Articles | Volume 15, issue 12
https://doi.org/10.5194/essd-15-5467-2023
© 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/essd-15-5467-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
05 Dec 2023
Data description paper |
| 05 Dec 2023
| 05 Dec 2023
The historical Greenland Climate Network (GC-Net) curated and augmented level-1 dataset
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, 1350, Denmark
Jason E. Box
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, 1350, Denmark
Andreas P. Ahlstrøm
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, 1350, Denmark
Signe B. Andersen
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, 1350, Denmark
Nicolas Bayou
UNAVCO, Boulder, CO 80301, USA
William T. Colgan
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, 1350, Denmark
Nicolas J. Cullen
School of Geography, University of Otago, Te Whare Wānanga o Otāgo, Dunedin, 9016, New Zealand
Robert S. Fausto
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, 1350, Denmark
Dominik Haas-Artho
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, 8903, Switzerland
Achim Heilig
Department of Earth and Environmental Sciences, Ludwig Maximilian University, Munich 80539, Germany
Derek A. Houtz
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, 8903, Switzerland
Penelope How
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, 1350, Denmark
Ionut Iosifescu Enescu
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, 8903, Switzerland
Nanna B. Karlsson
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, 1350, Denmark
Rebecca Kurup Buchholz
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, 8903, Switzerland
Kenneth D. Mankoff
Autonomic Integra LLC, New York, NY 10025, USA
NASA Goddard Institute for Space Studies, New York, NY 10025, USA
Daniel McGrath
Department of Geosciences, Colorado State University, Fort Collins, CO 80523, USA
Noah P. Molotch
Institute of Arctic and Alpine Research, University of Colorado Boulder, Boulder, CO 80303, USA
Bianca Perren
British Antarctic Survey, Cambridge, CB3 0ET, UK
Maiken K. Revheim
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, 1350, Denmark
Anja Rutishauser
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, 1350, Denmark
Kevin Sampson
National Center for Atmospheric Research, Boulder, Colorado, CO 80305, USA
Martin Schneebeli
WSL Institute for Snow and Avalanche Research SLF, Davos, 7260, Switzerland
Sandy Starkweather
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder CO, 80309, USA
National Oceanic and Atmospheric Administration, Boulder, CO 80305, USA
Simon Steffen
Earthanme, Zurich, 8057, Switzerland
Jeff Weber
Unidata Program Center, University Corporation for Atmospheric Research, Boulder, CO 80301, USA
Patrick J. Wright
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, 1350, Denmark
Henry Jay Zwally
Earth System Interdisciplinary Science Center (ESSIC), University of Maryland, College Park, MD 20742, USA
Konrad Steffen
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, 8903, Switzerland
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder CO, 80309, USA
deceased
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Kajsa Holland-Goon, Randall Bonnell, Daniel McGrath, W. Brad Baxter, Tate Meehan, Ryan Webb, Chris Larsen, Hans-Peter Marshall, Megan Mason, and Carrie Vuyovich
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Josephine Yolanda Lindsey-Clark, Aslak Grinsted, Baptiste Vandecrux, and Christine Schøtt Hvidberg
EGUsphere, https://doi.org/10.5194/egusphere-2025-2516, https://doi.org/10.5194/egusphere-2025-2516, 2025
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Earth Syst. Sci. Data, 17, 3047–3071, https://doi.org/10.5194/essd-17-3047-2025, https://doi.org/10.5194/essd-17-3047-2025, 2025
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Rajesh Kumar, Piyush Bhardwaj, Cenlin He, Jennifer Boehnert, Forrest Lacey, Stefano Alessandrini, Kevin Sampson, Matthew Casali, Scott Swerdlin, Olga Wilhelmi, Gabriele G. Pfister, Benjamin Gaubert, and Helen Worden
Earth Syst. Sci. Data, 17, 1807–1834, https://doi.org/10.5194/essd-17-1807-2025, https://doi.org/10.5194/essd-17-1807-2025, 2025
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Kirk M. Scanlan, Anja Rutishauser, and Sebastian B. Simonsen
The Cryosphere, 19, 1221–1239, https://doi.org/10.5194/tc-19-1221-2025, https://doi.org/10.5194/tc-19-1221-2025, 2025
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Ida Haven, Hans Christian Steen-Larsen, Laura J. Dietrich, Sonja Wahl, Jason E. Box, Michiel R. Van den Broeke, Alun Hubbard, Stephan T. Kral, Joachim Reuder, and Maurice Van Tiggelen
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Mai Winstrup, Heidi Ranndal, Signe Hillerup Larsen, Sebastian B. Simonsen, Kenneth D. Mankoff, Robert S. Fausto, and Louise Sandberg Sørensen
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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Arezoo Rafieeinasab, Amir Mazrooei, Thomas Enzminger, Ishita Srivastava, Aubrey Dugger, David Gochis, Nina Omani, Joe Grim, Kevin Sampson, Yongxin Zhang, Jacob LaFontaine, Roland Viger, Yuqiong Liu, and Tim Schneider
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-262, https://doi.org/10.5194/hess-2024-262, 2024
Manuscript not accepted for further review
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Integrated Water Availability Assessments is a national initiative to characterize water availability in the U.S. The WRF-Hydro model is used to generate an estimate of hydrological fluxes and storage across the conterminous United States. The streamflow performance is reasonable especially in the eastern and western U.S. Model performance in estimating snow, evapotranspiration and soil moisture is also reasonable with some differences against the verification datasets in certain areas.
Cecile B. Menard, Sirpa Rasmus, Ioanna Merkouriadi, Gianpaolo Balsamo, Annett Bartsch, Chris Derksen, Florent Domine, Marie Dumont, Dorothee Ehrich, Richard Essery, Bruce C. Forbes, Gerhard Krinner, David Lawrence, Glen Liston, Heidrun Matthes, Nick Rutter, Melody Sandells, Martin Schneebeli, and Sari Stark
The Cryosphere, 18, 4671–4686, https://doi.org/10.5194/tc-18-4671-2024, https://doi.org/10.5194/tc-18-4671-2024, 2024
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Signe Hillerup Larsen, Daniel Binder, Anja Rutishauser, Bernhard Hynek, Robert Schjøtt Fausto, and Michele Citterio
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 Greenland Ecosystem Monitoring programme has been running since 1995. In 2008, the Glaciological monitoring sub-program GlacioBasis was initiated at the Zackenberg site in northeast Greenland, with a transect of three weather stations on the A. P. Olsen Ice Cap. In 2022, the weather stations were replaced with a more standardized set up. Here, we provide the reprocessed and quality-checked data from 2008 to 2022, i.e., the first 15 years of continued monitoring.
Randall Bonnell, Daniel McGrath, Jack Tarricone, Hans-Peter Marshall, Ella Bump, Caroline Duncan, Stephanie Kampf, Yunling Lou, Alex Olsen-Mikitowicz, Megan Sears, Keith Williams, Lucas Zeller, and Yang Zheng
The Cryosphere, 18, 3765–3785, https://doi.org/10.5194/tc-18-3765-2024, https://doi.org/10.5194/tc-18-3765-2024, 2024
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Snow provides water for billions of people, but the amount of snow is difficult to detect remotely. During the 2020 and 2021 winters, a radar was flown over mountains in Colorado, USA, to measure the amount of snow on the ground, while our team collected ground observations to test the radar technique’s capabilities. The technique yielded accurate measurements of the snowpack that had good correlation with ground measurements, making it a promising application for the upcoming NISAR satellite.
Siobhan F. Killingbeck, Anja Rutishauser, Martyn J. Unsworth, Ashley Dubnick, Alison S. Criscitiello, James Killingbeck, Christine F. Dow, Tim Hill, Adam D. Booth, Brittany Main, and Eric Brossier
The Cryosphere, 18, 3699–3722, https://doi.org/10.5194/tc-18-3699-2024, https://doi.org/10.5194/tc-18-3699-2024, 2024
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A subglacial lake was proposed to exist beneath Devon Ice Cap in the Canadian Arctic based on the analysis of airborne data. Our study presents a new interpretation of the subglacial material beneath the Devon Ice Cap from surface-based geophysical data. We show that there is no evidence of subglacial water, and the subglacial lake has likely been misidentified. Re-evaluation of the airborne data shows that overestimation of a critical processing parameter has likely occurred in prior studies.
