Ground temperature time series in European mountain permafrost
<p>RELATED PUBLICATION</p> <p>This dataset is related to the following publication:</p> <p><strong>Noetzli J., Isaksen, K., Barnett, J., Chrisitiansen, H.H., Delaloye, R., Etzelmueller, B., Farinotti, D., Gallemann, T., Guglielmin, M., Hauck, C., Hilbich, C., Hoelzle, M., Lambiel, C., Magnin, F., Oliva, M., Paro, L, Pogliotti, P., Riedl, C., Schoeneich, P., M., Valt, M., Vieli A., Philliips, M. (2024). Enhanced permafrost warming in Euro­pean mountains in the 21st century. Nature Communications, 15, 10508, <a href="https://doi.org/10.1038/s41467-024-54831-9">https://doi.org/10.1038/s41467-024-54831-9</a>.</strong></p> <p><strong>==> </strong></p> <p><strong>For information on the measurements, selection criteria, processing information and data providers please refer to the methods, data availability and acknowledgements sections of the related publication ! </strong></p> <p> </p> <p>---------------------------------------------------------------------------------------------------------------------------</p> <p>CONTENT</p> <p>The dataset includes monthly and annual time series of ground temperatures measured in 64 boreholes in European mountain permafrost areas and corresponding metadata.</p> <p>Temporal coverage: at least 10 years until 2022</p> <p>Spatial coverage: European mountain regions (Svalbard, Scandinavia, Iceland, European Alps, Sierra Nevada)</p> <p>Depth of measurements: at least 10 m; for all boreholes data of the sensors closest to 5, 10 and 20 m depth are included</p> <p>Monthly means are calculated from daily values and annual values are derived from monthly mean values.</p> <p> </p> <p>---------------------------------------------------------------------------------------------------------------------------</p> <p>DATA COMPILATION</p> <p>The data were compiled to derive 10-year and 20-year warming rates in European mountain permafrost in the study by Noetzli et al. (in review, see above). Data were collected from national permafrost observation networks as well as from individual institutions (e.g, universities, environmental agencies).</p> <p>The aquisition of long time series over decades requires long-term committment from the responsible institutions to maintain instruments and to collect and curate the data. Details on the data source for each time series can be found in the metadata file as well as in the related publication. The main data sources by country are given in the list below.</p> <table> <tbody> <tr> <td><strong>Country</strong></td> <td><strong>Data source (institution or national network)</strong></td> </tr> <tr> <td>Austria</td> <td>GeoSphere Austria</td> </tr> <tr> <td>France</td> <td>Réseau français d'observation du permafrost (PermaFrance, <a href="https://wslch365-my.sharepoint.com/personal/jeannette_noetzli_slf_ch/Documents/PermafrostEurope/permafrance.osug.fr">permafrance.osug.fr</a>)</td> </tr> <tr> <td>Germany</td> <td>Bavarian Environment Agency</td> </tr> <tr> <td>Iceland</td> <td>University of Oslo</td> </tr> <tr> <td>Italy</td> <td>ARPA Piemonte, ARPA Valle d'Aosta, ARPA Veneto, University of Insubria</td> </tr> <tr> <td>Norway</td> <td>Norwegian Permafrost Monitoring Network (<a href="https://cryo.met.no/">cryo.met.no</a> and <a href="http://sios-svalbard.org/">sios-svalbard.org</a>)</td> </tr> <tr> <td>Spain</td> <td>Universitat de Barcelona</td> </tr> <tr> <td>Svalbard</td> <td>Norwegian Permafrost Monitoring Network (<a href="https://cryo.met.no/">cryo.met.no</a> and <a href="http://sios-svalbard.org/">sios-svalbard.org</a>)</td> </tr> <tr> <td>Sweden</td> <td>University of Stockholm</td> </tr> <tr> <td>Switzerland</td> <td>Swiss Permafrost Monitoring Network PERMOS (<a href="http://www.permos.ch">http://www.permos.ch</a>)</td> </tr> </tbody> </table> <p> </p> <p>---------------------------------------------------------------------------------------------------------------------------</p> <p>FILES AND FORMAT</p> <p>This data set includes three csv-files: <br>1) metadata with information on the measurement location and data provider<br>2) monthly ground temperature time series and <br>3) annual ground temperature time series. </p> <p>The variables in the three files are described below. Data files are in long data format.