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.
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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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.
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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
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EGUsphere, https://doi.org/10.5194/egusphere-2024-2563, https://doi.org/10.5194/egusphere-2024-2563, 2024
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We used L-band observations from the SMAP mission to quantify the surface and subsurface liquid water amounts (LWA) in the percolation zone of the Greenland ice sheet. The algorithm is described, and the validation results are provided. The results demonstrate the potential for creating an LWA data product across GrIS, which will advance our understanding of ice sheet physical processes for better projection of Greenland’s contribution to global sea level rise.
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
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Robert G. Bingham, Julien A. Bodart, Marie G. P. Cavitte, Ailsa Chung, Rebecca J. Sanderson, Johannes C. R. Sutter, Olaf Eisen, Nanna B. Karlsson, Joseph A. MacGregor, Neil Ross, Duncan A. Young, David W. Ashmore, Andreas Born, Winnie Chu, Xiangbin Cui, Reinhard Drews, Steven Franke, Vikram Goel, John W. Goodge, A. Clara J. Henry, Antoine Hermant, Benjamin H. Hills, Nicholas Holschuh, Michelle R. Koutnik, Gwendolyn J.-M. C. Leysinger Vieli, Emma J. Mackie, Elisa Mantelli, Carlos Martín, Felix S. L. Ng, Falk M. Oraschewski, Felipe Napoleoni, Frédéric Parrenin, Sergey V. Popov, Therese Rieckh, Rebecca Schlegel, Dustin M. Schroeder, Martin J. Siegert, Xueyuan Tang, Thomas O. Teisberg, Kate Winter, Shuai Yan, Harry Davis, Christine F. Dow, Tyler J. Fudge, Tom A. Jordan, Bernd Kulessa, Kenichi Matsuoka, Clara J. Nyqvist, Maryam Rahnemoonfar, Matthew R. Siegfried, Shivangini Singh, Verjan Višnjević, Rodrigo Zamora, and Alexandra Zuhr
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The ice sheets covering Antarctica have built up over millenia through successive snowfall events which become buried and preserved as internal surfaces of equal age detectable with ice-penetrating radar. This paper describes an international initiative to work together on this archival data to build a comprehensive 3-D picture of how old the ice is everywhere across Antarctica, and how this will be used to reconstruct past and predict future ice and climate behaviour.
Kirk M. Scanlan, Anja Rutishauser, and Sebastian B. Simonsen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2832, https://doi.org/10.5194/egusphere-2024-2832, 2024
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In this paper we investigate how to interpret Greenland surface roughness derived from reflected radar altimetry signals. Based on a comparison to conventional laser altimetry results, we 1) define a new mapping between the radar surface echo power strengths and surface roughness and 2) contextualize the horizontal lengths over which this roughness is representative. This work provides critical insight into how these observations integrate into Greenland Ice Sheet mass balance modeling.
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.
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 Discuss., https://doi.org/10.5194/essd-2024-180, https://doi.org/10.5194/essd-2024-180, 2024
Revised manuscript under review for ESSD
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We have created a 14-year hourly air quality dataset at 12 km resolution by combining satellite observations of atmospheric composition with air quality models over the contiguous United States (CONUS) . The dataset has been found to reproduce key observed features of air quality over the CONUS. To enable easy visualization and interpretation of county level air quality measures and trends by stakeholders, an ArcGIS air quality dashboard has also been developed.
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
Preprint archived
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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.
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.
Helle Astrid Kjær, Patrick Zens, Ross Edwards, Martin Olesen, Ruth Mottram, Gabriel Lewis, Christian Terkelsen Holme, Samuel Black, Kasper Holst Lund, Mikkel Schmidt, Dorthe Dahl-Jensen, Bo Vinther, Anders Svensson, Nanna Karlsson, Jason E. Box, Sepp Kipfstuhl, and Paul Vallelonga
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-337, https://doi.org/10.5194/tc-2020-337, 2021
Manuscript not accepted for further review
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We have reconstructed accumulation in 6 firn cores and 8 snow cores in Northern Greenland and compared with a regional Climate model over Greenland. We find the model underestimate precipitation especially in north-eastern part of the ice cap- an important finding if aiming to reconstruct surface mass balance.
Temperatures at 10 meters depth at 6 sites in Greenland were also determined and show a significant warming since the 1990's of 0.9 to 2.5 °C.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Rasmus Tonboe, Stefan Hendricks, Robert Ricker, James Mead, Robbie Mallett, Marcus Huntemann, Polona Itkin, Martin Schneebeli, Daniela Krampe, Gunnar Spreen, Jeremy Wilkinson, Ilkka Matero, Mario Hoppmann, and Michel Tsamados
The Cryosphere, 14, 4405–4426, https://doi.org/10.5194/tc-14-4405-2020, https://doi.org/10.5194/tc-14-4405-2020, 2020
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This study provides a first look at the data collected by a new dual-frequency Ka- and Ku-band in situ radar over winter sea ice in the Arctic Ocean. The instrument shows potential for using both bands to retrieve snow depth over sea ice, as well as sensitivity of the measurements to changing snow and atmospheric conditions.
Seyedhamidreza Mojtabavi, Frank Wilhelms, Eliza Cook, Siwan M. Davies, Giulia Sinnl, Mathias Skov Jensen, Dorthe Dahl-Jensen, Anders Svensson, Bo M. Vinther, Sepp Kipfstuhl, Gwydion Jones, Nanna B. Karlsson, Sergio Henrique Faria, Vasileios Gkinis, Helle Astrid Kjær, Tobias Erhardt, Sarah M. P. Berben, Kerim H. Nisancioglu, Iben Koldtoft, and Sune Olander Rasmussen
Clim. Past, 16, 2359–2380, https://doi.org/10.5194/cp-16-2359-2020, https://doi.org/10.5194/cp-16-2359-2020, 2020
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We present a first chronology for the East Greenland Ice-core Project (EGRIP) over the Holocene and last glacial termination. After field measurements and processing of the ice-core data, the GICC05 timescale is transferred from the NGRIP core to the EGRIP core by means of matching volcanic events and common patterns (381 match points) in the ECM and DEP records. The new timescale is named GICC05-EGRIP-1 and extends back to around 15 kyr b2k.
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.