Tate G. Meehan, Ahmad Hojatimalekshah, Hans-Peter Marshall, Elias J. Deeb, Shad O'Neel, Daniel McGrath, Ryan W. Webb, Randall Bonnell, Mark S. Raleigh, Christopher Hiemstra, and Kelly Elder
The Cryosphere, 18, 3253–3276, https://doi.org/10.5194/tc-18-3253-2024, https://doi.org/10.5194/tc-18-3253-2024, 2024
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Snow water equivalent (SWE) is a critical parameter for yearly water supply forecasting and can be calculated by multiplying the snow depth by the snow density. We combined high-spatial-resolution snow depth information with ground-based radar measurements to solve for snow density. Extrapolated density estimates over our study area resolved detailed patterns that agree with the known interactions of snow with wind, terrain, and vegetation and were utilized in the calculation of SWE.
Nanna B. Karlsson, Dustin M. Schroeder, Louise Sandberg Sørensen, Winnie Chu, Jørgen Dall, Natalia H. Andersen, Reese Dobson, Emma J. Mackie, Simon J. Köhn, Jillian E. Steinmetz, Angelo S. Tarzona, Thomas O. Teisberg, and Niels Skou
Earth Syst. Sci. Data, 16, 3333–3344, https://doi.org/10.5194/essd-16-3333-2024, https://doi.org/10.5194/essd-16-3333-2024, 2024
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In the 1970s, more than 177 000 km of observations were acquired from airborne radar over the Greenland ice sheet. The radar data contain information on not only the thickness of the ice, but also the properties of the ice itself. This information was recorded on film rolls and subsequently stored. In this study, we document the digitization of these film rolls that shed new and unprecedented detailed light on the Greenland ice sheet 50 years ago.
Anja Rutishauser, Kirk M. Scanlan, Baptiste Vandecrux, Nanna B. Karlsson, Nicolas Jullien, Andreas P. Ahlstrøm, Robert S. Fausto, and Penelope How
The Cryosphere, 18, 2455–2472, https://doi.org/10.5194/tc-18-2455-2024, https://doi.org/10.5194/tc-18-2455-2024, 2024
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The Greenland Ice Sheet interior is covered by a layer of firn, which is important for surface meltwater runoff and contributions to global sea-level rise. Here, we combine airborne radar sounding and laser altimetry measurements to delineate vertically homogeneous and heterogeneous firn. Our results reveal changes in firn between 2011–2019, aligning well with known climatic events. This approach can be used to outline firn areas primed for significantly changing future meltwater runoff.
Moein Mellat, Amy R. Macfarlane, Camilla F. Brunello, Martin Werner, Martin Schneebeli, Ruzica Dadic, Stefanie Arndt, Kaisa-Riikka Mustonen, Jeffrey M. Welker, and Hanno Meyer
EGUsphere, https://doi.org/10.5194/egusphere-2024-719, https://doi.org/10.5194/egusphere-2024-719, 2024
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Our research, utilizing data from the Arctic MOSAiC expedition, reveals how snow on Arctic sea ice changes due to weather conditions. By analyzing snow samples collected over a year, we found differences in snow layers that tell us about their origins and how they've been affected by the environment. We discovered variations in snow and vapour that reflect the influence of weather patterns and surface processes like wind and sublimation.
Alton C. Byers, Marcelo Somos-Valenzuela, Dan H. Shugar, Daniel McGrath, Mohan B. Chand, and Ram Avtar
The Cryosphere, 18, 711–717, https://doi.org/10.5194/tc-18-711-2024, https://doi.org/10.5194/tc-18-711-2024, 2024
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In spite of enhanced technologies, many large cryospheric events remain unreported because of their remoteness, inaccessibility, or poor communications. In this Brief communication, we report on a large ice-debris avalanche that occurred sometime between 16 and 21 August 2022 in the Kanchenjunga Conservation Area (KCA), eastern Nepal.
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.
Lucas Zeller, Daniel McGrath, Scott W. McCoy, and Jonathan Jacquet
The Cryosphere, 18, 525–541, https://doi.org/10.5194/tc-18-525-2024, https://doi.org/10.5194/tc-18-525-2024, 2024
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In this study we developed methods for automatically identifying supraglacial lakes in multiple satellite imagery sources for eight glaciers in Nepal. We identified a substantial seasonal variability in lake area, which was as large as the variability seen across entire decades. These complex patterns are not captured in existing regional-scale datasets. Our findings show that this seasonal variability must be accounted for in order to interpret long-term changes in debris-covered glaciers.
Tamara Pletzer, Jonathan P. Conway, Nicolas J. Cullen, Trude Eidhammer, and Marwan Katurji
Hydrol. Earth Syst. Sci., 28, 459–478, https://doi.org/10.5194/hess-28-459-2024, https://doi.org/10.5194/hess-28-459-2024, 2024
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We applied a glacier and hydrology model in the McMurdo Dry Valleys (MDV) to model the start and duration of melt over a summer in this extreme polar desert. To do so, we found it necessary to prevent the drainage of melt into ice and optimize the albedo scheme. We show that simulating albedo (for the first time in the MDV) is critical to modelling the feedbacks of albedo, snowfall and melt in the region. This paper is a first step towards more complex spatial modelling of melt and streamflow.
Louise Sandberg Sørensen, Rasmus Bahbah, Sebastian B. Simonsen, Natalia Havelund Andersen, Jade Bowling, Noel Gourmelen, Alex Horton, Nanna B. Karlsson, Amber Leeson, Jennifer Maddalena, Malcolm McMillan, Anne Solgaard, and Birgit Wessel
The Cryosphere, 18, 505–523, https://doi.org/10.5194/tc-18-505-2024, https://doi.org/10.5194/tc-18-505-2024, 2024
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Under the right topographic and hydrological conditions, lakes may form beneath the large ice sheets. Some of these subglacial lakes are active, meaning that they periodically drain and refill. When a subglacial lake drains rapidly, it may cause the ice surface above to collapse, and here we investigate how to improve the monitoring of active subglacial lakes in Greenland by monitoring how their associated collapse basins change over time.
Tong Zhang, William Colgan, Agnes Wansing, Anja Løkkegaard, Gunter Leguy, William H. Lipscomb, and Cunde Xiao
The Cryosphere, 18, 387–402, https://doi.org/10.5194/tc-18-387-2024, https://doi.org/10.5194/tc-18-387-2024, 2024
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The geothermal heat flux determines how much heat enters from beneath the ice sheet, and thus impacts the temperature and the flow of the ice sheet. In this study we investigate how much geothermal heat flux impacts the initialization of the Greenland ice sheet. We use the Community Ice Sheet Model with two different initialization methods. We find a non-trivial influence of the choice of heat flow boundary conditions on the ice sheet initializations for further designs of ice sheet modeling.
Amy R. Macfarlane, Henning Löwe, Lucille Gimenes, David N. Wagner, Ruzica Dadic, Rafael Ottersberg, Stefan Hämmerle, and Martin Schneebeli
The Cryosphere, 17, 5417–5434, https://doi.org/10.5194/tc-17-5417-2023, https://doi.org/10.5194/tc-17-5417-2023, 2023
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Snow acts as an insulating blanket on Arctic sea ice, keeping the underlying ice "warm", relative to the atmosphere. Knowing the snow's thermal conductivity is essential for understanding winter ice growth. During the MOSAiC expedition, we measured the thermal conductivity of snow. We found spatial and vertical variability to overpower any temporal variability or dependency on underlying ice type and the thermal resistance to be directly influenced by snow height.
Anja Løkkegaard, Kenneth D. Mankoff, Christian Zdanowicz, Gary D. Clow, Martin P. Lüthi, Samuel H. Doyle, Henrik H. Thomsen, David Fisher, Joel Harper, Andy Aschwanden, Bo M. Vinther, Dorthe Dahl-Jensen, Harry Zekollari, Toby Meierbachtol, Ian McDowell, Neil Humphrey, Anne Solgaard, Nanna B. Karlsson, Shfaqat A. Khan, Benjamin Hills, Robert Law, Bryn Hubbard, Poul Christoffersen, Mylène Jacquemart, Julien Seguinot, Robert S. Fausto, and William T. Colgan
The Cryosphere, 17, 3829–3845, https://doi.org/10.5194/tc-17-3829-2023, https://doi.org/10.5194/tc-17-3829-2023, 2023
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This study presents a database compiling 95 ice temperature profiles from the Greenland ice sheet and peripheral ice caps. Ice viscosity and hence ice flow are highly sensitive to ice temperature. To highlight the value of the database in evaluating ice flow simulations, profiles from the Greenland ice sheet are compared to a modeled temperature field. Reoccurring discrepancies between modeled and observed temperatures provide insight on the difficulties faced when simulating ice temperatures.
