Articles | Volume 4, issue 3
https://doi.org/10.5194/wcd-4-747-2023
© Author(s) 2023. 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-4-747-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The importance of regional sea-ice variability for the coastal climate and near-surface temperature gradients in Northeast Greenland
Department of Geography and Regional Science, University of Graz,
Graz, Austria
Austrian Polar Research Institute, Vienna, Austria
Jakob Abermann
Department of Geography and Regional Science, University of Graz,
Graz, Austria
Austrian Polar Research Institute, Vienna, Austria
Asiaq – Greenland Survey, Nuuk, Greenland
Tiago Silva
Department of Geography and Regional Science, University of Graz,
Graz, Austria
Austrian Polar Research Institute, Vienna, Austria
Kirsty Langley
Asiaq – Greenland Survey, Nuuk, Greenland
Signe Hillerup Larsen
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Mikhail Mastepanov
Department of Ecoscience, Aarhus University, Aarhus, Denmark
Wolfgang Schöner
Department of Geography and Regional Science, University of Graz,
Graz, Austria
Austrian Polar Research Institute, Vienna, Austria
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The Cryosphere, 16, 3375–3391, https://doi.org/10.5194/tc-16-3375-2022, https://doi.org/10.5194/tc-16-3375-2022, 2022
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To overcome internal climate variability, this study uses k-means clustering to combine NAO, GBI and IWV over the Greenland Ice Sheet (GrIS) and names the approach as the North Atlantic influence on Greenland (NAG). With the support of a polar-adapted RCM, spatio-temporal changes on SEB components within NAG phases are investigated. We report atmospheric warming and moistening across all NAG phases as well as large-scale and regional-scale contributions to GrIS mass loss and their interactions.
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We use measurements conducted with uncrewed aerial vehicles (UAVs) and reanalysis data to study the drivers of vertical air temperature structures and their link to the surface mass balance of Flade Isblink, a large ice cap in Northeast Greenland. Surface properties control temperature structures up to 100 m above ground, while large-scale circulation dominates above. Mass loss has increased since 2015, with record loss in 2023 associated with frequent synoptic conditions favoring melt.
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Ice in Greenland either ends in the ocean or on land and in lakes. We show that more than 95% of the margin ends on land. Ice ending in lakes is much rarer, but with 1.4% quite similar to the 2.2% ending in oceans. We also see that more than 20% of the margin ends in extremely steep, often vertical cliffs. We will now be able to compare these maps against local ice velocities, mass loss and climate to understand whether the margin shape teaches us something about the health of ice in the region.
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The Cryosphere, 19, 1431–1452, https://doi.org/10.5194/tc-19-1431-2025, https://doi.org/10.5194/tc-19-1431-2025, 2025
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EGUsphere, https://doi.org/10.5194/egusphere-2025-217, https://doi.org/10.5194/egusphere-2025-217, 2025
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Florina Roana Schalamon, Sebastian Scher, Andreas Trügler, Lea Hartl, Wolfgang Schöner, and Jakob Abermann
EGUsphere, https://doi.org/10.5194/egusphere-2024-4060, https://doi.org/10.5194/egusphere-2024-4060, 2025
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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).
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The Cryosphere, 18, 6005–6026, https://doi.org/10.5194/tc-18-6005-2024, https://doi.org/10.5194/tc-18-6005-2024, 2024
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Snow depth plays an important role in water resources, mountain tourism, and hazard management across the European Alps. Our study uses station-based historical observations to quantify how changes in temperature and precipitation affect average seasonal snow depth. We find that the relationship between these variables has been surprisingly robust over the last 120 years. This allows us to more accurately estimate how future climate will affect seasonal snow depth in different elevation zones.
Jorrit van der Schot, Jakob Abermann, Tiago Silva, Kerstin Rasmussen, Michael Winkler, Kirsty Langley, and Wolfgang Schöner
The Cryosphere, 18, 5803–5823, https://doi.org/10.5194/tc-18-5803-2024, https://doi.org/10.5194/tc-18-5803-2024, 2024
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We present snow data from nine locations in coastal Greenland. We show that a reanalysis product (CARRA) simulates seasonal snow characteristics better than a regional climate model (RACMO). CARRA output matches particularly well with our reference dataset when we look at the maximum snow water equivalent and the snow cover end date. We show that seasonal snow in coastal Greenland has large spatial and temporal variability and find little evidence of trends in snow cover characteristics.
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Earth Syst. Sci. Data, 16, 5405–5428, https://doi.org/10.5194/essd-16-5405-2024, https://doi.org/10.5194/essd-16-5405-2024, 2024
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Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving. Here we present an annual series (2019–2022) of summer digital elevation models (PRODEMs) for the Greenland Ice Sheet margin, covering all outlet glaciers from the ice sheet. The PRODEMs are based on fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry. With their high spatial and temporal resolution, the PRODEMs will enable detailed studies of the changes in marginal ice sheet elevations.
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The Cryosphere, 18, 5481–5494, https://doi.org/10.5194/tc-18-5481-2024, https://doi.org/10.5194/tc-18-5481-2024, 2024
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An avalanche event in February 2018 caused thick snow deposits on Freya Glacier, a peripheral mountain glacier in northeastern Greenland. The avalanche deposits contributed significantly to the mass balance, leaving a strong imprint in the elevation changes in 2013–2021. The 8-year geodetic mass balance (2013–2021) of the glacier is positive, whereas previous estimates by direct measurements were negative and now turned out to have a negative bias.
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EGUsphere, https://doi.org/10.5194/egusphere-2024-2571, https://doi.org/10.5194/egusphere-2024-2571, 2024
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Ecosystems in Greenland have experienced significant changes over recent decades. Here, we show the consistency of a high-resolution polar-adapted reanalysis product to represent bio-climatic factors influencing ecological processes. Our results describe the interaction between snowmelt and soil water availability before the growing season onset, infer how changes in the growing season relate to changes in spectral greenness and identify regions of ongoing changes in vegetation distribution.
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Earth Syst. Sci. Data, 16, 4103–4118, https://doi.org/10.5194/essd-16-4103-2024, https://doi.org/10.5194/essd-16-4103-2024, 2024
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The Cryosphere, 18, 2035–2059, https://doi.org/10.5194/tc-18-2035-2024, https://doi.org/10.5194/tc-18-2035-2024, 2024
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Florian Lippl, Alexander Maringer, Margit Kurka, Jakob Abermann, Wolfgang Schöner, and Manuela Hirschmugl
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-12, https://doi.org/10.5194/essd-2024-12, 2024
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The aim of our work was to give an overview of data currently available for the National Park Gesäuse and Johnsbachtal relevant to the European long-term ecosystem monitoring. This data, further was made available on respective data repositories, where all data is downloadable free of charge. Data presented in our paper is from all compartments, the atmosphere, social & economic sphere, biosphere and geosphere. We consider our approach as an opportunity to function as a showcase for other sites.