Jacinta Edebeli, Jürg C. Trachsel, Sven E. Avak, Markus Ammann, Martin Schneebeli, Anja Eichler, and Thorsten Bartels-Rausch
Atmos. Chem. Phys., 20, 13443–13454, https://doi.org/10.5194/acp-20-13443-2020, https://doi.org/10.5194/acp-20-13443-2020, 2020
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Earth’s snow cover is very dynamic and can change its physical properties within hours, as is well known by skiers. Snow is also a well-known host of chemical reactions – the products of which impact air composition and quality. Here, we present laboratory experiments that show how the dynamics of snow make snow essentially inert with respect to gas-phase ozone with time despite its content of reactive chemicals. Impacts on polar atmospheric chemistry are discussed.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
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We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Baptiste Vandecrux, Ruth Mottram, Peter L. Langen, Robert S. Fausto, Martin Olesen, C. Max Stevens, Vincent Verjans, Amber Leeson, Stefan Ligtenberg, Peter Kuipers Munneke, Sergey Marchenko, Ward van Pelt, Colin R. Meyer, Sebastian B. Simonsen, Achim Heilig, Samira Samimi, Shawn Marshall, Horst Machguth, Michael MacFerrin, Masashi Niwano, Olivia Miller, Clifford I. Voss, and Jason E. Box
The Cryosphere, 14, 3785–3810, https://doi.org/10.5194/tc-14-3785-2020, https://doi.org/10.5194/tc-14-3785-2020, 2020
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In the vast interior of the Greenland ice sheet, snow accumulates into a thick and porous layer called firn. Each summer, the firn retains part of the meltwater generated at the surface and buffers sea-level rise. In this study, we compare nine firn models traditionally used to quantify this retention at four sites and evaluate their performance against a set of in situ observations. We highlight limitations of certain model designs and give perspectives for future model development.
Christine S. Hvidberg, Aslak Grinsted, Dorthe Dahl-Jensen, Shfaqat Abbas Khan, Anders Kusk, Jonas Kvist Andersen, Niklas Neckel, Anne Solgaard, Nanna B. Karlsson, Helle Astrid Kjær, and Paul Vallelonga
The Cryosphere, 14, 3487–3502, https://doi.org/10.5194/tc-14-3487-2020, https://doi.org/10.5194/tc-14-3487-2020, 2020
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The Northeast Greenland Ice Stream (NEGIS) extends around 600 km from its onset in the interior of Greenland to the coast. Several maps of surface velocity and topography in Greenland exist, but accuracy is limited due to the lack of validation data. Here we present results from a 5-year GPS survey in an interior section of NEGIS. We use the data to assess a list of satellite-derived ice velocity and surface elevation products and discuss the implications for the ice stream flow in the area.
Angus J. Dowson, Pascal Sirguey, and Nicolas J. Cullen
The Cryosphere, 14, 3425–3448, https://doi.org/10.5194/tc-14-3425-2020, https://doi.org/10.5194/tc-14-3425-2020, 2020
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Satellite observations over 19 years are used to characterise the spatial and temporal variability of surface albedo across the gardens of Eden and Allah, two of New Zealand’s largest ice fields. The variability in response of individual glaciers reveals the role of topographic setting and suggests that glaciers in the Southern Alps do not behave as a single climatic unit. There is evidence that the timing of the minimum surface albedo has shifted to later in the summer on 10 of the 12 glaciers.
Kenneth D. Mankoff, Anne Solgaard, William Colgan, Andreas P. Ahlstrøm, Shfaqat Abbas Khan, and Robert S. Fausto
Earth Syst. Sci. Data, 12, 1367–1383, https://doi.org/10.5194/essd-12-1367-2020, https://doi.org/10.5194/essd-12-1367-2020, 2020
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We have produced an open and reproducible estimate of Greenland Ice Sheet solid ice discharge from 1986 to 2020. Our results show three modes at the the total ice sheet scale: steady discharge from 1986 through 2000, increasing discharge from 2000 through 2005, and steady discharge from 2005 through 2019. The behavior of individual sectors and glaciers is more complicated. This work was done to provide a 100 % reproducible estimate to help constrain mass balance and sea-level-rise estimates.
Neige Calonne, Bettina Richter, Henning Löwe, Cecilia Cetti, Judith ter Schure, Alec Van Herwijnen, Charles Fierz, Matthias Jaggi, and Martin Schneebeli
The Cryosphere, 14, 1829–1848, https://doi.org/10.5194/tc-14-1829-2020, https://doi.org/10.5194/tc-14-1829-2020, 2020
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During winter 2015–2016, the standard program to monitor the structure and stability of the snowpack at Weissflujoch, Swiss Alps, was complemented by additional measurements to compare between various traditional and newly developed techniques. Snow micro-penetrometer measurements allowed monitoring of the evolution of the snowpack's internal structure at a daily resolution throughout the winter. We show the potential of such high-resolution data for detailed evaluations of snowpack models.
Pirmin Philipp Ebner, Aaron Coulin, Joël Borner, Fabian Wolfsperger, Michael Hohl, and Martin Schneebeli
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-56, https://doi.org/10.5194/tc-2020-56, 2020
Revised manuscript not accepted
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These laboratory measurements allow to analyse wet snow and to find the narrow range of the starting point of water percolation in coarse-grained snow. Based on the electrical monitoring a promising perspective for retrieving water content and water distribution in the snowpack is given. The water distribution is analysed using micro-computer tomography to find preferential spots of the accumulated water. These findings are pertinent to the interpretation of the snow melt run-off of spring snow.
Alison Delhasse, Christoph Kittel, Charles Amory, Stefan Hofer, Dirk van As, Robert S. Fausto, and Xavier Fettweis
The Cryosphere, 14, 957–965, https://doi.org/10.5194/tc-14-957-2020, https://doi.org/10.5194/tc-14-957-2020, 2020
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The ERA5 reanalysis of the ECMWF replaced the ERA-Interim in August 2019 and has never been evaluated over Greenland. The aim was to evaluate the performance of ERA5 to simulate the near-surface climate of the Greenland Ice sheet (GrIS) against ERA-Interim and regional climate models with the help of in situ observations from the PROMICE dataset. We also highlighted that polar regional climate models are still a useful tool to study the GrIS climate compared to ERA5.
Achim Heilig, Olaf Eisen, Martin Schneebeli, Michael MacFerrin, C. Max Stevens, Baptiste Vandecrux, and Konrad Steffen
The Cryosphere, 14, 385–402, https://doi.org/10.5194/tc-14-385-2020, https://doi.org/10.5194/tc-14-385-2020, 2020
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We investigate the spatial representativeness of point observations of snow accumulation in SW Greenland. Such analyses have rarely been conducted but are necessary to link regional-scale observations from, e.g., remote-sensing data to firn cores and snow pits. The presented data reveal a low regional variability in density but snow depth can vary significantly. It is necessary to combine pits with spatial snow depth data to increase the regional representativeness of accumulation observations.
Kévin Fourteau, Patricia Martinerie, Xavier Faïn, Christoph F. Schaller, Rebecca J. Tuckwell, Henning Löwe, Laurent Arnaud, Olivier Magand, Elizabeth R. Thomas, Johannes Freitag, Robert Mulvaney, Martin Schneebeli, and Vladimir Ya. Lipenkov
The Cryosphere, 13, 3383–3403, https://doi.org/10.5194/tc-13-3383-2019, https://doi.org/10.5194/tc-13-3383-2019, 2019
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Understanding gas trapping in polar ice is essential to study the relationship between greenhouse gases and past climates. New data of bubble closure, used in a simple gas-trapping model, show inconsistency with the final air content in ice. This suggests gas trapping is not fully understood. We also use a combination of high-resolution measurements to investigate the effect of polar snow stratification on gas trapping and find that all strata have similar pores, but that some close in advance.