Julia Kaltenborn, Amy R. Macfarlane, Viviane Clay, and Martin Schneebeli
Geosci. Model Dev., 16, 4521–4550, https://doi.org/10.5194/gmd-16-4521-2023, https://doi.org/10.5194/gmd-16-4521-2023, 2023
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Snow layer segmentation and snow grain classification are essential diagnostic tasks for cryospheric applications. A SnowMicroPen (SMP) can be used to that end; however, the manual classification of its profiles becomes infeasible for large datasets. Here, we evaluate how well machine learning models automate this task. Of the 14 models trained on the MOSAiC SMP dataset, the long short-term memory model performed the best. The findings presented here facilitate and accelerate SMP data analysis.
Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
Earth Syst. Sci. Data, 15, 3075–3094, https://doi.org/10.5194/essd-15-3075-2023, https://doi.org/10.5194/essd-15-3075-2023, 2023
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Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
William Colgan, Christopher Shields, Pavel Talalay, Xiaopeng Fan, Austin P. Lines, Joshua Elliott, Harihar Rajaram, Kenneth Mankoff, Morten Jensen, Mira Backes, Yunchen Liu, Xianzhe Wei, Nanna B. Karlsson, Henrik Spanggård, and Allan Ø. Pedersen
Geosci. Instrum. Method. Data Syst., 12, 121–140, https://doi.org/10.5194/gi-12-121-2023, https://doi.org/10.5194/gi-12-121-2023, 2023
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We describe a new drill for glaciers and ice sheets. Instead of drilling down into the ice, via mechanical action, our drill melts into the ice. Our goal is simply to pull a cable of temperature sensors on a one-way trip down to the ice–bed interface. Here, we describe the design and testing of our drill. Under laboratory conditions, our melt-tip drill has an efficiency of ∼ 35 % with a theoretical maximum penetration rate of ∼ 12 m h−1. Under field conditions, our efficiency is just ∼ 15 %.
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023, https://doi.org/10.5194/tc-17-2211-2023, 2023
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We show that wind redistributes snow on Arctic sea ice, and Ka- and Ku-band radar measurements detect both newly deposited snow and buried snow layers that can affect the accuracy of snow depth estimates on sea ice. Radar, laser, meteorological, and snow data were collected during the MOSAiC expedition. With frequent occurrence of storms in the Arctic, our results show that
wind-redistributed snow needs to be accounted for to improve snow depth estimates on sea ice from satellite radars.
Kristian Chan, Cyril Grima, Anja Rutishauser, Duncan A. Young, Riley Culberg, and Donald D. Blankenship
The Cryosphere, 17, 1839–1852, https://doi.org/10.5194/tc-17-1839-2023, https://doi.org/10.5194/tc-17-1839-2023, 2023
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Climate warming has led to more surface meltwater produced on glaciers that can refreeze in firn to form ice layers. Our work evaluates the use of dual-frequency ice-penetrating radar to characterize these ice layers on the Devon Ice Cap. Results indicate that they are meters thick and widespread, and thus capable of supporting lateral meltwater runoff from the top of ice layers. We find that some of this meltwater runoff could be routed through supraglacial rivers in the ablation zone.
Julia Martin and Martin Schneebeli
The Cryosphere, 17, 1723–1734, https://doi.org/10.5194/tc-17-1723-2023, https://doi.org/10.5194/tc-17-1723-2023, 2023
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The grain size of snow determines how light is reflected and other physical properties. The IceCube measures snow grain size at the specific near-infrared wavelength of 1320 nm. In our study, the preparation of snow samples for the IceCube creates a thin layer of small particles. Comparisons of the grain size with computed tomography, particle counting and numerical simulation confirm the aforementioned observation. We conclude that measurements at this wavelength underestimate the grain size.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
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By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Oliver Wigmore and Noah P. Molotch
Earth Syst. Sci. Data, 15, 1733–1747, https://doi.org/10.5194/essd-15-1733-2023, https://doi.org/10.5194/essd-15-1733-2023, 2023
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We flew a custom-built drone fitted with visible, near-infrared and thermal cameras every week over a summer season at Niwot Ridge in Colorado's alpine tundra. We processed these images into seamless orthomosaics that record changes in snow cover, vegetation health and the movement of water over the land surface. These novel datasets provide a unique centimetre resolution snapshot of ecohydrologic processes, connectivity and spatial and temporal heterogeneity in the alpine zone.
Eva Friis Møller, Asbjørn Christensen, Janus Larsen, Kenneth D. Mankoff, Mads Hvid Ribergaard, Mikael Sejr, Philip Wallhead, and Marie Maar
Ocean Sci., 19, 403–420, https://doi.org/10.5194/os-19-403-2023, https://doi.org/10.5194/os-19-403-2023, 2023
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Melt from the Greenland ice sheet and sea ice both influence light and nutrient availability in the Arctic coastal ocean. We use a 3D coupled hydrodynamic–biogeochemical model to evaluate the relative importance of these processes for timing, distribution, and magnitude of phytoplankton production in Disko Bay, west Greenland. Our study indicates that decreasing sea ice and more freshwater discharge can work synergistically and increase primary productivity of the coastal ocean around Greenland.
Marte G. Hofsteenge, Nicolas J. Cullen, Carleen H. Reijmer, Michiel van den Broeke, Marwan Katurji, and John F. Orwin
The Cryosphere, 16, 5041–5059, https://doi.org/10.5194/tc-16-5041-2022, https://doi.org/10.5194/tc-16-5041-2022, 2022
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In the McMurdo Dry Valleys (MDV), foehn winds can impact glacial meltwater production and the fragile ecosystem that depends on it. We study these dry and warm winds at Joyce Glacier and show they are caused by a different mechanism than that found for nearby valleys, demonstrating the complex interaction of large-scale winds with the mountains in the MDV. We find that foehn winds increase sublimation of ice, increase heating from the atmosphere, and increase the occurrence and rates of melt.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Ruzica Dadic, Philip Rostosky, Michael Gallagher, Robbie Mallett, Andrew Barrett, Stefan Hendricks, Rasmus Tonboe, Michelle McCrystall, Mark Serreze, Linda Thielke, Gunnar Spreen, Thomas Newman, John Yackel, Robert Ricker, Michel Tsamados, Amy Macfarlane, Henna-Reetta Hannula, and Martin Schneebeli
The Cryosphere, 16, 4223–4250, https://doi.org/10.5194/tc-16-4223-2022, https://doi.org/10.5194/tc-16-4223-2022, 2022
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Impacts of rain on snow (ROS) on satellite-retrieved sea ice variables remain to be fully understood. This study evaluates the impacts of ROS over sea ice on active and passive microwave data collected during the 2019–20 MOSAiC expedition. Rainfall and subsequent refreezing of the snowpack significantly altered emitted and backscattered radar energy, laying important groundwork for understanding their impacts on operational satellite retrievals of various sea ice geophysical variables.
Brooke Medley, Thomas A. Neumann, H. Jay Zwally, Benjamin E. Smith, and C. Max Stevens
The Cryosphere, 16, 3971–4011, https://doi.org/10.5194/tc-16-3971-2022, https://doi.org/10.5194/tc-16-3971-2022, 2022
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Satellite altimeters measure the height or volume change over Earth's ice sheets, but in order to understand how that change translates into ice mass, we must account for various processes at the surface. Specifically, snowfall events generate large, transient increases in surface height, yet snow fall has a relatively low density, which means much of that height change is composed of air. This air signal must be removed from the observed height changes before we can assess ice mass change.
