Articles | Volume 6, issue 4
https://doi.org/10.5194/wcd-6-1075-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-6-1075-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Oct 2025
Research article |
| 07 Oct 2025
| 07 Oct 2025
The role of large-scale atmospheric patterns for recent warming periods in Greenland from 1900–2015
Florina Roana Schalamon
CORRESPONDING AUTHOR
Department of Geography and Regional Sciences, University of Graz, Heinrichstr. 36, 8010 Graz, Austria
Sebastian Scher
Department of Geography and Regional Sciences, University of Graz, Heinrichstr. 36, 8010 Graz, Austria
Wegener Center for Climate and Global Change (WEGC), University of Graz, Brandhofgasse 5, 8010 Graz, Austria
Andreas Trügler
Department of Geography and Regional Sciences, University of Graz, Heinrichstr. 36, 8010 Graz, Austria
Know-Center, Research Center for Data-Driven Business and Artificial Intelligence, Sandgasse 34/2, 8010 Graz, Austria
Lea Hartl
Institute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Innrain 25, 6020 Innsbruck, Austria
Alaska Climate Research Center, University of Alaska Fairbanks, 2156 Koyukuk Drive, Fairbanks, AK 99775, USA
Wolfgang Schöner
Department of Geography and Regional Sciences, University of Graz, Heinrichstr. 36, 8010 Graz, Austria
Jakob Abermann
Department of Geography and Regional Sciences, University of Graz, Heinrichstr. 36, 8010 Graz, Austria
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Klaus Haslinger, Wolfgang Schöner, Jakob Abermann, Gregor Laaha, Konrad Andre, Marc Olefs, and Roland Koch
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Moritz Buchmann, Gernot Resch, Michael Begert, Stefan Brönnimann, Barbara Chimani, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 17, 653–671, https://doi.org/10.5194/tc-17-653-2023, https://doi.org/10.5194/tc-17-653-2023, 2023
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Tiago Silva, Jakob Abermann, Brice Noël, Sonika Shahi, Willem Jan van de Berg, and Wolfgang Schöner
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Jonathan P. Conway, Jakob Abermann, Liss M. Andreassen, Mohd Farooq Azam, Nicolas J. Cullen, Noel Fitzpatrick, Rianne H. Giesen, Kirsty Langley, Shelley MacDonell, Thomas Mölg, Valentina Radić, Carleen H. Reijmer, and Jean-Emmanuel Sicart
The Cryosphere, 16, 3331–3356, https://doi.org/10.5194/tc-16-3331-2022, https://doi.org/10.5194/tc-16-3331-2022, 2022
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We used data from automatic weather stations on 16 glaciers to show how clouds influence glacier melt in different climates around the world. We found surface melt was always more frequent when it was cloudy but was not universally faster or slower than under clear-sky conditions. Also, air temperature was related to clouds in opposite ways in different climates – warmer with clouds in cold climates and vice versa. These results will help us improve how we model past and future glacier melt.
Thomas Goelles, Tobias Hammer, Stefan Muckenhuber, Birgit Schlager, Jakob Abermann, Christian Bauer, Víctor J. Expósito Jiménez, Wolfgang Schöner, Markus Schratter, Benjamin Schrei, and Kim Senger
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We propose a newly developed modular MObile LIdar SENsor System (MOLISENS) to enable new applications for small industrial light detection and ranging (lidar) sensors. MOLISENS supports both monitoring of dynamic processes and mobile mapping applications. The mobile mapping application of MOLISENS has been tested under various conditions, and results are shown from two surveys in the Lurgrotte cave system in Austria and a glacier cave in Longyearbreen on Svalbard.
Moritz Buchmann, John Coll, Johannes Aschauer, Michael Begert, Stefan Brönnimann, Barbara Chimani, Gernot Resch, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 16, 2147–2161, https://doi.org/10.5194/tc-16-2147-2022, https://doi.org/10.5194/tc-16-2147-2022, 2022
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Knowledge about inhomogeneities in a data set is important for any subsequent climatological analysis. We ran three well-established homogenization methods and compared the identified break points. By only treating breaks as valid when detected by at least two out of three methods, we enhanced the robustness of our results. We found 45 breaks within 42 of 184 investigated series; of these 70 % could be explained by events recorded in the station history.
Sebastian Scher and Stefanie Peßenteiner
Hydrol. Earth Syst. Sci., 25, 3207–3225, https://doi.org/10.5194/hess-25-3207-2021, https://doi.org/10.5194/hess-25-3207-2021, 2021
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In hydrology, it is often necessary to infer from a daily sum of precipitation a possible distribution over the day – for example how much it rained in each hour. In principle, for a given daily sum, there are endless possibilities. However, some are more likely than others. We show that a method from artificial intelligence called generative adversarial networks (GANs) can
learnwhat a typical distribution over the day looks like.
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schöner, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Sušnik, Alberto Trenti, Stefano Urbani, and Viktor Weilguni
The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, https://doi.org/10.5194/tc-15-1343-2021, 2021
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The first Alpine-wide assessment of station snow depth has been enabled by a collaborative effort of the research community which involves more than 30 partners, 6 countries, and more than 2000 stations. It shows how snow in the European Alps matches the climatic zones and gives a robust estimate of observed changes: stronger decreases in the snow season at low elevations and in spring at all elevations, however, with considerable regional differences.
Assaf Hochman, Sebastian Scher, Julian Quinting, Joaquim G. Pinto, and Gabriele Messori
Earth Syst. Dynam., 12, 133–149, https://doi.org/10.5194/esd-12-133-2021, https://doi.org/10.5194/esd-12-133-2021, 2021
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Skillful forecasts of extreme weather events have a major socioeconomic relevance. Here, we compare two approaches to diagnose the predictability of eastern Mediterranean heat waves: one based on recent developments in dynamical systems theory and one leveraging numerical ensemble weather forecasts. We conclude that the former can be a useful and cost-efficient complement to conventional numerical forecasts for understanding the dynamics of eastern Mediterranean heat waves.
Lea Hartl, Lucia Felbauer, Gabriele Schwaizer, and Andrea Fischer
The Cryosphere, 14, 4063–4081, https://doi.org/10.5194/tc-14-4063-2020, https://doi.org/10.5194/tc-14-4063-2020, 2020
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When glaciers become snow-free in summer, darker glacier ice is exposed. The ice surface is darker than snow and absorbs more radiation, which increases ice melt. We measured how much radiation is reflected at different wavelengths in the ablation zone of Jamtalferner, Austria. Due to impurities and water on the ice surface there are large variations in reflectance. Landsat 8 and Sentinel-2 surface reflectance products do not capture the full range of reflectance found on the glacier.
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Short summary
Atmospheric patterns influence the air temperature in Greenland. We investigate two warming periods, from 1922–1932 and 1993–2007, both showing similar temperature increases. Using a neural network-based clustering method, we defined predominant atmospheric patterns for further analysis. Our findings reveal that while the connection between these patterns and local air temperature remains stable, the distribution of patterns changes between the warming periods and the full period (1900–2015).
Atmospheric patterns influence the air temperature in Greenland. We investigate two warming...