Keith S. Jennings and Noah P. Molotch
Hydrol. Earth Syst. Sci., 23, 3765–3786, https://doi.org/10.5194/hess-23-3765-2019, https://doi.org/10.5194/hess-23-3765-2019, 2019
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There is a wide variety of modeling methods to designate precipitation as rain, snow, or a mix of the two. Here we show that method choice introduces marked uncertainty to simulated snowpack water storage (> 200 mm) and snow cover duration (> 1 month) in areas that receive significant winter and spring precipitation at air temperatures at and near freezing. This marked uncertainty has implications for water resources management as well as simulations of past and future hydroclimatic states.
I. Iosifescu Enescu, G-K. Plattner, L. Bont, M. Fraefel, R. Meile, T. Kramer, L. Espona-Pernas, D. Haas-Artho, M. Hägeli, and K. Steffen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W14, 107–110, https://doi.org/10.5194/isprs-archives-XLII-4-W14-107-2019, https://doi.org/10.5194/isprs-archives-XLII-4-W14-107-2019, 2019
Todd A. N. Redpath, Pascal Sirguey, and Nicolas J. Cullen
Hydrol. Earth Syst. Sci., 23, 3189–3217, https://doi.org/10.5194/hess-23-3189-2019, https://doi.org/10.5194/hess-23-3189-2019, 2019
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Spatio-temporal variability of seasonal snow cover is characterised from 16 years of MODIS data for the Clutha Catchment, New Zealand. No trend was detected in snow-covered area. Spatial modes of variability reveal the role of anomalous winter airflow. The sensitivity of snow cover duration to temperature and precipitation variability is found to vary spatially across the catchment. These findings provide new insight into seasonal snow processes in New Zealand and guidance for modelling efforts.
Johannes Sutter, Hubertus Fischer, Klaus Grosfeld, Nanna B. Karlsson, Thomas Kleiner, Brice Van Liefferinge, and Olaf Eisen
The Cryosphere, 13, 2023–2041, https://doi.org/10.5194/tc-13-2023-2019, https://doi.org/10.5194/tc-13-2023-2019, 2019
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The Antarctic Ice Sheet may have played an important role in moderating the transition between warm and cold climate epochs over the last million years. We find that the Antarctic Ice Sheet grew considerably about 0.9 Myr ago, a time when ice-age–warm-age cycles changed from a
40 000 to a 100 000 year periodicity. Our findings also suggest that ice as old as 1.5 Myr still exists at the bottom of the East Antarctic Ice Sheet despite the major climate reorganisations in the past.
Kenneth D. Mankoff, William Colgan, Anne Solgaard, Nanna B. Karlsson, Andreas P. Ahlstrøm, Dirk van As, Jason E. Box, Shfaqat Abbas Khan, Kristian K. Kjeldsen, Jeremie Mouginot, and Robert S. Fausto
Earth Syst. Sci. Data, 11, 769–786, https://doi.org/10.5194/essd-11-769-2019, https://doi.org/10.5194/essd-11-769-2019, 2019
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We have produced an open and reproducible estimate of Greenland Ice Sheet solid ice discharge from 1986 through 2017. Our results show three modes at the total ice-sheet scale: steady discharge from 1986 through 2000, increasing discharge from 2000 through 2005, and steady discharge from 2005 through 2017. The behavior of individual sectors and glaciers is more complicated. This work was done to provide a 100 % reproducible estimate to help constrain mass balance and sea-level rise estimates.
Baptiste Vandecrux, Michael MacFerrin, Horst Machguth, William T. Colgan, Dirk van As, Achim Heilig, C. Max Stevens, Charalampos Charalampidis, Robert S. Fausto, Elizabeth M. Morris, Ellen Mosley-Thompson, Lora Koenig, Lynn N. Montgomery, Clément Miège, Sebastian B. Simonsen, Thomas Ingeman-Nielsen, and Jason E. Box
The Cryosphere, 13, 845–859, https://doi.org/10.5194/tc-13-845-2019, https://doi.org/10.5194/tc-13-845-2019, 2019
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The perennial snow, or firn, on the Greenland ice sheet each summer stores part of the meltwater formed at the surface, buffering the ice sheet’s contribution to sea level. We gathered observations of firn air content, indicative of the space available in the firn to retain meltwater, and find that this air content remained stable in cold regions of the firn over the last 65 years but recently decreased significantly in western Greenland.
Isabelle Gouttevin, Moritz Langer, Henning Löwe, Julia Boike, Martin Proksch, and Martin Schneebeli
The Cryosphere, 12, 3693–3717, https://doi.org/10.5194/tc-12-3693-2018, https://doi.org/10.5194/tc-12-3693-2018, 2018
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Snow insulates the ground from the cold air in the Arctic winter, majorly affecting permafrost. This insulation depends on snow characteristics and is poorly quantified. Here, we characterize it at a carbon-rich permafrost site, using a recent technique that retrieves the 3-D structure of snow and its thermal properties. We adapt a snowpack model enabling the simulation of this insulation over a whole winter. We estimate that local snow variations induce up to a 6 °C spread in soil temperatures.
Daniel McGrath, Louis Sass, Shad O'Neel, Chris McNeil, Salvatore G. Candela, Emily H. Baker, and Hans-Peter Marshall
The Cryosphere, 12, 3617–3633, https://doi.org/10.5194/tc-12-3617-2018, https://doi.org/10.5194/tc-12-3617-2018, 2018
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Measuring the amount and spatial pattern of snow on glaciers is essential for monitoring glacier mass balance and quantifying the water budget of glacierized basins. Using repeat radar surveys for 5 consecutive years, we found that the spatial pattern in snow distribution is stable over the majority of the glacier and scales with the glacier-wide average. Our findings support the use of sparse stake networks for effectively measuring interannual variability in winter balance on glaciers.
Todd A. N. Redpath, Pascal Sirguey, and Nicolas J. Cullen
The Cryosphere, 12, 3477–3497, https://doi.org/10.5194/tc-12-3477-2018, https://doi.org/10.5194/tc-12-3477-2018, 2018
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A remotely piloted aircraft system (RPAS) is evaluated for mapping seasonal snow depth across an alpine basin. RPAS photogrammetry performs well at providing maps of snow depth at high spatial resolution, outperforming field measurements for resolving spatial variability. Uncertainty and error analysis reveal limitations and potential pitfalls of photogrammetric surface-change analysis. Ultimately, RPAS can be a useful tool for understanding snow processes and improving snow modelling efforts.