Maral Habibi, Iman Babaeian, and Wolfgang Schöner
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-48, https://doi.org/10.5194/hess-2024-48, 2024
Publication in HESS not foreseen
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Our study investigates how snow melting affects droughts in Iran's Urmia Lake Basin, revealing that future droughts will likely become more severe due to reduced snowmelt and increased evaporation. This is crucial for understanding water availability in the region, affecting millions. We used advanced climate models and drought indices to predict changes, aiming to inform water management strategies.
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
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How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
Klaus Haslinger, Wolfgang Schöner, Jakob Abermann, Gregor Laaha, Konrad Andre, Marc Olefs, and Roland Koch
Nat. Hazards Earth Syst. Sci., 23, 2749–2768, https://doi.org/10.5194/nhess-23-2749-2023, https://doi.org/10.5194/nhess-23-2749-2023, 2023
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Future changes of surface water availability in Austria are investigated. Alterations of the climatic water balance and its components are analysed along different levels of elevation. Results indicate in general wetter conditions with particular shifts in timing of the snow melt season. On the contrary, an increasing risk for summer droughts is apparent due to increasing year-to-year variability and decreasing snow melt under future climate conditions.
Alice C. Frémand, Peter Fretwell, Julien A. Bodart, Hamish D. Pritchard, Alan Aitken, Jonathan L. Bamber, Robin Bell, Cesidio Bianchi, Robert G. Bingham, Donald D. Blankenship, Gino Casassa, Ginny Catania, Knut Christianson, Howard Conway, Hugh F. J. Corr, Xiangbin Cui, Detlef Damaske, Volkmar Damm, Reinhard Drews, Graeme Eagles, Olaf Eisen, Hannes Eisermann, Fausto Ferraccioli, Elena Field, René Forsberg, Steven Franke, Shuji Fujita, Yonggyu Gim, Vikram Goel, Siva Prasad Gogineni, Jamin Greenbaum, Benjamin Hills, Richard C. A. Hindmarsh, Andrew O. Hoffman, Per Holmlund, Nicholas Holschuh, John W. Holt, Annika N. Horlings, Angelika Humbert, Robert W. Jacobel, Daniela Jansen, Adrian Jenkins, Wilfried Jokat, Tom Jordan, Edward King, Jack Kohler, William Krabill, Mette Kusk Gillespie, Kirsty Langley, Joohan Lee, German Leitchenkov, Carlton Leuschen, Bruce Luyendyk, Joseph MacGregor, Emma MacKie, Kenichi Matsuoka, Mathieu Morlighem, Jérémie Mouginot, Frank O. Nitsche, Yoshifumi Nogi, Ole A. Nost, John Paden, Frank Pattyn, Sergey V. Popov, Eric Rignot, David M. Rippin, Andrés Rivera, Jason Roberts, Neil Ross, Anotonia Ruppel, Dustin M. Schroeder, Martin J. Siegert, Andrew M. Smith, Daniel Steinhage, Michael Studinger, Bo Sun, Ignazio Tabacco, Kirsty Tinto, Stefano Urbini, David Vaughan, Brian C. Welch, Douglas S. Wilson, Duncan A. Young, and Achille Zirizzotti
Earth Syst. Sci. Data, 15, 2695–2710, https://doi.org/10.5194/essd-15-2695-2023, https://doi.org/10.5194/essd-15-2695-2023, 2023
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This paper presents the release of over 60 years of ice thickness, bed elevation, and surface elevation data acquired over Antarctica by the international community. These data are a crucial component of the Antarctic Bedmap initiative which aims to produce a new map and datasets of Antarctic ice thickness and bed topography for the international glaciology and geophysical community.
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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Our current knowledge of spatial and temporal snow depth trends is based almost exclusively on time series of non-homogenised observational data. However, like other long-term series from observations, they are susceptible to inhomogeneities that can affect the trends and even change the sign. To assess the relevance of homogenisation for daily snow depths, we investigated its impact on trends and changes in extreme values of snow indices between 1961 and 2021 in the Swiss observation network.
Tiago Silva, Jakob Abermann, Brice Noël, Sonika Shahi, Willem Jan van de Berg, and Wolfgang Schöner
The Cryosphere, 16, 3375–3391, https://doi.org/10.5194/tc-16-3375-2022, https://doi.org/10.5194/tc-16-3375-2022, 2022
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To overcome internal climate variability, this study uses k-means clustering to combine NAO, GBI and IWV over the Greenland Ice Sheet (GrIS) and names the approach as the North Atlantic influence on Greenland (NAG). With the support of a polar-adapted RCM, spatio-temporal changes on SEB components within NAG phases are investigated. We report atmospheric warming and moistening across all NAG phases as well as large-scale and regional-scale contributions to GrIS mass loss and their interactions.
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
Geosci. Instrum. Method. Data Syst., 11, 247–261, https://doi.org/10.5194/gi-11-247-2022, https://doi.org/10.5194/gi-11-247-2022, 2022
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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.
Mimmi Oksman, Anna Bang Kvorning, Signe Hillerup Larsen, Kristian Kjellerup Kjeldsen, Kenneth David Mankoff, William Colgan, Thorbjørn Joest Andersen, Niels Nørgaard-Pedersen, Marit-Solveig Seidenkrantz, Naja Mikkelsen, and Sofia Ribeiro
The Cryosphere, 16, 2471–2491, https://doi.org/10.5194/tc-16-2471-2022, https://doi.org/10.5194/tc-16-2471-2022, 2022
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One of the questions facing the cryosphere community today is how increasing runoff from the Greenland Ice Sheet impacts marine ecosystems. To address this, long-term data are essential. Here, we present multi-site records of fjord productivity for SW Greenland back to the 19th century. We show a link between historical freshwater runoff and productivity, which is strongest in the inner fjord – influenced by marine-terminating glaciers – where productivity has increased since the late 1990s.
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.
Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, Kathleen Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, Darcy Peter, Christina Minions, Julia Nojeim, Roisin Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki Iwata, Hideki Kobayashi, Pasi Kolari, Efrén López-Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans-Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret-Harte, Sigrid Dengel, Han Dolman, Colin W. Edgar, Bo Elberling, Eugenie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang-Jong Park, Roman Petrov, Anatoly S. Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, William Quinton, Andrej Varlagin, Donatella Zona, and Viacheslav I. Zyryanov
Earth Syst. Sci. Data, 14, 179–208, https://doi.org/10.5194/essd-14-179-2022, https://doi.org/10.5194/essd-14-179-2022, 2022
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The effects of climate warming on carbon cycling across the Arctic–boreal zone (ABZ) remain poorly understood due to the relatively limited distribution of ABZ flux sites. Fortunately, this flux network is constantly increasing, but new measurements are published in various platforms, making it challenging to understand the ABZ carbon cycle as a whole. Here, we compiled a new database of Arctic–boreal CO2 fluxes to help facilitate large-scale assessments of the ABZ carbon cycle.
