An inventory of permafrost evidence for the European Alps

• Published in: The Cryosphere
• Main Authors: Cremonese, Edoardo, Gruber, Stephan, Phillips, Maria, Pogliotti, Paolo, Boeckli, L., Noetzli, Jeannette, Suter, C., Bodin, Xavier, Crepaz, A., Kellerer-Pirklbauer, Andreas, Letey, S., Mair, V., Morra Di Cella, Umberto, Ravanel, Ludovic, Scapozza, Christian, Seppi, R., Zischg, A.
• Other Authors: Aosta Valley Regional Environmental Protection Agency (ARPA), Glaciology, Geomorphodynamics and Geochronology, Department of Geography Zürich, Universität Zürich Zürich = University of Zurich (UZH)-Universität Zürich Zürich = University of Zurich (UZH), Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Environnements, Dynamiques et Territoires de Montagne (EDYTEM), Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS), Department of Geography and Regional Scienc, Karl-Franzens-Universität Graz, Institute of Remote Sensing and Photogrammetry, Institut de Géographie Lausanne (IGUL), Université de Lausanne = University of Lausanne (UNIL), Earth Science Department, Università degli Studi di Pavia = University of Pavia (UNIPV), Abenis Alpinexpert srl
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2011
• Subjects: permafrost; The Cryosphere
• Online Access: https://hal.science/halsde-00871037; https://doi.org/10.5194/tc-5-651-2011

International audience The investigation and modelling of permafrost distribution, particularly in areas of discontinuous permafrost, is challenging due to spatial heterogeneity, remoteness of measurement sites and data scarcity. We have designed a strategy for standardizing different local data sets containing evidence of the presence or absence of permafrost into an inventory for the entire European Alps. With this brief communication, we present the structure and contents of this inventory. This collection of permafrost evidence not only highlights existing data and allows new analyses based on larger data sets, but also provides complementary information for an improved interpretation of monitoring results.