Brice Van Liefferinge, Frank Pattyn, Marie G. P. Cavitte, Nanna B. Karlsson, Duncan A. Young, Johannes Sutter, and Olaf Eisen
The Cryosphere, 12, 2773–2787, https://doi.org/10.5194/tc-12-2773-2018, https://doi.org/10.5194/tc-12-2773-2018, 2018
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Our paper provides an important review of the state of knowledge for oldest-ice prospection, but also adds new basal geothermal heat flux constraints from recently acquired high-definition radar data sets. This is the first paper to contrast the two primary target regions for oldest ice: Dome C and Dome Fuji. Moreover, we provide statistical comparisons of all available data sets and a summary of the community's criteria for the retrieval of interpretable oldest ice since the 2013 effort.
Lauren Schmeisser, John Backman, John A. Ogren, Elisabeth Andrews, Eija Asmi, Sandra Starkweather, Taneil Uttal, Markus Fiebig, Sangeeta Sharma, Kostas Eleftheriadis, Stergios Vratolis, Michael Bergin, Peter Tunved, and Anne Jefferson
Atmos. Chem. Phys., 18, 11599–11622, https://doi.org/10.5194/acp-18-11599-2018, https://doi.org/10.5194/acp-18-11599-2018, 2018
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This paper presents pan-Arctic seasonality of in-situ-measured aerosol optical properties from six surface monitoring sites. The analysis provides insight into aerosol annual variability throughout the region – something that is not possible using only measurements from satellite or temporary aircraft campaigns. This paper shows that the large spatiotemporal variability in aerosol optical properties needs to be taken into account in order to properly represent Arctic climate.
Nanna B. Karlsson, Tobias Binder, Graeme Eagles, Veit Helm, Frank Pattyn, Brice Van Liefferinge, and Olaf Eisen
The Cryosphere, 12, 2413–2424, https://doi.org/10.5194/tc-12-2413-2018, https://doi.org/10.5194/tc-12-2413-2018, 2018
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In this study, we investigate the probability that the Dome Fuji region in East Antarctica contains ice more than 1.5 Ma old. The retrieval of a continuous ice-core record extending beyond 1 Ma is imperative to understand why the frequency of ice ages changed from 40 to 100 ka approximately 1 Ma ago.
We use a new radar dataset to improve the ice thickness maps, and apply a thermokinematic model to predict basal temperature and age of the ice. Our results indicate several areas of interest.
Alexander Kokhanovsky, Maxim Lamare, Biagio Di Mauro, Ghislain Picard, Laurent Arnaud, Marie Dumont, François Tuzet, Carsten Brockmann, and Jason E. Box
The Cryosphere, 12, 2371–2382, https://doi.org/10.5194/tc-12-2371-2018, https://doi.org/10.5194/tc-12-2371-2018, 2018
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This work presents a new technique with which to derive the snow microphysical and optical properties from snow spectral reflectance measurements. The technique is robust and easy to use, and it does not require the extraction of snow samples from a given snowpack. It can be used in processing satellite imagery over extended fresh dry, wet and polluted snowfields.
Andreas M. Jobst, Daniel G. Kingston, Nicolas J. Cullen, and Josef Schmid
Hydrol. Earth Syst. Sci., 22, 3125–3142, https://doi.org/10.5194/hess-22-3125-2018, https://doi.org/10.5194/hess-22-3125-2018, 2018
Achim Heilig, Olaf Eisen, Michael MacFerrin, Marco Tedesco, and Xavier Fettweis
The Cryosphere, 12, 1851–1866, https://doi.org/10.5194/tc-12-1851-2018, https://doi.org/10.5194/tc-12-1851-2018, 2018
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This paper presents data on temporal changes in snow and firn, which were not available before. We present data on water infiltration in the percolation zone of the Greenland Ice Sheet that improve our understanding of liquid water retention in snow and firn and mass transfer. We compare those findings with model simulations. It appears that simulated accumulation in terms of SWE is fairly accurate, while modeling of the individual parameters density and liquid water content is incorrect.
Keith S. Jennings, Timothy G. F. Kittel, and Noah P. Molotch
The Cryosphere, 12, 1595–1614, https://doi.org/10.5194/tc-12-1595-2018, https://doi.org/10.5194/tc-12-1595-2018, 2018
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We show through observations and simulations that cold content, a key part of the snowpack energy budget, develops primarily through new snowfall. We also note that cold content damps snowmelt rate and timing at sub-seasonal timescales, while seasonal melt onset is controlled by the timing of peak cold content and total spring precipitation. This work has implications for how cold content is represented in snow models and improves our understanding of its effect on snowmelt processes.
Konstanze Haubner, Jason E. Box, Nicole J. Schlegel, Eric Y. Larour, Mathieu Morlighem, Anne M. Solgaard, Kristian K. Kjeldsen, Signe H. Larsen, Eric Rignot, Todd K. Dupont, and Kurt H. Kjær
The Cryosphere, 12, 1511–1522, https://doi.org/10.5194/tc-12-1511-2018, https://doi.org/10.5194/tc-12-1511-2018, 2018
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We investigate the effect of neglecting calving on Upernavik Isstrøm, West Greenland, between 1849 and 2012.
Our simulation is forced with observed terminus positions in discrete time steps and is responsive to the prescribed ice front changes.
Simulated frontal retreat is needed to obtain a realistic ice surface elevation and velocity evolution of Upernavik.
Using the prescribed terminus position change we gain insight to mass loss partitioning during different time periods.
Keith N. Musselman, Noah P. Molotch, and Steven A. Margulis
The Cryosphere, 11, 2847–2866, https://doi.org/10.5194/tc-11-2847-2017, https://doi.org/10.5194/tc-11-2847-2017, 2017
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We present a study of how melt rates in the California Sierra Nevada respond to a range of warming projected for this century. Snowfall and melt were simulated for historical and modified (warmer) snow seasons. Winter melt occurs more frequently and more intensely, causing an increase in extreme winter melt. In a warmer climate, less snow persists into the spring, causing spring melt to be substantially lower. The results offer insight into how snow water resources may respond to climate change.
Suzanne L. Bevan, Adrian Luckman, Bryn Hubbard, Bernd Kulessa, David Ashmore, Peter Kuipers Munneke, Martin O'Leary, Adam Booth, Heidi Sevestre, and Daniel McGrath
The Cryosphere, 11, 2743–2753, https://doi.org/10.5194/tc-11-2743-2017, https://doi.org/10.5194/tc-11-2743-2017, 2017
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Five 90 m boreholes drilled into an Antarctic Peninsula ice shelf show units of ice that are denser than expected and must have formed from refrozen surface melt which has been buried and transported downstream. We used surface flow speeds and snow accumulation rates to work out where and when these units formed. Results show that, as well as recent surface melt, a period of strong melt occurred during the 18th century. Surface melt is thought to be a factor in causing recent ice-shelf break-up.