Johan H. Scheller, Mikhail Mastepanov, Hanne H. Christiansen, and Torben R. Christensen
Biogeosciences, 18, 6093–6114, https://doi.org/10.5194/bg-18-6093-2021, https://doi.org/10.5194/bg-18-6093-2021, 2021
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Our study presents a time series of methane emissions in a high-Arctic-tundra landscape over 14 summers, which shows large variations between years. The methane emissions from the valley are expected to more than double in the late 21st century. This warming increases permafrost thaw, which could increase surface erosion in the valley. Increased erosion could offset some of the rise in methane fluxes from the valley, but this would require large-scale impacts on vegetated surfaces.
Robert S. Fausto, Dirk van As, Kenneth D. Mankoff, Baptiste Vandecrux, Michele Citterio, Andreas P. Ahlstrøm, Signe B. Andersen, William Colgan, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, Søren Nielsen, Allan Ø. Pedersen, Christopher L. Shields, Anne M. Solgaard, and Jason E. Box
Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, https://doi.org/10.5194/essd-13-3819-2021, 2021
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The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheet properties since 2007. Here, we present our data product from weather and ice sheet measurements from a network of automatic weather stations mainly located in the melt area of the ice sheet. Currently the PROMICE automatic weather station network includes 25 instrumented sites in Greenland.
Anne Solgaard, Anders Kusk, John Peter Merryman Boncori, Jørgen Dall, Kenneth D. Mankoff, Andreas P. Ahlstrøm, Signe B. Andersen, Michele Citterio, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 3491–3512, https://doi.org/10.5194/essd-13-3491-2021, https://doi.org/10.5194/essd-13-3491-2021, 2021
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The PROMICE Ice Velocity product is a time series of Greenland Ice Sheet ice velocity mosaics spanning September 2016 to present. It is derived from Sentinel-1 SAR data and has a spatial resolution of 500 m. Each mosaic spans 24 d (two Sentinel-1 cycles), and a new one is posted every 12 d (every Sentinel-1A cycle). The spatial comprehensiveness and temporal consistency make the product ideal for monitoring and studying ice-sheet-wide ice discharge and dynamics of glaciers.
Tiago Silva and Elisabeth Schlosser
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2021-22, https://doi.org/10.5194/wcd-2021-22, 2021
Revised manuscript not accepted
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For the first time, a 25-yr climatology of temperature and humidity inversions for Neumayer Station, Antarctica, was presented that takes into account different levels of inversion occurrence and different weather situations. Distinct differences in inversion features and formation mechanisms were found depending on inversion level and weather situation. These findings will increase our understanding of the polar boundary layer and improve the current paleoclimatic interpretation of ice cores.
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.
Kenneth D. Mankoff, Brice Noël, Xavier Fettweis, Andreas P. Ahlstrøm, William Colgan, Ken Kondo, Kirsty Langley, Shin Sugiyama, Dirk van As, and Robert S. Fausto
Earth Syst. Sci. Data, 12, 2811–2841, https://doi.org/10.5194/essd-12-2811-2020, https://doi.org/10.5194/essd-12-2811-2020, 2020
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This work partitions regional climate model (RCM) runoff from the MAR and RACMO RCMs to hydrologic outlets at the ice margin and coast. Temporal resolution is daily from 1959 through 2019. Spatial grid is ~ 100 m, resolving individual streams. In addition to discharge at outlets, we also provide the streams, outlets, and basin geospatial data, as well as a script to query and access the geospatial or time series discharge data from the data files.
Xavier Morel, Birger Hansen, Christine Delire, Per Ambus, Mikhail Mastepanov, and Bertrand Decharme
Earth Syst. Sci. Data, 12, 2365–2380, https://doi.org/10.5194/essd-12-2365-2020, https://doi.org/10.5194/essd-12-2365-2020, 2020
Short summary
Short summary
Nuuk fen site is a well-instrumented Greenlandic site where soil physical variables and greenhouse gas fluxes are monitored. But knowledge of soil carbon stocks and profiles is missing. This is a crucial shortcoming for a complete evaluation of models. For the first time we measured soil carbon and nitrogen density, profiles, and stocks in the Nuuk peatland. This new dataset can contribute to further develop joint modeling of greenhouse gas emissions and soil carbon in land-surface models.
Cited articles
Abermann, J., Hansen, B., Lund, M., Wacker, S., Karami, M., and Cappelen, J.: Hotspots and key periods of Greenland climate change during the past six
decades, Ambio, 46, 3–11, https://doi.org/10.1007/s13280-016-0861-y, 2017.
Alley, R. B., Dupont, T. K., Parizek, B. R., Anandakrishnan, S., Lawson, D.
E., Larson, G. J., and Evenson, E. B.: Outburst flooding and the initiation
of ice-stream surges in response to climatic cooling: A hypothesis,
Geomorphology, 75, 76–89, https://doi.org/10.1016/j.geomorph.2004.01.011, 2006.
Anderson, P. S.: A Method for Rescaling Humidity Sensors at Temperatures
Well below Freezing, J. Atmos. Ocean Tech., 11, 1388–1391, 1994.
Arlot, S., Celisse, A., and Harchaoui, Z.: A Kernel Multiple Change-point
Algorithm via Model Selection, J. Mach. Learn. Res., 20, 1–56, 2019.
Arltová, M. and Fedorová, D.: Selection of Unit Root Test on the
Basis of Time Series Length and Value of AR(1) Parameter, Statistika, 96, 47–64, 2016.
Ayala, A., Pellicciotti, F., MacDonell, S., McPhee, J., Vivero, S., Campos,
C., and Egli, P.: Modelling the hydrological response of debris-free and
debris-covered glaciers to present climatic conditions in the semiarid Andes
of central Chile, Hydrol. Process., 30, 4036–4058, https://doi.org/10.1002/hyp.10971, 2016.
Ballinger, T. J., Hanna, E., Hall, R. J., Cropper, T. E., Miller, J.,
Ribergaard, M. H., Overland, J. E., and Høyer, J. L.: Anomalous blocking
over Greenland preceded the 2013 extreme early melt of local sea ice, Ann.
Glaciol., 59, 181–190, https://doi.org/10.1017/aog.2017.30, 2018a.
Ballinger, T. J., Hanna, E., Hall, R. J., Miller, J., Ribergaard, M. H., and
Høyer, J. L.: Greenland coastal air temperatures linked to Baffin Bay and
Greenland Sea ice conditions during autumn through regional blocking patterns, Clim. Dynam., 50, 83–100, https://doi.org/10.1007/s00382-017-3583-3, 2018b.
Bennartz, R., Shupe, M. D., Turner, D. D., Walden, V. P., Steffen, K., Cox,
C. J., Kulie, M. S., Miller, N. B., and Pettersen, C.: July 2012 Greenland
melt extent enhanced by low-level liquid clouds, Nature, 496, 83–86,
https://doi.org/10.1038/nature12002, 2013.
Bhatt, U. S., Walker, D. A., Raynolds, M. K., Comiso, J. C., Epstein, H. E.,
Jia, G., Gens, R., Pinzon, J. E., Tucker, C. J., Tweedie, C. E., and Webber,
P. J.: Circumpolar Arctic Tundra Vegetation Change Is Linked to Sea Ice
Decline, Earth Interact., 14, 1–20, https://doi.org/10.1175/2010EI315.1, 2010.
