Gap‐filling algorithm for ground surface temperature data measured in permafrost and periglacial environments

Ground surface temperatures (GST) are widely measured in mountain permafrost areas, but their time series data can be interrupted by gaps. Gaps complicate the calculation of aggregates and indices required for analysing temporal and spatial variability between loggers and sites. We present an algorithm to estimate daily mean GST and the resulting uncertainty. The algorithm is designed to automatically fill data gaps in a database of several tens to hundreds of time series, for example, the Swiss Permafrost Monitoring Network (PERMOS). Using numerous randomly generated artificial gaps, we validated the performance of the gap-filling routine in terms of (1) the bias resulting on annual means, (2) thawing and freezing degree-days, and (3) the accuracy of the uncertainty estimation. Although quantile mapping provided the most reliable gap-filling approach overall, linear interpolation between neighbouring values performed equally well for gap durations of up to 3–5 days. Finding the most similar regressors is crucial and also the main source of errors, particularly because of the large spatial and temporal variability of ground and snow properties in high-mountain terrains. Applying the gap-filling technique to the PERMOS GST data increased the total number of complete hydrological years available for analysis by 70 per cent (>450-filled gaps), likely without exceeding a maximal uncertainty of ± 0.25 °C in calculated annual mean value

GIS-based modelling of rock-ice avalanches from Alpine permafrost areas

Changing permafrost conditions caused by present atmospheric warming are expected to affect the stability of steep rock walls in high mountain areas. The possible increase in periglacial slope instabilities and the especially long potential run-out distances in glacial environments require more awareness about the kind of events as well as robust models to foresee areas affected and distances reached. A geographic information system-based flow-routing model is introduced for modelling rock-ice avalanches on a regional scale. The model application to three major historical events in the European Alps shows the basic use for simulating such events for first-order assessments. By designating the path of steepest descent while allowing lateral spreading from the fall track up to 45°, general flow patterns as well as changes in the direction of progression are well reproduced. The run-out distances are determined using empirically based models and suit well the case studies presente

Attributing observed permafrost warming in the northern hemisphere to anthropogenic climate change

Permafrost temperatures are increasing globally with the potential of adverse environmental and socio-economic impacts. Nonetheless, the attribution of observed permafrost warming to anthropogenic climate change has relied mostly on qualitative evidence. Here, we compare long permafrost temperature records from 15 boreholes in the northern hemisphere to simulated ground temperatures from Earth system models contributing to CMIP6 using a climate change detection and attribution approach. We show that neither pre-industrial climate variability nor natural drivers of climate change suffice to explain the observed warming in permafrost temperature averaged over all boreholes. However, simulations are consistent with observations if the effects of human emissions on the global climate system are considered. Moreover, our analysis reveals that the effect of anthropogenic climate change on permafrost temperature is detectable at some of the boreholes. Thus, the presented evidence supports the conclusion that anthropogenic climate change is the key driver of northern hemisphere permafrost warming.Bundesministerium für Bildung und Forschunghttp://dx.doi.org/10.13039/501100002347Peer Reviewe

Attributing observed permafrost warming in the northern hemisphere to anthropogenic climate change

Permafrost temperatures are increasing globally with the potential of adverse environmental and socio-economic impacts. Nonetheless, the attribution of observed permafrost warming to anthropogenic climate change has relied mostly on qualitative evidence. Here, we compare long permafrost temperature records from 15 boreholes in the northern hemisphere to simulated ground temperatures from Earth system models contributing to CMIP6 using a climate change detection and attribution approach. We show that neither pre-industrial climate variability nor natural drivers of climate change suffice to explain the observed warming in permafrost temperature averaged over all boreholes. However, simulations are consistent with observations if the effects of human emissions on the global climate system are considered. Moreover, our analysis reveals that the effect of anthropogenic climate change on permafrost temperature is detectable at some of the boreholes. Thus, the presented evidence supports the conclusion that anthropogenic climate change is the key driver of northern hemisphere permafrost warming

Sustaining permafrost observations: priorities and needs of the Global Terrestrial Network for Permafrost (GTN-P)

The Global Terrestrial Network for Permafrost (GTN-P) is the primary international programme concerned with sustained long-term monitoring of permafrost. GTN-P was developed in the 1990s by the International Permafrost Association (IPA) under the Global Terrestrial Observing System (GTOS) as part of the Global Climate Observing System (GCOS). The two major components of GTN-P (Essential Climate Variables) are: (a) long-term monitoring of the thermal state of permafrost in an extensive borehole network, the Thermal State of Permafrost - TSP; and (b) monitoring of the Active-layer thickness - ALT. Long-term monitoring of permafrost generates essential baseline information for the assessment of climate change impacts in polar and high mountain regions

Distinguishing ice-rich and ice-poor permafrost to map ground temperatures and ground ice occurrence in the Swiss Alps