Peter Kuipers Munneke, Daniel McGrath, Brooke Medley, Adrian Luckman, Suzanne Bevan, Bernd Kulessa, Daniela Jansen, Adam Booth, Paul Smeets, Bryn Hubbard, David Ashmore, Michiel Van den Broeke, Heidi Sevestre, Konrad Steffen, Andrew Shepherd, and Noel Gourmelen
The Cryosphere, 11, 2411–2426, https://doi.org/10.5194/tc-11-2411-2017, https://doi.org/10.5194/tc-11-2411-2017, 2017
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How much snow falls on the Larsen C ice shelf? This is a relevant question, because this ice shelf might collapse sometime this century. To know if and when this could happen, we found out how much snow falls on its surface. This was difficult, because there are only very few measurements. Here, we used data from automatic weather stations, sled-pulled radars, and a climate model to find that melting the annual snowfall produces about 20 cm of water in the NE and over 70 cm in the SW.
Dominik Schneider, Noah P. Molotch, and Jeffrey S. Deems
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-167, https://doi.org/10.5194/tc-2017-167, 2017
Revised manuscript not accepted
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New data from the ongoing Airborne Snow Observatory (ASO) provides an unprecedented look at the spatial and temporal patterns of snow water content (SWE) over multiple years in California, USA. We found that relationships between SWE, snow covered area, and topography transfer between years at accuracy levels equivalent to those from models generated from ASO data collected on the day of interest. This research provides a first attempt at extending the value of ASO beyond the observations.
Pirmin Philipp Ebner, Hans Christian Steen-Larsen, Barbara Stenni, Martin Schneebeli, and Aldo Steinfeld
The Cryosphere, 11, 1733–1743, https://doi.org/10.5194/tc-11-1733-2017, https://doi.org/10.5194/tc-11-1733-2017, 2017
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Stable water isotopes (δ18O) obtained from snow and ice samples from polar regions are used to reconstruct past climate variability. We present an experimental study on the effect on the snow isotopic composition by airflow through a snowpack in controlled laboratory conditions. The disequilibrium between snow and vapor isotopes changed the isotopic content of the snow. These measurements suggest that metamorphism and its history affect the snow isotopic composition.
Dirk van As, Andreas Bech Mikkelsen, Morten Holtegaard Nielsen, Jason E. Box, Lillemor Claesson Liljedahl, Katrin Lindbäck, Lincoln Pitcher, and Bent Hasholt
The Cryosphere, 11, 1371–1386, https://doi.org/10.5194/tc-11-1371-2017, https://doi.org/10.5194/tc-11-1371-2017, 2017
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The Greenland ice sheet melts faster in a warmer climate. The ice sheet is flatter at high elevation, therefore atmospheric warming increases the melt area exponentially. For current climate conditions, we find that the ice sheet shape amplifies the total meltwater generation by roughly 60 %. Meltwater is not stored underneath the ice sheet, as previously found, but it does take multiple days for it to pass through the seasonally developing subglacial drainage channels, moderating discharge.
Sascha Bellaire, Martin Proksch, Martin Schneebeli, Masashi Niwano, and Konrad Steffen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-55, https://doi.org/10.5194/tc-2017-55, 2017
Preprint withdrawn
Xavier Fettweis, Jason E. Box, Cécile Agosta, Charles Amory, Christoph Kittel, Charlotte Lang, Dirk van As, Horst Machguth, and Hubert Gallée
The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, https://doi.org/10.5194/tc-11-1015-2017, 2017
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This paper shows that the surface melt increase over the Greenland ice sheet since the end of the 1990s has been unprecedented, with respect to the last 120 years, using a regional climate model. These simulations also suggest an increase of the snowfall accumulation through the last century before a surface mass decrease in the 2000s. Such a mass gain could have impacted the ice sheet's dynamic stability and could explain the recent observed increase of the glaciers' velocity.
Gabriel Lewis, Erich Osterberg, Robert Hawley, Brian Whitmore, Hans Peter Marshall, and Jason Box
The Cryosphere, 11, 773–788, https://doi.org/10.5194/tc-11-773-2017, https://doi.org/10.5194/tc-11-773-2017, 2017
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We analyze 25 flight lines from NASA's Operation IceBridge Accumulation Radar totaling to determine snow accumulation throughout the dry snow and percolation zone of the Greenland Ice Sheet. Our results indicate that regional differences between IceBridge and model accumulation are large enough to significantly alter the Greenland Ice Sheet surface mass balance, with implications for future global sea-level rise.
Pascal Bohleber, Leo Sold, Douglas R. Hardy, Margit Schwikowski, Patrick Klenk, Andrea Fischer, Pascal Sirguey, Nicolas J. Cullen, Mariusz Potocki, Helene Hoffmann, and Paul Mayewski
The Cryosphere, 11, 469–482, https://doi.org/10.5194/tc-11-469-2017, https://doi.org/10.5194/tc-11-469-2017, 2017
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Our study is the first to use ground-penetrating radar (GPR) to investigate ice thickness and internal layering at Kilimanjaro’s largest ice body, the Northern Ice Field (NIF). For monitoring the ongoing ice loss, our ice thickness soundings allowed us to estimate the total ice volume remaining at NIF's southern portion. Englacial GPR reflections indicate undisturbed layers within NIF's center and provide a first link between age information obtained from ice coring and vertical wall sampling.
Louise C. Sime, Dominic Hodgson, Thomas J. Bracegirdle, Claire Allen, Bianca Perren, Stephen Roberts, and Agatha M. de Boer
Clim. Past, 12, 2241–2253, https://doi.org/10.5194/cp-12-2241-2016, https://doi.org/10.5194/cp-12-2241-2016, 2016
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Latitudinal shifts in the Southern Ocean westerly wind jet could explain large observed changes in the glacial to interglacial ocean CO2 inventory. However there is considerable disagreement in modelled deglacial-warming jet shifts. Here multi-model output is used to show that expansion of sea ice during the glacial period likely caused a slight poleward shift and intensification in the westerly wind jet. Issues with model representation of the winds caused much of the previous disagreement.
Pascal Sirguey, Holly Still, Nicolas J. Cullen, Marie Dumont, Yves Arnaud, and Jonathan P. Conway
The Cryosphere, 10, 2465–2484, https://doi.org/10.5194/tc-10-2465-2016, https://doi.org/10.5194/tc-10-2465-2016, 2016
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Fourteen years of satellite observations are used to monitor the albedo of Brewster Glacier, New Zealand and estimate annual and seasonal balances. This confirms the governing role of the summer balance in the annual balance and allows the reconstruction of the annual balance to 1977 using a photographic record of the snowline. The longest mass balance record for a New Zealand glacier shows negative balances after 2008, yielding a loss of 35 % of the gain accumulated over the previous 30 years.
Jonathan C. Ryan, Alun Hubbard, Marek Stibal, Jason E. Box, and the Dark Snow Project team
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-204, https://doi.org/10.5194/tc-2016-204, 2016
Preprint withdrawn
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Using digital imagery and broadband albedo acquired by a fixed-wing UAS we classified and measured the albedo of six surface types that dominate the Greenland ablation area and its dark region. We found that the primary control on ablation area albedo is the fractional area of distributed impurities. Although not the darkest surface type observed, the distributed impurities dominate the albedo signal because of their extensive coverage.
