen, Switzerland
  • 14Personalized Health and Related Technologies, ETH Zurich, Switzerland
  • 15Chair of Landslide Research, Technical University of Munich, Germany

Abstract. Permafrost warming is coinciding with accelerated mass movements, talking place especially in steep, mountainous topography. While this observation is backed up by evidence and analysis of both remote sensing as well as repeat terrestrial surveys undertaken since decades much knowledge is to be gained about the specific details, the variability and the processes governing these mass movements in the mountain cryosphere. 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 m 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. To date this dataset has seen numerous use cases in research as well as natural-hazard mitigation and adaptation due to climate change.

Jan Beutel et al.

Status: open (until 09 Oct 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • AC1: 'Comment on essd-2021-176 - dataset availability', Jan Beutel, 23 Jun 2021 reply
  • RC1: 'Comment on essd-2021-176', Anonymous Referee #1, 15 Jul 2021 reply

Jan Beutel et al.

Data sets

Kinematic observations of the mountain cryosphere using in-situ GNSS instruments 2011-2021 Jan Beutel et al.

Model code and software

Scripts for GNSS processing using RTKLIB Jan Beutel

PermaSense Data Manager Samuel Weber, Jan Beutel, Matthias Meyer

Jan Beutel et al.


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Short summary
Using standard GPS receivers it is possible to track terrain movements at the sub centimeter scale. This paper documents experiments using this technique monitoring different cryosphere-related mass movement in high-alpine terrain: rock glaciers, landslides as well as steep bedrock. The data serves basic research but also decision making and mitigation of natural hazard as well as adaptation to climate change. It is the largest data set of it’s kind comprising over 209’000 daily positions.