</p> <p><strong>File 1 – borehole_overview.csv<br></strong>Key information on the boreholes, responsible institutions and contact persons.</p> <table> <tbody> <tr> <td><strong>Variable</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>Name</td> <td>Name of the borehole (as used in the related study)</td> </tr> <tr> <td>Country</td> <td>Alpha-2 code</td> </tr> <tr> <td>Region</td> <td>Larger region</td> </tr> <tr> <td>First_year</td> <td>First year of data</td> </tr> <tr> <td>Elevation [m asl.]</td> <td>Elevation of the borehole</td> </tr> <tr> <td>Lat [° N]</td> <td>Latitude</td> </tr> <tr> <td>Lon [° E]</td> <td>Longitude</td> </tr> <tr> <td>Depth [m]</td> <td>Total depth of the borehole</td> </tr> <tr> <td>DZAA [m]</td> <td>Depth of the Zero Annual Amplitude (uppermost sensor with annual amplitude ≤0.1)</td> </tr> <tr> <td>Phase lag</td> <td>Phase lag at 10 m depth compared to surface in months</td> </tr> <tr> <td>Morphology</td> <td>Main morphology of the site</td> </tr> <tr> <td>Surface_cover</td> <td>Main surface cover at the site</td> </tr> <tr> <td>Lithology</td> <td>Main lithology of the site</td> </tr> <tr> <td>Ice_content</td> <td>Basic classification by ground ice content at the site (no ice, ice-poor, ice-bearing, ice-rich), see publication for details</td> </tr> <tr> <td>Institution</td> <td>Responsible institution (in the year 2024)</td> </tr> <tr> <td>Contact_person</td> <td>Contact person (in the year 2024)</td> </tr> <tr> <td>Special_remarks</td> <td>Remarks on location, e.g. horizontal borehole</td> </tr> </tbody> </table> <p> </p> <p><strong>File 2 – permafrost_temperatures_european_mountains_monthly_2022.csv<br></strong>Time series of monthly mean ground temperatures at ca. 5, 10 and 20 m depth for 64 boreholes in European mountain permafrost until 2022.</p> <table> <tbody> <tr> <td><strong>Variable</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>bh</td> <td>Name of the borehole</td> </tr> <tr> <td>time [YYYY-MM-DD]</td> <td>Date</td> </tr> <tr> <td>depth [m]</td> <td>Depth of measurement</td> </tr> <tr> <td>temp [°C]</td> <td>Monthly mean ground temperature (aggregated from daily values)</td> </tr> <tr> <td>t_min [°C]</td> <td>Minimum daily ground temperature of the year</td> </tr> <tr> <td>t_max [°C]</td> <td>Maximum daily ground temperature of the year</td> </tr> <tr> <td>count</td> <td>Number of daily values available to calculate monthly mean values</td> </tr> <tr> <td>dclass [5, 10 or 20 m]</td> <td>Depth class defined for analyses in related study</td> </tr> </tbody> </table> <p> </p> <p><strong>File 3 – permafrost_temperatures_european_mountains_annual_2022.csv<br></strong>Time series of annual mean ground temperatures at ca. 5, 10 and 20 m depth for 64 boreholes in European mountain permafrost until 2022.</p> <table> <tbody> <tr> <td><strong>Variable</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>bh</td> <td>Name of the borehole</td> </tr> <tr> <td>time [YYYY]</td> <td>Year</td> </tr> <tr> <td>depth [m]</td> <td>Depth of measurement</td> </tr> <tr> <td>temp [°C]</td> <td>Annual mean ground temperature (aggregated from monthly values)</td> </tr> <tr> <td>t_min [°C]</td> <td>Minimum monthly ground temperature of the year</td> </tr> <tr> <td>t_max [°C]</td> <td>Maximum monthlyground temperature of the year</td> </tr> <tr> <td>count</td> <td>Number of monthly values available to calculate annual mean values</td> </tr> <tr> <td>dclass [5, 10 or 20 m]</td> <td>Depth class defined for analyses in related study</td> </tr> </tbody> </table> <p> </p> <p>---------------------------------------------------------------------------------------------------------------------------</p> <p>CONTACT</p> <p>For question related to this dataset please contact the corresponding author: jeannette.noetzli@slf.ch. <br>For questions related to a specific time series, see metadata for contact information.</p>
ShareScore
52/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 12
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 8