Juha Lemmetyinen, Anna Kontu, Jouni Pulliainen, Juho Vehviläinen, Kimmo Rautiainen, Andreas Wiesmann, Christian Mätzler, Charles Werner, Helmut Rott, Thomas Nagler, Martin Schneebeli, Martin Proksch, Dirk Schüttemeyer, Michael Kern, and Malcolm W. J. Davidson
Geosci. Instrum. Method. Data Syst., 5, 403–415, https://doi.org/10.5194/gi-5-403-2016, https://doi.org/10.5194/gi-5-403-2016, 2016
Nicole-Jeanne Schlegel, David N. Wiese, Eric Y. Larour, Michael M. Watkins, Jason E. Box, Xavier Fettweis, and Michiel R. van den Broeke
The Cryosphere, 10, 1965–1989, https://doi.org/10.5194/tc-10-1965-2016, https://doi.org/10.5194/tc-10-1965-2016, 2016
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We investigate Greenland Ice Sheet mass change from 2003–2012 by comparing observations from GRACE with state-of-the-art atmospheric and ice sheet model simulations. We find that the largest discrepancies (in the northwest and southeast) are likely controlled by errors in modeled surface climate as well as ice–ocean interaction and hydrological processes (not included in the models). Models should consider such processes at monthly to seasonal resolutions in order to improve future projections.
Naoki Mizukami, Martyn P. Clark, Kevin Sampson, Bart Nijssen, Yixin Mao, Hilary McMillan, Roland J. Viger, Steve L. Markstrom, Lauren E. Hay, Ross Woods, Jeffrey R. Arnold, and Levi D. Brekke
Geosci. Model Dev., 9, 2223–2238, https://doi.org/10.5194/gmd-9-2223-2016, https://doi.org/10.5194/gmd-9-2223-2016, 2016
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mizuRoute version 1 is a stand-alone runoff routing tool that post-processes runoff outputs from any distributed hydrologic models to produce streamflow estimates in large-scale river network. mizuRoute is flexible to river network representation and includes two different river routing schemes. This paper demonstrates mizuRoute's capability of multi-decadal streamflow estimations in the river networks over the entire contiguous Unites States, which contains over 54 000 river segments.
Felix C. Seidel, Karl Rittger, S. McKenzie Skiles, Noah P. Molotch, and Thomas H. Painter
The Cryosphere, 10, 1229–1244, https://doi.org/10.5194/tc-10-1229-2016, https://doi.org/10.5194/tc-10-1229-2016, 2016
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Quantifying the snow albedo effect is an important step to predict water availability as well as changes in climate and sea level. We use imaging spectroscopy to determine optical properties of mountain snow. We find an inverse relationship between snow albedo and grain size as well as between elevation and grain size. Under strong melt conditions, however, we show that the optical-equivalent snow grain size increases slower than expected at lower elevations and we explain possible reasons.
Andreas Bech Mikkelsen, Alun Hubbard, Mike MacFerrin, Jason Eric Box, Sam H. Doyle, Andrew Fitzpatrick, Bent Hasholt, Hannah L. Bailey, Katrin Lindbäck, and Rickard Pettersson
The Cryosphere, 10, 1147–1159, https://doi.org/10.5194/tc-10-1147-2016, https://doi.org/10.5194/tc-10-1147-2016, 2016
Pascal Hagenmuller, Margret Matzl, Guillaume Chambon, and Martin Schneebeli
The Cryosphere, 10, 1039–1054, https://doi.org/10.5194/tc-10-1039-2016, https://doi.org/10.5194/tc-10-1039-2016, 2016
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The paper focuses on the characterization of snow microstructure with X-ray microtomography, a technique that is progressively becoming the standard for snow characterization. In particular, it rigorously investigates how the image processing algorithms affect the subsequent microstructure characterization in terms of density and specific surface area. From this analysis, practical recommendations concerning the processing X-ray tomographic images of snow are provided.
William Maslanka, Leena Leppänen, Anna Kontu, Mel Sandells, Juha Lemmetyinen, Martin Schneebeli, Martin Proksch, Margret Matzl, Henna-Reetta Hannula, and Robert Gurney
Geosci. Instrum. Method. Data Syst., 5, 85–94, https://doi.org/10.5194/gi-5-85-2016, https://doi.org/10.5194/gi-5-85-2016, 2016
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The paper presents the initial findings of the Arctic Snow Microstructure Experiment in Sodankylä, Finland. The experiment observed the microwave emission of extracted snow slabs on absorbing and reflecting bases. Snow parameters were recorded to simulate the emission upon those bases using two different emission models. The smallest simulation errors were associated with the absorbing base at vertical polarization. The observations will be used for the development of snow emission modelling.
Pirmin Philipp Ebner, Martin Schneebeli, and Aldo Steinfeld
The Cryosphere, 10, 791–797, https://doi.org/10.5194/tc-10-791-2016, https://doi.org/10.5194/tc-10-791-2016, 2016
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Changes of the porous ice structure were observed in a snow sample. Sublimation occurred due to the slight undersaturation of the incoming air into the warmer ice matrix. Diffusion of water vapor opposite to the direction of the temperature gradient counteracted the mass transport of advection. Therefore, the total net ice change was negligible, leading to a constant porosity profile. However, the strong recrystallization of water molecules in snow may impact its isotopic or chemical content.
Martin Proksch, Nick Rutter, Charles Fierz, and Martin Schneebeli
The Cryosphere, 10, 371–384, https://doi.org/10.5194/tc-10-371-2016, https://doi.org/10.5194/tc-10-371-2016, 2016
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Density is a fundamental property of porous media such as snow. During the MicroSnow Davos 2014 workshop, different approaches (box-, wedge- and cylinder-type density cutters, micro-computed tomography) to measure snow density were applied in a controlled laboratory environment and in the field. In general, results suggest that snow densities measured by different methods agree within 9 %. However, the density profiles resolved by the measurement methods differed considerably.
J. P. Conway and N. J. Cullen
The Cryosphere, 10, 313–328, https://doi.org/10.5194/tc-10-313-2016, https://doi.org/10.5194/tc-10-313-2016, 2016
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Clouds are shown to force fundamental changes in the surface energy and mass balance of Brewster Glacier, New Zealand. Cloudy periods exhibit greater melt due to increased incoming long-wave radiation and higher atmospheric vapour pressure rather than through minimal changes in mean air temperature and wind speed. Surface mass-balance sensitivity to air temperature is enhanced in overcast compared to clear-sky periods due to more frequent melt and a strong precipitation phase to albedo feedback.
N. Wever, L. Schmid, A. Heilig, O. Eisen, C. Fierz, and M. Lehning
The Cryosphere, 9, 2271–2293, https://doi.org/10.5194/tc-9-2271-2015, https://doi.org/10.5194/tc-9-2271-2015, 2015
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A verification of the physics based SNOWPACK model with field observations showed that typical snowpack properties like density and temperature are adequately simulated. Also two water transport schemes were verified, showing that although Richards equation improves snowpack runoff and several aspects of the internal snowpack structure, the bucket scheme appeared to have a higher agreement with the snow microstructure. The choice of water transport scheme may depend on the intended application.