Bintanja, R. and Selten, F. M.: Future increases in Arctic precipitation
linked to local evaporation and sea-ice retreat, Nature, 509, 479–482,
https://doi.org/10.1038/nature13259, 2014.
Bintanja, R. and Van Der Linden, E. C.: The changing seasonal climate in the
Arctic, Sci. Rep., 3, 1556, https://doi.org/10.1038/srep01556, 2013.
Cappelen, J., Jørgensen, B. V., Laursen, E. V., Stannius, L. S., and Thomsen, R. S.: The Observed Climate of Greenland, 1958–99 – with Climatological Standard Normals, 1961–90, Danish Meteorological Institute, Technical Report, 1–152, https://www.dmi.dk/fileadmin/user_upload/Rapporter/TR/2000/tr00-18.pdf (last access: 1 January 2018), 2001.
Celisse, A., Marot, G., Pierre-Jean, M., and Rigaill, G. J.: New efficient
algorithms for multiple change-point detection with reproducing kernels,
Comput. Stat. Data Anal., 128, 200–220, https://doi.org/10.1016/j.csda.2018.07.002, 2018.
Cho, H., Kug, J.-S., and Jun, S.-Y.: Influence of the recent winter Arctic
sea ice loss in short-term simulations of a regional atmospheric model, Sci.
Rep., 12, 8901, https://doi.org/10.1038/s41598-022-12783-4, 2022.
Chutko, K. J. and Lamoureux, S. F.: The influence of low-level thermal inversions on estimated melt-season characteristics in the central Canadian
Arctic, Int. J. Climatol., 29, 259–268, https://doi.org/10.1002/joc.1722, 2009.
Citterio, M., Sejr, M. K., Langen, P. L., Mottram, R. H., Abermann, J., Hillerup Larsen, S., Skov, K., and Lund, M.: Towards quantifying the glacial
runoff signal in the freshwater input to Tyrolerfjord–Young Sound, NE Greenland, Ambio, 46, 146–159, https://doi.org/10.1007/s13280-016-0876-4, 2017.
Comiso, J. C.: Correlation and trend studies of the sea-ice cover and surface temperatures in the Arctic, Ann. Glaciol., 34, 420–428,
https://doi.org/10.3189/172756402781818067, 2002.
Cullen, R. M. and Marshall, S. J.: Mesoscale Temperature Patterns in the
Rocky Mountains and Foothills Region of Southern Alberta, Atmos.-Ocean, 49, 189–205, https://doi.org/10.1080/07055900.2011.592130, 2011.
de Boer, G., Houston, A., Jacob, J., Chilson, P. B., Smith, S. W., Argrow,
B., Lawrence, D., Elston, J., Brus, D., Kemppinen, O., Klein, P., Lundquist,
J. K., Waugh, S., Bailey, S. C. C., Frazier, A., Sama, M. P., Crick, C.,
Schmale III, D., Pinto, J., Pillar-Little, E. A., Natalie, V., and Jensen, A.: Data generated during the 2018 LAPSE-RATE campaign: an introduction and
overview, Earth Syst. Sci. Data, 12, 3357–3366, https://doi.org/10.5194/essd-12-3357-2020, 2020.
Delhasse, A., Kittel, C., Amory, C., Hofer, S., van As, D., Fausto, R. S.,
and Fettweis, X.: Brief communication: Evaluation of the near-surface climate in ERA5 over the Greenland Ice Sheet, The Cryosphere, 14, 957–965,
https://doi.org/10.5194/tc-14-957-2020, 2020.
Deser, C., Walsh, J. E., and Timlin, M. S.: Arctic Sea Ice Variability in
the Context of Recent Atmospheric Circulation Trends, J. Climate, 13, 617–633, https://doi.org/10.1175/1520-0442(2000)013<0617:ASIVIT>2.0.CO;2, 2000.
Dickey, D. A. and Fuller, W. A.: Distribution of the Estimators for Autoregressive Time Series with a Unit Root, J. Am. Stat. Assoc., 74, 427–431, https://doi.org/10.1080/01621459.1979.10482531, 1979.
Ding, Q., Schweiger, A., L'Heureux, M., Battisti, D. S., Po-Chedley, S.,
Johnson, N. C., Blanchard-Wrigglesworth, E., Harnos, K., Zhang, Q., Eastman,
R., and Steig, E. J.: Influence of high-latitude atmospheric circulation
changes on summertime Arctic sea ice, Nat. Clim. Change, 7, 289–295,
https://doi.org/10.1038/nclimate3241, 2017.
Djoumna, G., Mernild, S. H., and Holland, D. M.: Meteorological Conditions
and Cloud Effects on Surface Radiation Balance Near Helheim Glacier and
Jakobshavn Isbræ (Greenland) Using Ground-Based Observations, Front. Earth Sci., 8, 616105, https://doi.org/10.3389/feart.2020.616105, 2021.
Elberling, B., Tamstorf, M. P., Michelsen, A., Arndal, M. F., Sigsgaard, C., Illeris, L., Bay, C., Hansen, B. U., Christensen, T. R., Hansen, E. S., Jakobsen, B. H., and Beyens, L.: Soil and Plant Community-Characteristics and Dynamics at Zackenberg, in: Advances in Ecological Research, Vol. 40, Academic Press, 223–248, https://doi.org/10.1016/S0065-2504(07)00010-4, 2008.
European State of the Climate: Sea ice, https://climate.copernicus.eu/ESOTC/2019/sea-ice (last access: 31 March 2022), 2019.
Fausto, R. S., van As, D., Mankoff, K. D., Vandecrux, B., Citterio, M., Ahlstrøm, A. P., Andersen, S. B., Colgan, W., Karlsson, N. B., Kjeldsen, K. K., Korsgaard, N. J., Larsen, S. H., Nielsen, S., Pedersen, A. Ø., Shields, C. L., Solgaard, A. M., and Box, J. E.: Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station data, Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, 2021.
Fettweis, X., Mabille, G., Erpicum, M., Nicolay, S., and Van den Broeke, M.:
The 1958–2009 Greenland ice sheet surface melt and the mid-tropospheric
atmospheric circulation, Clim. Dynam., 36, 139–159, https://doi.org/10.1007/s00382-010-0772-8, 2011.
Fettweis, X., Hanna, E., Lang, C., Belleflamme, A., Erpicum, M., and Gallée, H.: Brief communication “Important role of the mid-tropospheric atmospheric circulation in the recent surface melt increase over the Greenland ice sheet”, The Cryosphere, 7, 241–248, https://doi.org/10.5194/tc-7-241-2013, 2013.
Forbush, S. E., Pomerantz, M. A., Duggal, S. P., and Tsao, C. H.: Statistical considerations in the analysis of solar oscillation data by the superposed epoch method, Sol. Phys., 82, 113–122, https://doi.org/10.1007/BF00145551, 1983.