Océane Hames, Mahdi Jafari, David Nicholas Wagner, Ian Raphael, David Clemens-Sewall, Chris Polashenski, Matthew D. Shupe, Martin Schneebeli, and Michael Lehning
Geosci. Model Dev., 15, 6429–6449, https://doi.org/10.5194/gmd-15-6429-2022, https://doi.org/10.5194/gmd-15-6429-2022, 2022
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This paper presents an Eulerian–Lagrangian snow transport model implemented in the fluid dynamics software OpenFOAM, which we call snowBedFoam 1.0. We apply this model to reproduce snow deposition on a piece of ridged Arctic sea ice, which was produced during the MOSAiC expedition through scan measurements. The model appears to successfully reproduce the enhanced snow accumulation and deposition patterns, although some quantitative uncertainties were shown.
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.
Aubrey Miller, Pascal Sirguey, Simon Morris, Perry Bartelt, Nicolas Cullen, Todd Redpath, Kevin Thompson, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 22, 2673–2701, https://doi.org/10.5194/nhess-22-2673-2022, https://doi.org/10.5194/nhess-22-2673-2022, 2022
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Natural hazard modelers simulate mass movements to better anticipate the risk to people and infrastructure. These simulations require accurate digital elevation models. We test the sensitivity of a well-established snow avalanche model (RAMMS) to the source and spatial resolution of the elevation model. We find key differences in the digital representation of terrain greatly affect the simulated avalanche results, with implications for hazard planning.
Joseph A. MacGregor, Winnie Chu, William T. Colgan, Mark A. Fahnestock, Denis Felikson, Nanna B. Karlsson, Sophie M. J. Nowicki, and Michael Studinger
The Cryosphere, 16, 3033–3049, https://doi.org/10.5194/tc-16-3033-2022, https://doi.org/10.5194/tc-16-3033-2022, 2022
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Where the bottom of the Greenland Ice Sheet is frozen and where it is thawed is not well known, yet knowing this state is increasingly important to interpret modern changes in ice flow there. We produced a second synthesis of knowledge of the basal thermal state of the ice sheet using airborne and satellite observations and numerical models. About one-third of the ice sheet’s bed is likely thawed; two-fifths is likely frozen; and the remainder is too uncertain to specify.
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.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
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Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
William Colgan, Agnes Wansing, Kenneth Mankoff, Mareen Lösing, John Hopper, Keith Louden, Jörg Ebbing, Flemming G. Christiansen, Thomas Ingeman-Nielsen, Lillemor Claesson Liljedahl, Joseph A. MacGregor, Árni Hjartarson, Stefan Bernstein, Nanna B. Karlsson, Sven Fuchs, Juha Hartikainen, Johan Liakka, Robert S. Fausto, Dorthe Dahl-Jensen, Anders Bjørk, Jens-Ove Naslund, Finn Mørk, Yasmina Martos, Niels Balling, Thomas Funck, Kristian K. Kjeldsen, Dorthe Petersen, Ulrik Gregersen, Gregers Dam, Tove Nielsen, Shfaqat A. Khan, and Anja Løkkegaard
Earth Syst. Sci. Data, 14, 2209–2238, https://doi.org/10.5194/essd-14-2209-2022, https://doi.org/10.5194/essd-14-2209-2022, 2022
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We assemble all available geothermal heat flow measurements collected in and around Greenland into a new database. We use this database of point measurements, in combination with other geophysical datasets, to model geothermal heat flow in and around Greenland. Our geothermal heat flow model is generally cooler than previous models of Greenland, especially in southern Greenland. It does not suggest any high geothermal heat flows resulting from Icelandic plume activity over 50 million years ago.
Michael J. MacFerrin, C. Max Stevens, Baptiste Vandecrux, Edwin D. Waddington, and Waleed Abdalati
Earth Syst. Sci. Data, 14, 955–971, https://doi.org/10.5194/essd-14-955-2022, https://doi.org/10.5194/essd-14-955-2022, 2022
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The vast majority of the Greenland ice sheet's surface is covered by pluriannual snow, also called firn, that accumulates year after year and is compressed into glacial ice. The thickness of the firn layer changes through time and responds to the surface climate. We present continuous measurement of the firn compaction at various depths for eight sites. The dataset will help to evaluate firn models, interpret ice cores, and convert remotely sensed ice sheet surface height change to mass loss.
Anja Rutishauser, Donald D. Blankenship, Duncan A. Young, Natalie S. Wolfenbarger, Lucas H. Beem, Mark L. Skidmore, Ashley Dubnick, and Alison S. Criscitiello
The Cryosphere, 16, 379–395, https://doi.org/10.5194/tc-16-379-2022, https://doi.org/10.5194/tc-16-379-2022, 2022
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Recently, a hypersaline subglacial lake complex was hypothesized to lie beneath Devon Ice Cap, Canadian Arctic. Here, we present results from a follow-on targeted aerogeophysical survey. Our results support the evidence for a hypersaline subglacial lake and reveal an extensive brine network, suggesting more complex subglacial hydrological conditions than previously inferred. This hypersaline system may host microbial habitats, making it a compelling analog for bines on other icy worlds.
Brianna Rick, Daniel McGrath, William Armstrong, and Scott W. McCoy
The Cryosphere, 16, 297–314, https://doi.org/10.5194/tc-16-297-2022, https://doi.org/10.5194/tc-16-297-2022, 2022
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Glacial lakes impact societies as both resources and hazards. Lakes form, grow, and drain as glaciers thin and retreat, and understanding lake evolution is a critical first step in assessing their hazard potential. We map glacial lakes in Alaska between 1984 and 2019. Overall, lakes grew in number and area, though lakes with different damming material (ice, moraine, bedrock) behaved differently. Namely, ice-dammed lakes decreased in number and area, a trend lost if dam type is not considered.
Ionuț Iosifescu Enescu, David Hanimann, Dominik Haas-Artho, Marius Rüetschi, Dirk Nikolaus Karger, Gian-Kasper Plattner, Martin Hägeli, Rebecca Kurup Buchholz, Lucia de Espona, Niklaus E. Zimmermann, and Loïc Pellissier
Abstr. Int. Cartogr. Assoc., 3, 119, https://doi.org/10.5194/ica-abs-3-119-2021, https://doi.org/10.5194/ica-abs-3-119-2021, 2021
Ionuț Iosifescu Enescu, David Hanimann, Dominik Haas-Artho, Marius Rüetschi, Dirk Nikolaus Karger, Gian-Kasper Plattner, Martin Hägeli, Rebecca Kurup Buchholz, Lucia de Espona, Niklaus E. Zimmermann, and Loïc Pellissier
Abstr. Int. Cartogr. Assoc., 3, 120, https://doi.org/10.5194/ica-abs-3-120-2021, https://doi.org/10.5194/ica-abs-3-120-2021, 2021
Kenneth D. Mankoff, Xavier Fettweis, Peter L. Langen, Martin Stendel, Kristian K. Kjeldsen, Nanna B. Karlsson, Brice Noël, Michiel R. van den Broeke, Anne Solgaard, William Colgan, Jason E. Box, Sebastian B. Simonsen, Michalea D. King, Andreas P. Ahlstrøm, Signe Bech Andersen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, https://doi.org/10.5194/essd-13-5001-2021, 2021
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We estimate the daily mass balance and its components (surface, marine, and basal mass balance) for the Greenland ice sheet. Our time series begins in 1840 and has annual resolution through 1985 and then daily from 1986 through next week. Results are operational (updated daily) and provided for the entire ice sheet or by commonly used regions or sectors. This is the first input–output mass balance estimate to include the basal mass balance.
Nicolaj Hansen, Peter L. Langen, Fredrik Boberg, Rene Forsberg, Sebastian B. Simonsen, Peter Thejll, Baptiste Vandecrux, and Ruth Mottram
The Cryosphere, 15, 4315–4333, https://doi.org/10.5194/tc-15-4315-2021, https://doi.org/10.5194/tc-15-4315-2021, 2021
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We have used computer models to estimate the Antarctic surface mass balance (SMB) from 1980 to 2017. Our estimates lies between 2473.5 ± 114.4 Gt per year and 2564.8 ± 113.7 Gt per year. To evaluate our models, we compared the modelled snow temperatures and densities to in situ measurements. We also investigated the spatial distribution of the SMB. It is very important to have estimates of the Antarctic SMB because then it is easier to understand global sea level changes.