C. Charalampidis, D. van As, J. E. Box, M. R. van den Broeke, W. T. Colgan, S. H. Doyle, A. L. Hubbard, M. MacFerrin, H. Machguth, and C. J. P. P. Smeets
The Cryosphere, 9, 2163–2181, https://doi.org/10.5194/tc-9-2163-2015, https://doi.org/10.5194/tc-9-2163-2015, 2015
P. Kuipers Munneke, S. R. M. Ligtenberg, B. P. Y. Noël, I. M. Howat, J. E. Box, E. Mosley-Thompson, J. R. McConnell, K. Steffen, J. T. Harper, S. B. Das, and M. R. van den Broeke
The Cryosphere, 9, 2009–2025, https://doi.org/10.5194/tc-9-2009-2015, https://doi.org/10.5194/tc-9-2009-2015, 2015
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The snow layer on top of the Greenland Ice Sheet is changing: it is thickening in the high and cold interior due to increased snowfall, while it is thinning around the margins. The marginal thinning is caused by compaction, and by more melt.
This knowledge is important: there are satellites that measure volume change of the ice sheet. It can be caused by increased ice discharge, or by compaction of the snow layer. Here, we quantify the latter, so that we can translate volume to mass change.
M. Proksch, C. Mätzler, A. Wiesmann, J. Lemmetyinen, M. Schwank, H. Löwe, and M. Schneebeli
Geosci. Model Dev., 8, 2611–2626, https://doi.org/10.5194/gmd-8-2611-2015, https://doi.org/10.5194/gmd-8-2611-2015, 2015
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The measurement of snow properties on global scale relies on microwave remote sensing data. The interpretation of the data is however challenging. Here we introduce MEMLS3&a, an extension of the snow emission model MEMLS, to include a backscatter model for active microwave remote sensing. In MEMLS3&a, snow input parameters can be derived by objective measurement methods, which avoids fitting the scattering efficiency of snow. The model is validated with combined active and passive measurements.
V. Masson-Delmotte, H. C. Steen-Larsen, P. Ortega, D. Swingedouw, T. Popp, B. M. Vinther, H. Oerter, A. E. Sveinbjornsdottir, H. Gudlaugsdottir, J. E. Box, S. Falourd, X. Fettweis, H. Gallée, E. Garnier, V. Gkinis, J. Jouzel, A. Landais, B. Minster, N. Paradis, A. Orsi, C. Risi, M. Werner, and J. W. C. White
The Cryosphere, 9, 1481–1504, https://doi.org/10.5194/tc-9-1481-2015, https://doi.org/10.5194/tc-9-1481-2015, 2015
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The deep NEEM ice core provides the oldest Greenland ice core record, enabling improved understanding of the response of ice core records to local climate. Here, we focus on shallow ice cores providing a stack record of accumulation and water-stable isotopes spanning the past centuries. For the first time, we document the ongoing warming in a Greenland ice core. By combining our data with other Greenland ice cores and model results, we characterise the spatio-temporal patterns of variability.
N. B. Karlsson and D. Dahl-Jensen
The Cryosphere, 9, 1465–1479, https://doi.org/10.5194/tc-9-1465-2015, https://doi.org/10.5194/tc-9-1465-2015, 2015
P. P. Ebner, M. Schneebeli, and A. Steinfeld
The Cryosphere, 9, 1363–1371, https://doi.org/10.5194/tc-9-1363-2015, https://doi.org/10.5194/tc-9-1363-2015, 2015
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Time-lapse X-ray microtomography was used to investigate the structural dynamics of isothermal snow metamorphism exposed to an advective airflow and possible effects on natural snowpacks were discussed. The results showed that isothermal advection with saturated air have no influence on the coarsening rate that is typical for isothermal snow metamorphism. It is driven by sublimation-deposition caused by Kelvin effect and is the limiting factor independently of the transport regime in the pores.
A. A. Harpold, J. A. Marshall, S. W. Lyon, T. B. Barnhart, B. A. Fisher, M. Donovan, K. M. Brubaker, C. J. Crosby, N. F. Glenn, C. L. Glennie, P. B. Kirchner, N. Lam, K. D. Mankoff, J. L. McCreight, N. P. Molotch, K. N. Musselman, J. Pelletier, T. Russo, H. Sangireddy, Y. Sjöberg, T. Swetnam, and N. West
Hydrol. Earth Syst. Sci., 19, 2881–2897, https://doi.org/10.5194/hess-19-2881-2015, https://doi.org/10.5194/hess-19-2881-2015, 2015
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This review's objective is to demonstrate the transformative potential of lidar by critically assessing both challenges and opportunities for transdisciplinary lidar applications in geomorphology, hydrology, and ecology. We find that using lidar to its full potential will require numerous advances, including more powerful open-source processing tools, new lidar acquisition technologies, and improved integration with physically based models and complementary observations.
J. Schwaab, M. Bavay, E. Davin, F. Hagedorn, F. Hüsler, M. Lehning, M. Schneebeli, E. Thürig, and P. Bebi
Biogeosciences, 12, 467–487, https://doi.org/10.5194/bg-12-467-2015, https://doi.org/10.5194/bg-12-467-2015, 2015
A. J. Newman, M. P. Clark, K. Sampson, A. Wood, L. E. Hay, A. Bock, R. J. Viger, D. Blodgett, L. Brekke, J. R. Arnold, T. Hopson, and Q. Duan
Hydrol. Earth Syst. Sci., 19, 209–223, https://doi.org/10.5194/hess-19-209-2015, https://doi.org/10.5194/hess-19-209-2015, 2015
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The focus of this paper is to (1) present a community data set of daily forcing and hydrologic response data for 671 unimpaired basins across the contiguous United States that spans a very wide range of hydroclimatic conditions, and (2) provide a calibrated model performance benchmark using a common conceptual snow and hydrologic modeling system. This benchmark provides a reference level of model performance across a very large basin sample and highlights regional variations in performance.
J. C. Ryan, A. L. Hubbard, J. E. Box, J. Todd, P. Christoffersen, J. R. Carr, T. O. Holt, and N. Snooke
The Cryosphere, 9, 1–11, https://doi.org/10.5194/tc-9-1-2015, https://doi.org/10.5194/tc-9-1-2015, 2015
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An unmanned aerial vehicle (UAV) equipped with a commercial digital camera enabled us to obtain high-resolution digital images of the calving front of Store glacier, Greenland. The three sorties flown enabled key glaciological parameters to be quantified in sufficient detail to reveal that the terminus of Store glacier is a complex system with large variations in crevasse patterns surface velocities, calving processes, surface elevations and front positions at a daily and seasonal timescale.