Francis, J. A., Chan, W., Leathers, D. J., Miller, J. R., and Veron, D. E.:
Winter Northern Hemisphere weather patterns remember summer Arctic sea-ice
extent, Geophys. Res. Lett., 36, L07503, https://doi.org/10.1029/2009GL037274, 2009.
Gao, L., Bernhardt, M., and Schulz, K.: Elevation correction of ERA-Interim
temperature data in complex terrain, Hydrol. Earth Syst. Sci., 16, 4661–4673, https://doi.org/10.5194/hess-16-4661-2012, 2012.
Gardner, A. S., Sharp, M. J., Koerner, R. M., Labine, C., Boon, S., Marshall, S. J., Burgess, D. O., and Lewis, D.: Near-surface temperature lapse rates over arctic glaciers and their implications for temperature downscaling, J. Climate, 22, 4281–4298, https://doi.org/10.1175/2009JCLI2845.1, 2009.
GEM: ClimateBasis Zackenberg – Air temperature – Air temperature, 200 cm @
60 min sample (∘C) (Version 1.0), GEM [data set], https://doi.org/10.17897/XV96-HC57, 2020a.
GEM: GeoBasis Zackenberg – Meteorology – M2 (Version 1.0), GEM [data set],
https://doi.org/10.17897/7WAM-6143, 2020b.
GEM: GeoBasis Zackenberg – Meteorology – M3 (Version 1.0), GEM [data set],
https://doi.org/10.17897/7JXY-VX51, 2020c.
GEM: GeoBasis Zackenberg – Meteorology – M6_60min (Version 1.0), GEM [data set], https://doi.org/10.17897/SEFH-AM39, 2020d.
GEM: GeoBasis Zackenberg – Meteorology – M7 (Version 1.0), GEM [data set],
https://doi.org/10.17897/D081-0X68, 2020e.
GEM: GeoBasis Zackenberg – Meteorology – M8 (Version 1.0), GEM [data set],
https://doi.org/10.17897/1VH5-F517, 2020f.
GEM: GlacioBasis Zackenberg – Near surface weather – AWS-Zack-M (Version 1.0), GEM [data set], https://doi.org/10.17897/KDSV-GH23, 2020g.
GEM: GlacioBasis Zackenberg – Near surface weather – AWS-Zack-S (Version 1.0), GEM [data set], https://doi.org/10.17897/NVJ0-V931, 2020h.
GEM: GlacioBasis Zackenberg – Near surface weather – AWS-Zack-T (Version 1.0), GEM [data set], https://doi.org/10.17897/3MD2-PZ63, 2020i.
GEM: MarineBasis Zackenberg – Sea ice conditions – Sea ice formation
(Version 1.0), GEM [data set], https://doi.org/10.17897/5MNP-KX83, 2020j.
Glickman, T. S.: Glossary of Meteorology, American Meteorological Society,
850 pp., ISBN 9781878220349, 2000.
Goff, J. A. and Gratch, S.: Low-pressure properties of water-from −160 to
212 ∘F, Trans. Am. Heat. Vent. Eng., 52, 95–121, 1946.
Graham, R. M., Hudson, S. R., and Maturilli, M.: Improved Performance of ERA5 in Arctic Gateway Relative to Four Global Atmospheric Reanalyses, Geophys. Res. Lett., 46, 6138–6147, https://doi.org/10.1029/2019GL082781, 2019.
Häkkinen, S., Rhines, P. B., and Worthen, D. L.: Atmospheric Blocking and Atlantic Multidecadal Ocean Variability, Science, 334, 655–659, https://doi.org/10.1126/science.1205683, 2011.
Hanna, E., Jónsson, T., and Box, J. E.: An analysis of Icelandic climate
since the nineteenth century, Int. J. Climatol., 24, 1193–1210, https://doi.org/10.1002/joc.1051, 2004.
Hanna, E., Mernild, S. H., Cappelen, J., and Steffen, K.: Recent warming in
Greenland in a long-term instrumental (1881–2012) climatic context: I. Evaluation of surface air temperature records, Environ. Res. Lett., 7, 45404, https://doi.org/10.1088/1748-9326/7/4/045404, 2012.
Hanna, E., Fettweis, X., Mernild, S. H., Cappelen, J., Ribergaard, M. H.,
Shuman, C. A., Steffen, K., Wood, L., and Mote, T. L.: Atmospheric and oceanic climate forcing of the exceptional Greenland ice sheet surface melt in summer 2012, Int. J. Climatol., 34, 1022–1037, https://doi.org/10.1002/joc.3743, 2014.
Hanna, E., Cropper, T. E., Jones, P. D., Scaife, A. A., and Allan, R.: Recent seasonal asymmetric changes in the NAO (a marked summer decline and increased winter variability) and associated changes in the AO and Greenland Blocking Index, Int. J. Climatol., 35, 2540–2554, https://doi.org/10.1002/joc.4157, 2015.
Hanna, E., Cropper, T. E., Hall, R. J., and Cappelen, J.: Greenland Blocking
Index 1851–2015: a regional climate change signal, Int. J. Climatol., 36, 4847–4861, https://doi.org/10.1002/joc.4673, 2016.
Hanna, E., Cappelen, J., Fettweis, X., Mernild, S. H., Mote, T. L., Mottram,
R., Steffen, K., Ballinger, T. J., and Hall, R. J.: Greenland surface air
temperature changes from 1981 to 2019 and implications for ice-sheet melt and mass-balance change, Int. J. Climatol., 41, E1336–E1352, https://doi.org/10.1002/joc.6771, 2021.
Hansen, B. U., Sigsgaard, C., Rasmussen, L., Cappelen, J., Hinkler, J.,
Mernild, S. H., Petersen, D., Tamstorf, M. P., Rasch, M., and Hasholt, B.:
Present-Day Climate at Zackenberg, in: Advances in Ecological Research, vol. 40, Academic Press, 111–149, https://doi.org/10.1016/S0065-2504(07)00006-2, 2008.
Hemingway, B. L., Frazier, A. E., Elbing, B. R., and Jacob, J. D.: Vertical Sampling Scales for Atmospheric Boundary Layer Measurements from Small Unmanned Aircraft Systems (sUAS), Atmosphere, 8, 176, https://doi.org/10.3390/atmos8090176, 2017.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A.,
Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5
hourly data on pressure levels from 1979 to present, Copernicus Climate
Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.bd0915c6, 2018a.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A.,
Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5
hourly data on single levels from 1979 to present, Copernicus Climate Change
Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.adbb2d47, 2018b.
Hersbach, H., Bell, B., Berrisford, P., Horányi, A., Sabater, J. M.,
Nicolas, J., Radu, R., Schepers, D., Simmons, A., Soci, C., and Dee, D.:
Global reanalysis: goodbye ERA-Interim, hello ERA5, ECMWF Newsletter, ECMWF, 17–24, https://doi.org/10.21957/vf291hehd7, 2019.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay,
P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5
global reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Heynen, M., Miles, E., Ragettli, S., Buri, P., Immerzeel, W. W., and Pellicciotti, F.: Air temperature variability in a high-elevation Himalayan
catchment, Ann. Glaciol., 57, 212–222, https://doi.org/10.3189/2016AoG71A076, 2016.