Sönke Maus, Martin Schneebeli, and Andreas Wiegmann
The Cryosphere, 15, 4047–4072, https://doi.org/10.5194/tc-15-4047-2021, https://doi.org/10.5194/tc-15-4047-2021, 2021
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As the hydraulic permeability of sea ice is difficult to measure, observations are sparse. The present work presents numerical simulations of the permeability of young sea ice based on a large set of 3D X-ray tomographic images. It extends the relationship between permeability and porosity available so far down to brine porosities near the percolation threshold of a few per cent. Evaluation of pore scales and 3D connectivity provides novel insight into the percolation behaviour of sea ice.
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.
Cited articles
Ahlstrøm, A. P. and PROMICE project team: A new programme for monitoring the mass loss of the Greenland ice sheet, GEUS Bulletin, 15, 61–64, https://doi.org/10.34194/geusb.v15.5045, 2008.
Albert, T. H.: Assessment of glacier mass balances from small tropical glaciers to the large ice sheet of Greenland, PhD Thesis, Florida State University, https://doi.org/10.22008/FK2/DQRE71, 2007.
Anderson, P. S.: A Method for Rescaling Humidity Sensors at Temperatures Well below Freezing, J. Atmos. Ocean. Tech., 11, 1388–1391, https://doi.org/10.1175/1520-0426(1994)011<1388:AMFRHS>2.0.CO;2, 1994.
Anderson, P. S.: Mechanism for the Behavior of Hydroactive Materials Used in Humidity Sensors, J. Atmos. Ocean. Tech., 12, 662–667, https://doi.org/10.1175/1520-0426(1995)012<0662:MFTBOH>2.0.CO;2, 1995.
Andersen, M. L., Larsen, T. B., Nettles, M., Elosegui, P., Van As, D., Hamilton, G. S., Stearns, L. A., Davis, J. L., Ahlstrøm, A. P., de Juan, J., and Ekström, G.: Spatial and temporal melt variability at Helheim Glacier, East Greenland, and its effect on ice dynamics, J. Geophys. Res.-Earth Surf., 115, F04041, https://doi.org/10.1029/2010JF001760, 2010.
Aoki, T., Kuchiki, K., Niwano, M., Kodama, Y., Hosaka, M., and Tanaka, T.: Physically based snow albedo model for calculating broadband albedos and the solar heating profile in snowpack for general circulation models, J. Geophys. Res.-Atmos., 116, D11114, https://doi.org/10.1029/2010JD015507, 2011.
Aoki, T., Matoba, S., Uetake, J., Takeuchi, N., and Motoyama, H.: Field activities of the “Snow Impurity and Glacial Microbe effects on abrupt warming in the Arctic” (SIGMA) Project in Greenland in 2011–2013, B. Glaciol. Res., 32, 3–20, https://doi.org/10.5331/bgr.32.3, 2014.
Bales, R. C., McConnell, J. R., Mosley-Thompson, E., and Csatho, B.: Accumulation over the Greenland ice sheet from historical and recent records, J. Geophys. Res., 106, 33813–33825, https://doi.org/10.1029/2001JD900153, 2001a.
Bales, R. C., Mosley-Thompson, E., and McConnell, J. R.: Variability of accumulation in northwest Greenland over the past 250 years, Geophys. Res. Lett., 28, 2679–2682, https://doi.org/10.1029/2000GL011634, 2001b.
Bayou, N. and Steffen, K.: QCheck: a Matlab package for the processing of GC-Net automated weather station data, GitHub [code], https://github.com/GEUS-Glaciology-and-Climate/GC-Net-Matlab-processing-scripts, last access: 1 March 2023, 2011.
Braithwaite, R., Konzelmann, T., Marty, C., and Olesen, O.: Errors in daily ablation measurements in northern Greenland, 1993–94, and their implications for glacier climate studies, J. Glaciol., 44, 583–588, https://doi.org/10.3189/S0022143000002094, 1998.
Box, J. E. and Steffen, K.: Sublimation on the Greenland ice sheet from automated weather station observations, J. Geophys. Res.-Atmos., 106, 33965–33981, https://doi.org/10.1029/2001JD900219, 2001a.
Box, J. E. and Steffen, K.: FORTRAN and IDL processing scripts for the historical GC-Net data, GitHub [code], https://github.com/GEUS-Glaciology-and-Climate/JEB_GC-Net, last access: 1 March 2023, 2001b.
Box, J. E., Stroeve, J. C., and Abdalati, W.: Steffen, K., Abdalati, W., and Stroeve, J.: Climate sensitivity studies of the Greenland ice sheet using satellite AVHRR, SMMR SSM/I and in situ data, Meteorol. Atmos. Phys., 51, 239–258, https://doi.org/10.1007/bf01030497, 1993., Prog. Phys. Geogr.-Earth Environ., 45, 632–638, https://doi.org/10.1177/03091333211011368, 2021.
Box, J. E., Revheim, M., and Vandecrux, B.: GCNet_photogrammetry: GC-Net weather station geometry from field picture photogrammetry (Version v1), Zenodo [code], https://doi.org/10.5281/zenodo.7729252, 2023a.
Box, J. E., Vandecrux, B., Houtz, D., and Steffen, K.: GC-Net historical photo archive, Zenodo [data set], https://doi.org/10.5281/zenodo.7839788, 2023b.
Bromwich, D. H., Robasky, F. M., Keen, R. A., and Bolzan, J. F.: Modeled Variations of Precipitation over the Greenland Ice Sheet, J. Climate, 6, 1253–1268, https://doi.org/10.1175/1520-0442(1993)006<1253:MVOPOT>2.0.CO;2, 1993.
Brotzge, J. A. and Duchon, C. E.: A Field Comparison among a Domeless Net Radiometer, Two Four-Component Net Radiometers, and a Domed Net Radiometer, J. Atmos. Ocean. Tech., 17, 1569–1582, https://doi.org/10.1175/1520-0426(2000)017<1569:AFCAAD>2.0.CO;2. 2000.
Campbell Scientific: Q-7.1 Net Radiometer, Instruction Manual, https://s.campbellsci.com/documents/us/manuals/q-7-1.pdf (last access: 28 February 2023), 1996.
Campbell Scientific: SR50 Sonic Ranging Sensor, Instruction Manual, https://s.campbellsci.com/documents/au/manuals/sr50.pdf (last access: 28 February 2023), 2007.
Cathles, L. M., Cathles, L. M., and Albert, M. R.: A physically based method for correcting temperature profile measurements made using thermocouples, J. Glaciol., 53, 298–304, https://doi.org/10.3189/172756507782202892, 2007.
Citterio, M., Mottram, R., Hillerup Larsen, S., and Ahlstrøm, A.: Glaciological investigations at the Malmbjerg mining prospect, central East Greenland. GEUS Bulletin, 17, 73–76, https://doi.org/10.34194/geusb.v17.5018, 2009.
Covi, F., Hock, R., Reijmer, C. H.: Challenges in modeling the energy balance and melt in the percolation zone of the Greenland ice sheet, J. Glaciol., 69, 164–178, https://doi.org/10.1017/jog.2022.54, 2022.
Cullen, N. J., Mölg, T., Conway, J., and Steffen, K.: Assessing the role of sublimation in the dry snow zone of the Greenland ice sheet in a warming world, J. Geophys. Res.-Atmos., 119, 6563–6577, https://doi.org/10.1002/2014JD021557, 2014.
Dahl-Jensen, D., Gundestrup, N. S., Miller, H., Watanabe, O., Johnsen, S. J., Steffensen, J. P., Clausen, H. B., Svensson, A., and Larsen, L. B.: The NorthGRIP deep drilling programme, Ann. Glaciol., 35, 1–4, https://doi.org/10.3189/172756402781817275, 2002.
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.
Finsterwalder, R.: Expédition Glaciologique Internationale Au Groenland 1957–60 (E.G.I.G.), J. Glaciol., 3, 542–546, https://doi.org/10.3189/S0022143000017299, 1959.
Fristrup, B.: Overvintringsstationer på indlandsisen – III. Amerikanske permanente stationer m.v, Tidsskriftet Grønland, 321–344, 1962.
Genthon, C., Six, D., Favier, V., Lazzara, M., and Keller, L.: Atmospheric Temperature Measurement Biases on the Antarctic Plateau, J. Atmos. Ocean. Tech., 28, 1598–1605, https://doi.org/10.1175/JTECH-D-11-00095.1, 2011.
