In situ observations of the Swiss periglacial environment using GNSS instruments

Cicoria, Alessandro and Weber, Samuel and Biri, Andreas. and Buchli, Ben and Delaloye, Reynald and Da Forno, Reto and Gärtner-Roer, Isabelle and Gruber, Stephan and Gsell, Tonio and Hasler, Andreas and Lim, Roman and Limpach, Philippe and Mayoraz, Raphael and Meyer, Matthias and Noetzli, Jeannette and Phillips, Marcia and Pointner, Eric and Raetzo, Hugo and Scapozza, Cristian and Strozzi, Tazio and Thiele, Lothar and Vieli, Andreas and Vonder Mühll, Daniel and Wirz, Vanessa and Beutel, Jan (2022) In situ observations of the Swiss periglacial environment using GNSS instruments. Earth System Science Data, 14. pp. 5061-5091.

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Monitoring of the periglacial environment is relevant for many disciplines including glaciology, natural hazard management, geomorphology, and geodesy. Since October 2022, Rock Glacier Velocity (RGV) is a new Essential Climate Variable (ECV) product within the Global Climate Observing System (GCOS). However, geodetic surveys at high elevation remain very challenging due to environmental and logistical reasons. During the past decades, the introduction of low-cost global navigation satellite system (GNSS) technologies has allowed us to increase the accuracy and frequency of the observations. Today, permanent GNSS instruments enable continuous surface displacement observations at millimetre accuracy with a sub-daily resolution. In this paper, we describe decennial time series of GNSS observables as well as accompanying meteorological data. The observations comprise 54 positions located on different periglacial landforms (rock glaciers, landslides,and steep rock walls) at altitudes ranging from 2304 to 4003ma:s:l: and spread across the Swiss Alps. The primary data products consist of raw GNSS observables in RINEX format, inclinometers, and weather station data. Additionally, cleaned and aggregated time series of the primary data products are provided, including daily GNSS positions derived through two independent processing tool chains. The observations documented here extend beyond the dataset presented in the paper and are currently continued with the intention of long-term monitoring. An annual update of the dataset, available at (Beutel et al., 2022), is planned. With its future continuation, the dataset holds potential for advancing fundamental process understanding and for the development of applied methods in support of e.g. natural hazard management.

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