Hinkler, J.: From digital cameras to large scale sea-ice dynamics. A
snow–ecosystem perspective, PhD thesis, University of Copenhagen, Copenhagen, 184 pp., https://pure.au.dk/portal/en/publications/from-digital-cameras-to-large-scale-seaice-dynamics(209bb1f0-7e9e-11dd-a5a8-000ea68e967b)/export.html (last access: 15 December 2021), 2005.
Hofer, S., Tedstone, A. J., Fettweis, X., and Bamber, J. L.: Decreasing
cloud cover drives the recent mass loss on the Greenland Ice Sheet, Sci. Adv., 3, e1700584, https://doi.org/10.1126/sciadv.1700584, 2017.
Hulth, J., Rolstad, C., Trondsen, K., and Rødby, R. W.: Surface mass and
energy balance of Sørbreen, Jan Mayen, 2008, Ann. Glaciol., 51, 110–119,
https://doi.org/10.3189/172756410791392754, 2010.
InterMet: iMet-XQ2 Second-Generation Atmospheric Sensor for UAV
Deployment, https://www.intermetsystems.com/wp-content/uploads/2022/01/202021_iMet-XQ2_210415.pdf (last access: 10 August 2021), 2021.
Isaksen, K., Nordli, Ø., Ivanov, B., Køltzow, M. A. Ø., Aaboe, S.,
Gjelten, H. M., Mezghani, A., Eastwood, S., Førland, E., Benestad, R. E.,
Hanssen-Bauer, I., Brækkan, R., Sviashchennikov, P., Demin, V., Revina, A., and Karandasheva, T.: Exceptional warming over the Barents area, Sci. Rep., 12, 9371, https://doi.org/10.1038/s41598-022-13568-5, 2022.
Ivanov, V.: Arctic Sea Ice Loss Enhances the Oceanic Contribution to Climate Change, Atmosphere, 14, 409, https://doi.org/10.3390/atmos14020409, 2023.
Jakobson, L., Vihma, T., and Jakobson, E.: Relationships between Sea Ice
Concentration and Wind Speed over the Arctic Ocean during 1979–2015, J.
Climate, 32, 7783–7796, https://doi.org/10.1175/JCLI-D-19-0271.1, 2019.
Jensen, L. M., Christensen, T. R., and Schmidt, N. M.: Zackenberg Ecological Research Operations, 19th Annual Report 2013, DCE – Danish Centre for Environment and Energy, Aarhus University, https://g-e-m.dk/fileadmin/Resources/DMU/GEM/Zackenberg/Nye_Zac_files/ZERO_19th_Annual_Report_2014.pdf (last access: 30 June 2021), 2014.
Jiang, S., Ye, A., and Xiao, C.: The temperature increase in Greenland has
accelerated in the past five years, Global Planet. Change, 194, 103297,
https://doi.org/10.1016/j.gloplacha.2020.103297, 2020.
Khan, S. A., Colgan, W., Neumann, T. A., van den Broeke, M. R., Brunt, K. M., Noël, B., Bamber, J. L., Hassan, J., and Bjørk, A. A.: Accelerating Ice Loss From Peripheral Glaciers in North Greenland, Geophys. Res. Lett., 49, e2022GL098915, https://doi.org/10.1029/2022GL098915, 2022.
Kimball, S. K., Montalvo, C. J., and Mulekar, M. S.: Assessing iMET-XQ Performance and Optimal Placement on a Small Off-the-Shelf, Rotary-Wing UAV, as a Function of Atmospheric Conditions, Atmosphere, 11, 660, https://doi.org/10.3390/atmos11060660, 2020.
Kirchner, M., Faus-Kessler, T., Jakobi, G., Leuchner, M., Ries, L., Scheel,
H.-E., and Suppan, P.: Altitudinal temperature lapse rates in an Alpine valley: trends and the influence of season and weather patterns, Int. J. Climatol., 33, 539–555, https://doi.org/10.1002/joc.3444, 2013.
Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., and Shin, Y.: Testing the
null hypothesis of stationarity against the alternative of a unit root: How
sure are we that economic time series have a unit root?, J. Econ., 54,
159–178, https://doi.org/10.1016/0304-4076(92)90104-Y, 1992.
Laken, B. A. and Čalogović, J.: Composite analysis with Monte Carlo
methods: an example with cosmic rays and clouds, J. Space Weather Space
Clim., 3, A29, https://doi.org/10.1051/swsc/2013051, 2013.
Marshall, S. J., Sharp, M. J., Burgess, D. O., and Anslow, F. S.: Near-surface-temperature lapse rates on the Prince of Wales Icefield, Ellesmere Island, Canada: implications for regional downscaling of temperature, Int. J. Climatol., 27, 385–398, https://doi.org/10.1002/joc.1396, 2007.
McCrystall, M. R., Stroeve, J., Serreze, M., Forbes, B. C., and Screen, J. A.: New climate models reveal faster and larger increases in Arctic precipitation than previously projected, Nat. Commun., 12, 6765,
https://doi.org/10.1038/s41467-021-27031-y, 2021.
Meltofte, H. and Rasch, M.: The Study Area at Zackenberg, in: Advances in
Ecological Research, vol. 40, Academic Press, 101–110,
https://doi.org/10.1016/S0065-2504(07)00005-0, 2008.
Meltofte, H. and Thing, H.: Zackenberg Ecological Research Operations, 1st Annual Report 1995, Danish Polar Center, Ministry of Research & Technology, https://g-e-m.dk/fileadmin/Resources/DMU/GEM/Zackenberg/Nye_Zac_files/ZERO_Annual_Report1995.pdf (last access: 9 March 2022), 1996.
Mernild, S. H. and Liston, G. E.: The Influence of air temperature inversions on snowmelt and glacier mass balance simulations, Ammassalik Island, Southeast Greenland, J. Appl. Meteorol. Clim., 49, 47–67, https://doi.org/10.1175/2009JAMC2065.1, 2010.
Mernild, S. H., Hasholt, B., and Liston, G. E.: Climatic control on river
discharge simulations, Zackenberg River drainage basin, northeast Greenland,
Hydrol. Process., 22, 1932–1948, https://doi.org/10.1002/hyp.6777, 2008.
Mernild, S. H., Hanna, E., Yde, J. C., Cappelen, J., and Malmros, J. K.:
Coastal Greenland air temperature extremes and trends 1890–2010: annual and
monthly analysis, Int. J. Climatol., 34, 1472–1487, https://doi.org/10.1002/joc.3777, 2014.
Minder, J. R., Mote, P. W., and Lundquist, J. D.: Surface temperature lapse rates over complex terrain: Lessons from the Cascade Mountains, J. Geophys. Res., 115, D14122, https://doi.org/10.1029/2009JD013493, 2010.