GEUS: GEUS takes over American climate stations on the Greenland ice sheet, https://eng.geus.dk/about/news/news-archive/2020/december/geus-takes-over-american-climate-stations-on-the-greenland-ice-sheet (last access: 30 November 2023), 2020.
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.
Greuell, W. and Konzelmann, T.: Numerical modelling of the energy balance and the englacial temperature of the Greenland Ice Sheet. Calculations for the ETH-Camp location (West Greenland, 1155 m asl), Global Planet. Change, 9, 91–114, https://doi.org/10.1016/0921-8181(94)90010-8, 1994.
Hahn, L. C., Storelvmo, T., Hofer, S., Parfitt, R., and Ummenhofer, C. C.: Importance of orography for Greenland cloud and melt response to atmospheric blocking, J. Climate, 33, 4187–4206, https://doi.org/10.1175/jcli-d-19-0527.1, 2020.
Hamilton, G. S. and Whillans, I. M.: Point measurements of mass balance of the Greenland Ice Sheet using precision vertical Global Positioning System (GPS) surveys, J. Geophys. Res., 105, 16295–16301, https://doi.org/10.1029/2000JB900102, 2000.
He, F. and Clark, P. U.: Freshwater forcing of the Atlantic Meridional Overturning Circulation revisited, Nat. Clim. Chang., 12, 449–454, https://doi.org/10.1038/s41558-022-01328-2, 2022.
Heinemann, G.: The KABEG'97 field experiment: An aircraft-based study of katabatic wind dynamics over the Greenland ice sheet, Bound.-Lay. Meteorol., 93, 75–116, https://doi.org/10.1023/A:1002009530877, 1999.
How, P., Abermann, J., Ahlstrøm, A. P., Andersen, S. B., Box, J. E., Citterio, M., Colgan, W. T., Fausto, R. S., Karlsson, N. B., Jakobsen, J., Langley, K., Larsen, S. H., Mankoff, K. D., Pedersen, A. Ø., Rutishauser, A., Shield, C. L., Solgaard, A. M., van As, D., Vandecrux, B., and Wright, P. J.: PROMICE and GC-Net automated weather station data in Greenland, V8, GEUS Dataverse [data set], https://doi.org/10.22008/FK2/IW73UU, 2022a.
How, P., Mankoff, K. D., Wright, P. J., and Vandecrux, B.: pypromice, V1, GEUS Dataverse [data set], https://doi.org/10.22008/FK2/3TSBF0, 2022b.
Iosifescu Enescu, I., Bavay, M., and Mankoff, K.: Non-Binary Environmental Archive Data (NEAD) format, EnviDat [data set], https://doi.org/10.16904/envidat.187, 2020.
Jensen, C. D.: Weather Observations from Greenland 1958–2021 – Observational Data with Description, DMI Report 22-08, https://www.dmi.dk/fileadmin/Rapporter/2022/DMIRep22-08.pdf (last access: 30 November 2023), 2022.
Kendrick, A. K., Schroeder, D. M., Chu, W., Young, T. J., Christoffersen, P., Todd, J., Doyle, S. H., Box, J. E., Hubbard, A., Hubbard, B., Brennan, P. V., Nicholls, K. W., and Lok, L. B.: Surface meltwater impounded by seasonal englacial storage in West Greenland, Geophys. Res. Lett., 45, 10474–10481, https://doi.org/10.1029/2018GL079787, 2018.
Kipp & Zonen, NR Lite 2 Net Radiometer Instruction Sheet, https://www.kippzonen.com/Download/335/Instruction-Sheet-Net-Radiometers-NR-Lite2, last access: 28 February 2023.
Konzelmann, T. and Braithwaite, R.: Variations of ablation, albedo and energy balance at the margin of the Greenland ice sheet, Kronprins Christian Land, eastern north Greenland, J. Glaciol., 41, 174–182, https://doi.org/10.3189/S002214300001786X, 1995.
Kuipers Munneke, P., McGrath, D., Medley, B., Luckman, A., Bevan, S., Kulessa, B., Jansen, D., Booth, A., Smeets, P., Hubbard, B., Ashmore, D., Van den Broeke, M., Sevestre, H., Steffen, K., Shepherd, A., and Gourmelen, N.: Observationally constrained surface mass balance of Larsen C ice shelf, Antarctica, The Cryosphere, 11, 2411–2426, https://doi.org/10.5194/tc-11-2411-2017, 2017.
MacFerrin, M. J., Stevens, C. M., Vandecrux, B., Waddington, E. D., and Abdalati, W.: The Greenland Firn Compaction Verification and Reconnaissance (FirnCover) dataset, 2013–2019, Earth Syst. Sci. Data, 14, 955–971, https://doi.org/10.5194/essd-14-955-2022, 2022.
Mankoff, K. and Vandecrux, B.: pyNEAD: Python interface to NEAD file format (Version v1), Zenodo [code], https://doi.org/10.5281/zenodo.7728587, 2023.
Mankoff, K. D., Fettweis, X., Langen, P. L., Stendel, M., Kjeldsen, K. K., Karlsson, N. B., Noël, B., van den Broeke, M. R., Solgaard, A., Colgan, W., Box, J. E., Simonsen, S. B., King, M. D., Ahlstrøm, A. P., Andersen, S. B., and Fausto, R. S.: Greenland ice sheet mass balance from 1840 through next week, Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, 2021.
Matoba, S., Motoyama, H., Fujita, K., Yamasaki, T., Minowa, M., Onuma, Y., Komuro, Y., Aoki, T., Yamaguchi, S., Sugiyama, S., and Enomoto, H.: Glaciological and meteorological observations at the SIGMA-D site, northwestern Greenland Ice Sheet, B. Glaciol. Res., 33, 7–14, https://doi.org/10.5331/bgr.33.7, 2015.
McGrath, D., Colgan, W., Bayou, N., Muto, A., and Steffen, K.: Recent warming at Summit, Greenland: Global context and implications, Geophys. Res. Lett., 40, 2091–2096, https://doi.org/10.1002/grl.50456, 2013.
McGrath, D., Bayou, N., and Steffen, K.: Larsen C automatic weather station data 2008–2011, U.S. Antarctic Program (USAP) Data Center [data set], https://doi.org/10.15784/601445, 2021.
Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E., and Houston, T. G.: An overview of the Global Historical Climatology Network-Daily Database, J. Atmos. Ocean. Tech., 29, 897–910, https://doi.org/10.1175/JTECH-D-11-00103.1, 2012.
Morino, S., Kurita, N., Hirasawa, N., Motoyama, H., Sugiura, K., Lazzara, M., Mikolajczyk, D., Welhouse, L., Keller, L., and Weidner, G.: Comparison of Ventilated and Unventilated Air Temperature Measurements in Inland Dronning Maud Land on the East Antarctic Plateau, J. Atmos. Ocean. Tech., 38, 2061–2070, https://doi.org/10.1175/JTECH-D-21-0107.1, 2021.
Mosley-Thompson, E., McConnell, J. R., Bales, R. C., Li, Z., Lin, P.-N., Steffen, K., Thompson, L. G., Edwards, R., and Bathke, D.: Local to regional-scale variability of annual net accumulation on the Greenland ice sheet from PARCA cores, J. Geophys. Res., 106, 33839–33851, https://doi.org/10.1029/2001JD900067, 2001.
Mosley-Thompson, E., Readinger, C. R., Craigmile, P., Thompson, L. G., and Calder, C. A.: Regional sensitivity of Greenland precipitation to NAO variability, Geophys. Res. Lett., 32, L24707, https://doi.org/10.1029/2005GL024776, 2005.
NEEM team: Eemian interglacial reconstructed from a greenland folded ice core, Nature, 493, 489–494, https://doi.org/10.1038/nature11789, 2013.
Nerem, R. S., Beckley, B. D., Fasullo, J. T., Hamlington, B. D., Masters, D., and Mitchum, G. T.: Climate-change–driven accelerated sea-level rise detected in the altimeter era, P. Natl. Acad. Sci. USA, 115, 2022–2025, https://doi.org/10.1073/pnas.1717312115, 2018.