Mountain permafrost is invisible, and mapping it is still a challenge. Available permafrost distribution maps often overestimate the permafrost extent and include large permafrost-free areas in their permafrost zonation. In addition, the representation of the lower belt of permafrost consisting of ice-rich features such as rock glaciers or ice-rich talus slopes can be challenging. These problems are caused by considerable differences in genesis and thermal characteristics between ice-poor permafrost, occurring for example in rock walls, and ice-rich permafrost. While ice- poor permafrost shows a strong correlation of ground temperature with elevation and potential incoming solar radiation, ice-rich ground does not show such a correlation. Instead, the distribution of ice-rich ground is controlled by gravitational processes such as the relocation of ground ice by permafrost creep or by ground ice genesis from avalanche deposits or glacierets covered with talus. We therefore developed a mapping method which distinguishes between ice-poor and ice-rich permafrost and tested it for the entire Swiss Alps. For ice-poor ground we found a linear regression formula based on elevation and potential incoming solar radiation which predicts borehole ground temperatures at multiple depths with an accuracy higher than 0.6 ∘C. The zone of ice-rich permafrost was defined by modelling the deposition zones of alpine mass wasting processes. This dual approach allows the cartographic representation of permafrost-free belts, which are bounded above and below by permafrost. This enables a high quality of permafrost modelling, as is shown by the validation of our map. The dominating influence of the two rather simple connected factors, elevation (as a proxy for mean annual air temperature) and solar radiation, on the distribution of ice-poor permafrost is significant for permafrost modelling in different climate conditions and regions. Indicating temperatures of ice- poor permafrost and distinguishing between ice-poor and ice-rich permafrost on a national permafrost map provides new information for users

Semi-automated calibration method for modelling of mountain permafrost evolution in Switzerland

Permafrost is a widespread phenomenon in mountainous regions of the world such as the European Alps. Many important topics such as the future evolution of permafrost related to climate change and the detection of permafrost related to potential natural hazards sites are of major concern to our society. Numerical permafrost models are the only tools which allow for the projection of the future evolution of permafrost. Due to the complexity of the processes involved and the heterogeneity of Alpine terrain, models must be carefully calibrated, and results should be compared with observations at the site (borehole) scale. However, for large-scale applications, a site- specific model calibration for a multitude of grid points would be very time-consuming. To tackle this issue, this study presents a semi-automated calibration method using the Generalized Likelihood Uncertainty Estimation (GLUE) as implemented in a 1-D soil model (CoupModel) and applies it to six permafrost sites in the Swiss Alps. We show that this semi-automated calibration method is able to accurately reproduce the main thermal condition characteristics with some limitations at sites with unique conditions such as 3-D air or water circulation, which have to be calibrated manually. The calibration obtained was used for global and regional climate model (GCM/RCM)-based long-term climate projections under the A1B climate scenario (EU-ENSEMBLES project) specifically downscaled at each borehole site. The projection shows general permafrost degradation with thawing at 10 m, even partially reaching 20 m depth by the end of the century, but with different timing among the sites and with partly considerable uncertainties due to the spread of the applied climatic forcing

Permafrost Measurements Best Practice: GCW’s contribution to standardization of global observations

The Global Cryosphere Watch (GCW), in the context of the framework of the World Meteorological Organization (WMO), published the Measurement of Cryospheric Variables, Volume II of the Guide to Instruments and Methods of Observation in 2018, in which best practice for observations of snow parameters was included. As a follow-up effort, measurement best practices for the other cryosphere components are under development, including permafrost and seasonally frozen ground. The measurement best practice for permafrost aims to define reference methods for the configuration and ongoing operation of stations for in situ observations in high mountains and polar regions. It will: address gaps in the existing permafrost monitoring systems, define methods for improving traceability and comparability, recommend instrumental characteristics and provide measurements uncertainty evaluation. A further objective is to support capacity building of countries in terms of developing a permafrost observation network. A Task Team within the framework of GCW was established, to lead the development and publication of a complete guide to the measurements of permafrost variables. The documents in preparation will be coordinated with the ongoing revision of Products and Requirements of the Global Climate Observing System (GCOS) Permafrost Essential Climate Variable (ECV), including existing variables measured by the GTN-P (Global Terrestrial Network for Permafrost). Further, the needs of developing Essential Arctic Variables (EAV) and Shared Arctic Variables (SAV) identified at the Arctic Observing Summit (AOS) are considered. The work will be based on existing methodologies, promoting and recommending methods to improve data reliability and traceability, also for the implementation of new stations

In situ observations of the Swiss periglacial environment using GNSS instruments

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 4003 ma.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 https://doi.org/10.1594/PANGAEA.948334 (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

Permafrost is warming at a global scale

Permafrost warming has the potential to amplify global climate change, because when frozen sediments thaw it unlocks soil organic carbon. Yet to date, no globally consistent assessment of permafrost temperature change has been compiled. Here we use a global data set of permafrost temperature time series from the Global Terrestrial Network for Permafrost to evaluate temperature change across permafrost regions for the period since the International Polar Year (2007-2009). During the reference decade between 2007 and 2016, ground temperature near the depth of zero annual amplitude in the continuous permafrost zone increased by 0.39 ± 0.15 °C. Over the same period, discontinuous permafrost warmed by 0.20 ± 0.10 °C. Permafrost in mountains warmed by 0.19 ± 0.05 °C and in Antarctica by 0.37 ± 0.10 °C. Globally, permafrost temperature increased by 0.29 ± 0.12 °C. The observed trend follows the Arctic amplification of air temperature increase in the Northern Hemisphere. In the discontinuous zone, however, ground warming occurred due to increased snow thickness while air temperature remained statistically unchanged