Müller, M., Kelder, T., and Palerme, C.: Decline of sea-ice in the Greenland Sea intensifies extreme precipitation over Svalbard, Weather Clim. Extrem., 36, 100437, https://doi.org/10.1016/j.wace.2022.100437, 2022.
NSIDC: Arctic sea ice down to second-lowest extent; likely record-low volume, https://nsidc.org/news-analyses/news-stories/arctic-sea-ice-down-second-lowest-extent-likely-record-low-volume (last access: 9 May 2023), 2023.
Nielsen-Englyst, P., Høyer, J. L., Madsen, K. S., Tonboe, R., Dybkjaer, G., and Alerskans, E.: In situ observed relationships between snow and ice
surface skin temperatures and 2 m air temperatures in the Arctic, The Cryosphere, 13, 1005–1024, https://doi.org/10.5194/tc-13-1005-2019, 2019.
Noël, B., Fettweis, X., Van De Berg, W. J., van den Broeke, M. R., and
Erpicum, M.: Sensitivity of Greenland Ice Sheet surface mass balance to
perturbations in sea surface temperature and sea ice cover: a study with the
regional climate model MAR, The Cryosphere, 8, 1871–1883,
https://doi.org/10.5194/tc-8-1871-2014, 2014.
Noël, B., Van De Berg, W. J., Van Meijgaard, E., Kuipers Munneke, P.,
Van De Wal, R. S. W., and Van Den Broeke, M. R.: Evaluation of the updated
regional climate model RACMO2.3: Summer snowfall impact on the Greenland Ice
Sheet, The Cryosphere, 9, 1831–1844, https://doi.org/10.5194/tc-9-1831-2015, 2015.
Noël, B., van de Berg, W. J., Lhermitte, S., Wouters, B., Machguth, H.,
Howat, I., Citterio, M., Moholdt, G., Lenaerts, J. T. M., and van den Broeke, M. R.: A tipping point in refreezing accelerates mass loss of Greenland's glaciers and ice caps, Nat. Commun., 8, 14730, https://doi.org/10.1038/ncomms14730, 2017.
Noël, B., van de Berg, W. J., van Wessem, J. M., van Meijgaard, E., van As, D., Lenaerts, J. T. M., Lhermitte, S., Kuipers Munneke, P., Smeets, C. J. P. P., van Ulft, L. H., van de Wal, R. S. W., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using
RACMO2 – Part 1: Greenland (1958–2016), The Cryosphere, 12, 811–831,
https://doi.org/10.5194/tc-12-811-2018, 2018.
Noël, B., Van De Berg, W. J., Lhermitte, S., and van den Broeke, M. R.:
Rapid ablation zone expansion amplifies north Greenland mass loss, Sci. Adv.,
5, 1–9, https://doi.org/10.1126/sciadv.aaw0123, 2019.
Ohmura, A.: Earth's Surface Energy Balance, Wiley, https://doi.org/10.1002/9781119300762.wsts0127, 2019.
Olesen, J. M., Dupont, Y. L., O'Gorman, E., Ings, T. C., Layer, K., Melián, C. J., Trøjelsgaard, K., Pichler, D. E., Rasmussen, C., and
Woodward, G.: Chapter 1 – From Broadstone to Zackenberg: Space, Time and
Hierarchies in Ecological Networks, in: Ecological Networks, vol. 42, edited
by: Woodward, G. B. T.-A., Academic Press, 1–69,
https://doi.org/10.1016/B978-0-12-381363-3.00001-0, 2010.
Ono, J., Watanabe, M., Komuro, Y., Tatebe, H., and Abe, M.: Enhanced Arctic
warming amplification revealed in a low-emission scenario, Commun. Earth
Environ., 3, 27, https://doi.org/10.1038/s43247-022-00354-4, 2022.
Overland, J. E. and Wang, M.: Large-scale atmospheric circulation changes
are associated with the recent loss of Arctic sea ice, Tellus A, 62, 1–9,
https://doi.org/10.1111/j.1600-0870.2009.00421.x, 2010.
Overland, J. E., Francis, J. A., Hanna, E., and Wang, M.: The recent shift in early summer Arctic atmospheric circulation, Geophys. Res. Lett., 39, L19804, https://doi.org/10.1029/2012GL053268, 2012.
Peng, G. and Meier, W. N.: Temporal and regional variability of Arctic sea-ice coverage from satellite data, Ann. Glaciol., 59, 191–200,
https://doi.org/10.1017/aog.2017.32, 2018.
Pepin, N.: Lapse rate changes in northern England, Theor. Appl. Climatol., 68, 1–16, https://doi.org/10.1007/s007040170049, 2001.
Pepin, N. and Losleben, M.: Climate change in the Colorado Rocky Mountains:
free air versus surface temperature trends, Int. J. Climatol., 22, 311–329, https://doi.org/10.1002/joc.740, 2002.
Pepin, N. C. and Seidel, D. J.: A global comparison of surface
and free-air temperatures at high elevations, J. Geophys. Res.-Atmos., 110, D03104, https://doi.org/10.1029/2004JD005047, 2005.
Pepin, N. C., Arnone, E., Gobiet, A., Haslinger, K., Kotlarski, S., Notarnicola, C., Palazzi, E., Seibert, P., Serafin, S., Schöner, W.,
Terzago, S., Thornton, J. M., Vuille, M., and Adler, C.: Climate Changes and
Their Elevational Patterns in the Mountains of the World, Rev. Geophys., 60, e2020RG000730, https://doi.org/10.1029/2020RG000730, 2022.
Perovich, D. K., Meier, W., Tschudi, M., Gerland, S., and Richter-Menge, J.: [The Arctic] Sea ice cover [in “State of the Climate in 2012”], B. Am. Meteorol. Soc., 94, 126–127, 2013.
Phillips, P. C. B. and Perron, P.: Testing for a unit root in time series
regression, Biometrika, 75, 335–346, https://doi.org/10.1093/biomet/75.2.335, 1988.
Polyakov, I. V, Mayer, M., Tietsche, S., and Karpechko, A. Yu.: Climate Change Fosters Competing Effects of Dynamics and Thermodynamics in Seasonal
Predictability of Arctic Sea Ice, J. Climate, 35, 2849–2865,
https://doi.org/10.1175/JCLI-D-21-0463.1, 2022.
Preece, J. R., Wachowicz, L. J., Mote, T. L., Tedesco, M., and Fettweis, X.:
Summer Greenland Blocking Diversity and Its Impact on the Surface Mass Balance of the Greenland Ice Sheet, J. Geophys. Res.-Atmos., 127, e2021JD035489, https://doi.org/10.1029/2021JD035489, 2022.
Rogers, J. C., Yang, L., and Li, L.: The role of Fram Strait winter cyclones on sea ice flux and on Spitsbergen air temperatures, Geophys. Res. Lett., 32, L06709, https://doi.org/10.1029/2004GL022262, 2005.