Nishimura, M., Aoki, T., Niwano, M., Matoba, S., Tanikawa, T., Yamasaki, T., Yamaguchi, S., and Fujita, K.: Quality-controlled meteorological datasets from SIGMA automatic weather stations in northwest Greenland, 2012–2020, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-116, in review, 2023.
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, eaaw0123, https://doi.org/10.1126/sciadv.aaw0123, 2019.
Oerlemans, J. and Vugts, H. F.: A Meteorological Experiment in the Melting Zone of the Greenland Ice Sheet, B. Am. Meteorol. Soc., 74, 355–366, https://doi.org/10.1175/1520-0477(1993)074<0355:AMEITM>2.0.CO;2, 1993.
Ohmura, A., Steffen, K., Blatter, H., Greuell, W., Rotach, M., Konzelmann, T., Laternser, M., Abe-Ouchi, A., and Steiger, D.: Energy and mass balance during the melt season at the equilibrium line altitude, Paakitsoq, Greenland ice sheet. ETH Greenland Expedition Prog. Report no. 1, Dept of Geography, Swiss Fed. Inst, of Technol., Zurich, 1991.
Ohmura, A., Steffen, K., Blatter, H., Greuell, W., Rotach, M., Konzelmann,T., Forrer, J., Abe-Ouchi, A., Steiger.D., Stober, M., and Niederbàumer, G.: Energy and mass balance during the melt season at the equilibrium line altitude, Paakitsoq, Greenland ice sheet. ETH Greenland Expedition Prog. Report no. 2, Dept of Geography, Swiss Fed. Inst, of Technol., Zurich, 1992.
Oksman, M., Kvorning, A. B., Larsen, S. H., Kjeldsen, K. K., Mankoff, K. D., Colgan, W., Andersen, T. J., Nørgaard-Pedersen, N., Seidenkrantz, M.-S., Mikkelsen, N., and Ribeiro, S.: Impact of freshwater runoff from the southwest Greenland Ice Sheet on fjord productivity since the late 19th century, The Cryosphere, 16, 2471–2491, https://doi.org/10.5194/tc-16-2471-2022, 2022.
Olesen, O. and Andreasen, J.-O: Glaciological, glacier-hydrological and climatological investigations around 66∘ N, West Greenland, Rapport Grønlands Geologiske Undersøgelse, 115, 107–111, https://doi.org/10.34194/rapggu.v115.7842, 1983.
Olesen, O. B. and Braithwaite, R. J.: Field stations for glacier-climate research, West Greenland, in:, Glacier fluctuations and climatic change, edited by: Oerlemans, J., Dordrecht, Kluwer Academic Publishers, 207–218, 1989.
Picard, G., Dumont, M., Lamare, M., Tuzet, F., Larue, F., Pirazzini, R., and Arnaud, L.: Spectral albedo measurements over snow-covered slopes: theory and slope effect corrections, The Cryosphere, 14, 1497–1517, https://doi.org/10.5194/tc-14-1497-2020, 2020.
Reeh, N., Thompson, H. H., Higgins, A. K., Weidick, A., and Starzer, W.: Stability conditions of north-east Greenland floating ice margins. In Climate change and sea level: final report of work undertaken for the Commission of the European Communities under contract No. ENV4-CT095-0124, 1 March 1996–28 February 1999, Copenhagen, Danish Polar Center, Report 9, 1999.
Reeh, N., Olesen, O. B., Thomsen, H. H., Starzer, W., and Bøggild, C. E.: Mass balance parameterisation for Hans Tausen Iskappe, Peary Land, North Greenland, in: The Hans Tausen Ice Cap. Glaciology and Glacial Geology, Meddelelser om Grønland, vol. 39, edited by: Hammer, C. U., 57–69, Danish Polar Center, Museum Tusculanum Press, 2001.
Reijmer, C., Kuipers Munneke, P., and Smeets, P.: Helheim firn aquifer weather station data and melt rates, Greenland, 2014–2016, Arctic Data Center [data set], https://doi.org/10.18739/A26D5PB4R, 2019.
Rignot, E. and Steffen, K.: Channelized bottom melting and stability of floating ice shelves, Geophys. Res. Lett., 35, L02503, https://doi.org/10.1029/2007GL031765, 2008.
Ridley, J. K., Huybrechts, P., Gregory, J. M., and Lowe, J. A.: Elimination of the Greenland Ice Sheet in a High CO2 Climate, J. Climate, 18, 3409–3427, https://doi.org/10.1175/JCLI3482.1, 2005.
Samimi, S., Marshall, S. J., Vandecrux, B., and MacFerrin, M.: Time-domain reflectometry measurements and modeling of firn meltwater infiltration at DYE-2, Greenland, J. Geophys. Res.-Earth Surf., 126, e2021JF006295, https://doi.org/10.1029/2021JF006295, 2021.
Sampson, K.: Shallow firn layer climatology derived from greenland climate network automatic weather station data, Master Thesis, Colorado University, https://doi.org/10.13140/RG.2.2.28475.90407, 2009.
Shuman, C. A., Steffen, K., Box, J. E., and Stearns, C. R.: A Dozen Years of Temperature Observations at the Summit: Central Greenland Automatic Weather Stations 1987–99, J. Appl. Meteorol., 40, 741–752, 2001.
Sigl, M., Winstrup, M., McConnell, J. R., Welten, K. C., Plunkett, G., Ludlow, F., Büntgen, U., Caffee, M., Chellman, N., Dahl-Jensen, D., and Fischer, H.: Timing and climate forcing of volcanic eruptions for the past 2,500 years, Nature, 523, 543–549, https://doi.org/10.1038/nature14565, 2015.
Simpson, C. J. W.: The British North Greenland Expedition, Geogr. J., 121, 274–289, https://doi.org/10.2307/1790892, 1955.
Stearns, C. R. and Weidner, G. A.: The polar automatic weather station project of the University of Wisconsin, in: International Conference on the Role of the Polar Regions in Global Change: Proceedings of a conference held 11–15 June 1990, the University of Alaska Fairbanks, vol. 1, edited by: Weller, G., Wilson, C. L., and Severin, B. A. B., 58–62, Geophysical Insti- tute, Univ. Alaska, Fairbanks AK, https://inis.iaea.org/collection/NCLCollectionStore/_Public/24/041/24041533.pdf?r=1 (last access: 30 November 2023), 1991.
Steffen, K.: Surface energy exchange at the equilibrium line on the Greenland ice sheet during onset of melt, Ann. Glaciol., 21, 13–18, https://doi.org/10.3189/S0260305500015536, 1995.
Steffen, K. and Box, J.: Surface climatology of the Greenland Ice Sheet: Greenland Climate Network 1995–1999, J. Geophys. Res., 106, 33951–33964, https://doi.org/10.1029/2001JD900161, 2001.
Steffen, K. and deMaria, T.: Surface Energy Fluxes of Arctic Winter Sea Ice in Barrow Strait, J. Appl. Meteorol. Climatol., 35, 2067–2079, https://doi.org/10.1175/1520-0450(1996)035<2067:SEFOAW>2.0.CO;2, 1996.
Steffen, K., Box, J. E., and Abdalati, W.: Greenland climate network: GC-Net, in: Glaciers, Ice Sheets and Volcanoes: A Tribute to Mark F. Meier, edited by: Colbeck, S., US Army Cold Regions Reattach and Engineering (CRREL), CRREL Special Report, 98–103, https://apps.dtic.mil/sti/citations/ADA321342 (last access: 30 November 2023), 1996.
Steffen, K., Cullen, N., Huff, R., Starkweather, S., Albert, T., and McAllister, M..: Variability and forcing of climate parameters on the greenland ice sheet: greenland climate network (GC-NET), NASA Greenland Progress Report, https://www.researchgate.net/publication/268254712_VARIABILITY_AND_FORCING_OF_CLIMATE_PARAMETERS_ON_THE_GREENLAND_ICE_SHEET_GREENLAND_CLIMATE_NETWORK_GC-NET (last access: 30 November 2023), 2003.
Steffen, K., Cullen, N. Huff, R., Maurer, J., Stober, M., Hepperle, J., and Heise, A.: Variability and forcing of climate parameters on the greenland ice sheet: greenland climate network (GC-NET), NASA Greenland Progress Report, https://www.yumpu.com/en/document/view/22269484/greenland-climate-network-gc-net-hft-stuttgart (last access: 30 November 2023), 2005.