Rolland, C.: Spatial and Seasonal Variations of Air Temperature Lapse Rates
in Alpine Regions, J. Climate, 16, 1032–1046,
https://doi.org/10.1175/1520-0442(2003)016<1032:SASVOA>2.0.CO;2, 2003.
Rysgaard, S., Sejr, M. K., Frandsen, E. R., Frederiksen, M., Arendt, K., and Mikkelsen, D. M.: The Zackenberg marine monitoring programme, https://g-e-m.dk/fileadmin/Resources/DMU/GEM/Zackenberg/Nye_Zac_files/MarinBasis_Zac_Manual_2009.pdf (last access: 5 February 2023), 2009.
Said, S. E. and Dickey, D. A.: Testing for unit roots in autoregressive-moving average models of unknown order, Biometrika, 71,
599–607, https://doi.org/10.1093/biomet/71.3.599, 1984.
Savitzky, A. and Golay, M. J. E.: Smoothing and Differentiation of Data by Simplified Least Squares Procedures, Anal. Chem., 36, 1627–1639,
https://doi.org/10.1021/ac60214a047, 1964.
Schuster, L., Maussion, F., Langhamer, L., and Moseley, G. E.: Lagrangian
detection of precipitation moisture sources for an arid region in northeast
Greenland: relations to the North Atlantic Oscillation, sea ice cover, and
temporal trends from 1979 to 2017, Weather Clim. Dynam., 2, 1–17,
https://doi.org/10.5194/wcd-2-1-2021, 2021.
Schweiger, A. J., Lindsay, R. W., Vavrus, S., and Francis, J. A.: Relationships between Arctic sea ice and clouds during autumn, J. Climate, 21, 4799–4810, https://doi.org/10.1175/2008JCLI2156.1, 2008.
Screen, J. A. and Simmonds, I.: The central role of diminishing sea ice in
recent Arctic temperature amplification, Nature, 464, 1334–1337,
https://doi.org/10.1038/nature09051, 2010.
Serreze, M. C. and Barry, R. G.: The Arctic Climate System, in: 2nd Edn.,
Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9781139583817, 2014.
Serreze, M. C., Barrett, A. P., Stroeve, J. C., Kindig, D. N., and Holland, M. M.: The emergence of surface-based Arctic amplification, The Cryosphere, 3, 11–19, https://doi.org/10.5194/tc-3-11-2009, 2009.
Serreze, M. C., Barrett, A. P., and Cassano, J. J.: Circulation and surface controls on the lower tropospheric air temperature field of the Arctic, J. Geophys. Res.-Atmos., 116, D07104, https://doi.org/10.1029/2010JD015127, 2011.
Shahi, S., Abermann, J., Heinrich, G., Prinz, R., and Schöner, W.: Regional variability and trends of temperature inversions in Greenland, J. Climate, 33, 9391–9407, https://doi.org/10.1175/JCLI-D-19-0962.1, 2020.
Shepherd, T. G.: Effects of a warming Arctic, Science, 353, 989–990,
https://doi.org/10.1126/science.aag2349, 2016.
Stendel, M., Christensen, J. H., and Petersen, D.: Arctic Climate and Climate Change with a Focus on Greenland, in: Advances in Ecological Research, vol. 40, Elsevier, 13–43, https://doi.org/10.1016/S0065-2504(07)00002-5, 2008.
Stranne, C., Nilsson, J., Ulfsbo, A., O'Regan, M., Coxall, H. K., Meire, L.,
Muchowski, J., Mayer, L. A., Brüchert, V., Fredriksson, J., Thornton, B., Chawarski, J., West, G., Weidner, E., and Jakobsson, M.: The climate sensitivity of northern Greenland fjords is amplified through sea-ice damming, Commun Earth Environ, 2, 70, https://doi.org/10.1038/s43247-021-00140-8, 2021.
Stroeve, J. and Notz, D.: Changing state of Arctic sea ice across all seasons, Environ. Res. Lett., 13, 103001, https://doi.org/10.1088/1748-9326/aade56, 2018.
Stroeve, J. C., Serreze, M. C., Barrett, A., and Kindig, D. N.: Attribution
of recent changes in autumn cyclone associated precipitation in the Arctic,
Tellus A, 63, 653–663, https://doi.org/10.1111/j.1600-0870.2011.00515.x, 2011.
Stroeve, J. C., Markus, T., Boisvert, L., Miller, J., and Barrett, A.: Changes in Arctic melt season and implications for sea ice loss, Geophys. Res. Lett., 41, 1216–1225, https://doi.org/10.1002/2013GL058951, 2014.
Stroeve, J. C., Mioduszewski, J. R., Rennermalm, A., Boisvert, L. N., Tedesco, M., and Robinson, D.: Investigating the local-scale influence of sea ice on Greenland surface melt, The Cryosphere, 11, 2363–2381,
https://doi.org/10.5194/tc-11-2363-2017, 2017.
Swinbank, W. C.: Long-wave radiation from clear skies, Q. J. Roy. Meteorol. Soc., 89, 339–348, https://doi.org/10.1002/qj.49708938105, 1963.
Thayyen, R. J. and Dimri, A. P.: Slope Environmental Lapse Rate (SELR) of Temperature in the Monsoon Regime of the Western Himalaya, Front. Environ. Sci., 6, 42, https://doi.org/10.3389/fenvs.2018.00042, 2018.
Truong, C., Oudre, L., and Vayatis, N.: Selective review of offline change point detection methods, Signal Process., 167, 107299,
https://doi.org/10.1016/j.sigpro.2019.107299, 2020.
Van As, D.: Warming, glacier melt and surface energy budget from weather
station observations in the melville bay region of northwest greenland, J. Glaciol., 57, 208–220, https://doi.org/10.3189/002214311796405898, 2011.
Van Meijgaard, E., van Ulft, L. H., Van de Berg, W. J., Bosveld, F. C., van den Hurk, B. J. J. M., Lenderink, G., and Siebesma, A. P.: The KNMI regional atmospheric climate model RACMO version 2.1, Technical Report 302, https://cdn.knmi.nl/knmi/pdf/bibliotheek/knmipubTR/TR302.pdf (last access: 14 July 2021), 2008.
Van Tricht, K., Lhermitte, S., Lenaerts, J. T. M., Gorodetskaya, I. V.,
L'Ecuyer, T. S., Noël, B., van den Broeke, M. R., Turner, D. D., and van Lipzig, N. P. M.: Clouds enhance Greenland ice sheet meltwater runoff, Nat. Commun., 7, 10266, https://doi.org/10.1038/ncomms10266, 2016.
Short summary
This study highlights how the sea ice variability in the Greenland Sea affects the terrestrial climate and the surface mass changes of peripheral glaciers of the Zackenberg region (ZR), Northeast Greenland, combining model output and observations. Our results show that the temporal evolution of sea ice influences the climate anomaly magnitude in the ZR. We also found that the changing temperature and precipitation patterns due to sea ice variability can affect the surface mass of the ice cap.
This study highlights how the sea ice variability in the Greenland Sea affects the terrestrial...