Steffen, K., Huff, R., and Rial, J.: Greenland – accumulation and melt layers: regional climatology, process studies, and seismicity, NASA Greenland Progress Report, https://www.researchgate.net/publication/267206192_GREENLAND_-ACCUMULATION_AND_MELT_LAYERS_REGIONAL_CLIMATOLOGY_PROCESS_STUDIES_AND_SEISMICITY_With_contributions_by (last access: 30 November 2023), 2006.
Steffen, K., Vandecrux, B., Houtz, D., Abdalati, W., Bayou, N., Box, J., Colgan, L., Espona Pernas, L., Griessinger, N., Haas-Artho, D., Heilig, A., Hubert, A., Iosifescu Enescu, I., Johnson-Amin, N., Karlsson, N. B., Kurup Buchholz, R., McGrath, D., Cullen, N. J., Naderpour, R., Molotch, N. P., Pederson, A. Ø., Perren, B., Philipps, T., Plattner, G. K., Proksch, M., Revheim, M. K., Særrelse, M., Schneebli, M., Sampson, K., Starkweather, S., Steffen, S., Stroeve, J., Watler, B., Winton, Ø. A., Zwally, J., and Ahlstrøm, A.: GC-Net Level 1 automated weather station data, V3, GEUS Dataverse [data set], https://doi.org/10.22008/FK2/VVXGUT, 2023.
Stroeve, J., Box, J. E., Wang, Z., Schaaf, C., and Barrett, A.: Re-evaluation of MODIS MCD43 Greenland albedo accuracy and trends, Remote Sens. Environ., 138, 199–214, https://doi.org/10.1016/j.rse.2013.07.023, 2013.
The IMBIE Team: Mass balance of the Greenland Ice Sheet from 1992 to 2018, Nature, 579, 233–239, https://doi.org/10.1038/s41586-019-1855-2, 2020.
Thomas, R., Akins, T., Csatho, B., Fahnestock, M., Gogineni, P., Kim, C., and Sonntag, J.: Mass Balance of the Greenland Ice Sheet at High Elevations, Science, 289, 426–428, https://doi.org/10.1126/science.289.5478.426, 2000.
Thomas, R. H.: Program for Arctic Regional Climate Assessment (PARCA): Goals, key findings, and future directions, J. Geophys. Res., 106, 33691–33705, https://doi.org/10.1029/2001JD900042, 2001.
Thomsen, H. H., Reeh, N., Olesen, O. B., Starzer, W., and Bøggild, C. E.: Bottom melting, surface mass balance and dynamics of floating North-East Greenland ice tongues, Final report, EC Environment and Climate Programme 1994–1998, Copenhagen, https://orbit.dtu.dk/en/publications/bottom-melting-surface-mass-balance-and-dynamics-of-floating-nort-2 (last access: 30 October 2023), 1999.
Toniazzo, T., Gregory, J. M., and Huybrechts, P., P.: Climatic Impact of a Greenland Deglaciation and Its Possible Irreversibility, J. Climate, 17, 21–33, https://doi.org/10.1175/1520-0442(2004)017<0021:CIOAGD>2.0.CO;2, 2004.
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 As, D., Bøggild, C. E., Nielsen, S., Ahlstrøm, A. P., Fausto, R. S., Podlech, S., and Andersen, M. L.: Climatology and ablation at the South Greenland ice sheet margin from automatic weather station observations, The Cryosphere Discuss., 3, 117–158, https://doi.org/10.5194/tcd-3-117-2009, 2009.
Vandecrux, B.: GC-Net evaluation scripts (Version v1), Zenodo [code], https://doi.org/10.5281/zenodo.7728938, 2023.
Vandecrux, B. and Box, J. E.: GC-Net AWS observed and estimated positions (Version v1), Zenodo [data set], https://doi.org/10.5281/zenodo.7829098, 2023.
Vandecrux, B., Fausto, R. S., van As, D., Colgan, W., Langen, P. L., Haubner, K., Ingeman-Nielsen, T., Heilig, A., Stevens, C. M., MacFerrin, M., Niwano, M., Steffen, K., and Box, J. E.: Firn cold content evolution at nine sites on the Greenland ice sheet between 1998 and 2017, J. Glaciol., 66, 591–602, https://doi.org/10.1017/jog.2020.30, 2020.
Vandecrux, B., Box, J., Houtz, D., and Revheim, M. K.: The GC-Net level 1 dataset and processing scripts, GitHub [code], https://github.com/GEUS-Glaciology-and-Climate/GC-Net-level-1-data-processing (last access: 1 March 2023), 2023a.
Vandecrux, B., Houtz, D., and Box, J. E.: GC-Net historical metadata compilation, Zenodo [data set], https://doi.org/10.5281/zenodo.7728549, 2023b.
Van den Broeke, M. R. Duynkerke, P. G., and Oerlemans, J.: The observed katabatic flow at the edge of the Greenland ice sheet during GIMEX-91, Global Planet. Change, 9, 3–15, https://doi.org/10.1016/0921-8181(94)90003-5, 1994.
van den Broeke, M., van As, D., Reijmer, C., and van de Wal, R.: Assessing and Improving the Quality of Unattended Radiation Observations in Antarctica, J. Atmos. Ocean. Tech., 21, 1417–1431, https://doi.org/10.1175/1520-0426(2004)021<1417:AAITQO>2.0.CO;2, 2004.
Van de Wal, R. S. W. and Russell, A. J.: A comparison of energy balance calculations, measured ablation and meltwater runoff near Søndre Strømfjord, West Greenland, Global Planet. Change, 9, 29–38, https://doi.org/10.1016/0921-8181(94)90005-1, 1994.
Wang, W., Zender, C. S., van As, D., Smeets, P. C. J. P., and van den Broeke, M. R.: A Retrospective, Iterative, Geometry-Based (RIGB) tilt-correction method for radiation observed by automatic weather stations on snow-covered surfaces: application to Greenland, The Cryosphere, 10, 727–741, https://doi.org/10.5194/tc-10-727-2016, 2016.
Weidner, G., King, J., Box, J. E., Colwell, S., Jones, P., Lazzara, M., Cappelen, J., Brunet, M., and Cerveny, R. S.: WMO evaluation of northern hemispheric coldest temperature: −69.6 ∘C at Klinck, Greenland, 22 December 1991, Q. J. Roy. Meteor. Soc., 147, 21–29, https://doi.org/10.1002/qj.3901, 2020.
Weidner, G. A. and Stearns, C. R.: A Two-Year Record of the Climate on the Greenland Crest from an Automatic Weather Station, in: International Conference on the Role of the Polar Regions in Global Change: Proceedings of a conference held 11–15 June 1990, University of Alaska Fairbanks, vol. 1, edited by: Weller, G., Wilson, C. L., and Severin, B. A. B., 58–62, Geophysical Institute, Univ. Alaska, Fairbanks AK, 1991.
Weiser, U., Olefs, M., Schöner, W., Weyss, G., and Hynek, B.: Correction of broadband snow albedo measurements affected by unknown slope and sensor tilts, The Cryosphere, 10, 775–790, https://doi.org/10.5194/tc-10-775-2016, 2016.
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J. W., da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., Gonzalez-Beltran, A., Gray, A. J., Groth, P., Goble, C., Grethe, J. S., Heringa, J., 't Hoen, P. A., Hooft, R., Kuhn, T., Kok, R., Kok, J., Lusher, S. J., Martone, M. E., Mons, A., Packer, A. L., Persson, B., Rocca-Serra, P., Roos, M., van Schaik, R., Sansone, S. A., Schultes, E., Sengstag, T., Slater, T., Strawn, G., Swertz, M. A., Thompson, M., van der Lei, J., van Mulligen, E., Velterop, J., Waagmeester, A., Wittenburg, P., Wolstencroft, K., Zhao, J., and Mons, B.: The FAIR Guiding Principles for scientific data management and stewardship, Sci. Data, 3, 160018, https://doi.org/10.1038/sdata.2016.18, 2016.
Zender, C., Wang, W., Laffin, M., and Saini, A.: JAWS: An extensible toolkit to harmonize and analyze polar automatic weather station datasets, University of California, Irvine, GitHub [code], https://github.com/jaws/jaws (last access: 30 November 2023), 2018.
Short summary
The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather...
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