A. Messerli, N. B. Karlsson, and A. Grinsted
The Cryosphere Discuss., https://doi.org/10.5194/tcd-8-6235-2014, https://doi.org/10.5194/tcd-8-6235-2014, 2014
Preprint withdrawn
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We use 2014 Landsat-8 imagery in combination with a newly developed feature tracking toolbox, ImGRAFT to produce velocity fields and flux for five major Greenland marine terminating glaciers: Helheim, Kangerdlugssuaq, Nioghalvfjerdsbræ, Petermann and Jakobshavn Isbræ. A major finding of the paper documents the increased velocities observed at Jakobshavn Isbræ. We measure velocities over 50m/day which exceed that of the previously recorded maximum.
S. Schleef, H. Löwe, and M. Schneebeli
The Cryosphere, 8, 1825–1838, https://doi.org/10.5194/tc-8-1825-2014, https://doi.org/10.5194/tc-8-1825-2014, 2014
P. P. Ebner, S. A. Grimm, M. Schneebeli, and A. Steinfeld
Geosci. Instrum. Method. Data Syst., 3, 179–185, https://doi.org/10.5194/gi-3-179-2014, https://doi.org/10.5194/gi-3-179-2014, 2014
S. A. Khan, K. K. Kjeldsen, K. H. Kjær, S. Bevan, A. Luckman, A. Aschwanden, A. A. Bjørk, N. J. Korsgaard, J. E. Box, M. van den Broeke, T. M. van Dam, and A. Fitzner
The Cryosphere, 8, 1497–1507, https://doi.org/10.5194/tc-8-1497-2014, https://doi.org/10.5194/tc-8-1497-2014, 2014
N. Chauché, A. Hubbard, J.-C. Gascard, J. E. Box, R. Bates, M. Koppes, A. Sole, P. Christoffersen, and H. Patton
The Cryosphere, 8, 1457–1468, https://doi.org/10.5194/tc-8-1457-2014, https://doi.org/10.5194/tc-8-1457-2014, 2014
A. A. W. Fitzpatrick, A. L. Hubbard, J. E. Box, D. J. Quincey, D. van As, A. P. B. Mikkelsen, S. H. Doyle, C. F. Dow, B. Hasholt, and G. A. Jones
The Cryosphere, 8, 107–121, https://doi.org/10.5194/tc-8-107-2014, https://doi.org/10.5194/tc-8-107-2014, 2014
K. Helfricht, M. Kuhn, M. Keuschnig, and A. Heilig
The Cryosphere, 8, 41–57, https://doi.org/10.5194/tc-8-41-2014, https://doi.org/10.5194/tc-8-41-2014, 2014
W. Colgan, S. Luthcke, W. Abdalati, and M. Citterio
The Cryosphere, 7, 1901–1914, https://doi.org/10.5194/tc-7-1901-2013, https://doi.org/10.5194/tc-7-1901-2013, 2013
T. Kobashi, K. Goto-Azuma, J. E. Box, C.-C. Gao, and T. Nakaegawa
Clim. Past, 9, 2299–2317, https://doi.org/10.5194/cp-9-2299-2013, https://doi.org/10.5194/cp-9-2299-2013, 2013
H. Löwe, F. Riche, and M. Schneebeli
The Cryosphere, 7, 1473–1480, https://doi.org/10.5194/tc-7-1473-2013, https://doi.org/10.5194/tc-7-1473-2013, 2013
A. K. Rennermalm, L. C. Smith, V. W. Chu, J. E. Box, R. R. Forster, M. R. Van den Broeke, D. Van As, and S. E. Moustafa
The Cryosphere, 7, 1433–1445, https://doi.org/10.5194/tc-7-1433-2013, https://doi.org/10.5194/tc-7-1433-2013, 2013
A. P. Ahlstrøm, S. B. Andersen, M. L. Andersen, H. Machguth, F. M. Nick, I. Joughin, C. H. Reijmer, R. S. W. van de Wal, J. P. Merryman Boncori, J. E. Box, M. Citterio, D. van As, R. S. Fausto, and A. Hubbard
Earth Syst. Sci. Data, 5, 277–287, https://doi.org/10.5194/essd-5-277-2013, https://doi.org/10.5194/essd-5-277-2013, 2013
T. Bartels-Rausch, S. N. Wren, S. Schreiber, F. Riche, M. Schneebeli, and M. Ammann
Atmos. Chem. Phys., 13, 6727–6739, https://doi.org/10.5194/acp-13-6727-2013, https://doi.org/10.5194/acp-13-6727-2013, 2013
M. Tedesco, X. Fettweis, T. Mote, J. Wahr, P. Alexander, J. E. Box, and B. Wouters
The Cryosphere, 7, 615–630, https://doi.org/10.5194/tc-7-615-2013, https://doi.org/10.5194/tc-7-615-2013, 2013
M. Citterio and A. P. Ahlstrøm
The Cryosphere, 7, 445–449, https://doi.org/10.5194/tc-7-445-2013, https://doi.org/10.5194/tc-7-445-2013, 2013
T. Kobashi, D. T. Shindell, K. Kodera, J. E. Box, T. Nakaegawa, and K. Kawamura
Clim. Past, 9, 583–596, https://doi.org/10.5194/cp-9-583-2013, https://doi.org/10.5194/cp-9-583-2013, 2013
N. J. Cullen, P. Sirguey, T. Mölg, G. Kaser, M. Winkler, and S. J. Fitzsimons
The Cryosphere, 7, 419–431, https://doi.org/10.5194/tc-7-419-2013, https://doi.org/10.5194/tc-7-419-2013, 2013
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Domain: ESSD – Atmosphere | Subject: Meteorology
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Earth Syst. Sci. Data, 16, 5643–5663, https://doi.org/10.5194/essd-16-5643-2024, https://doi.org/10.5194/essd-16-5643-2024, 2024
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This dataset provides, for the first time, combined observations of clouds and precipitation with coincident retrievals of atmospheric thermodynamics obtained from the same space-based instrument. Furthermore, it provides the locations of the ray trajectories of the observations along various precipitation-related products interpolated into them with the aim of fostering the use of such dataset in scientific and operational applications.
Frédéric Laly, Patrick Chazette, Julien Totems, Jérémy Lagarrigue, Laurent Forges, and Cyrille Flamant
Earth Syst. Sci. Data, 16, 5579–5602, https://doi.org/10.5194/essd-16-5579-2024, https://doi.org/10.5194/essd-16-5579-2024, 2024
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We present a dataset of water vapor mixing ratio profiles acquired during the Water Vapor Lidar Network Assimilation campaign in fall and winter 2022 and summer 2023, using three lidar systems deployed on the western Mediterranean coastline. This innovative campaign provides access to lower-tropospheric water vapor variability to constrain meteorological forecasting models. The scientific objective is to improve forecasting of heavy-precipation events that lead to flash floods and landslides.
Uwe Pfeifroth, Jaqueline Drücke, Steffen Kothe, Jörg Trentmann, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 16, 5243–5265, https://doi.org/10.5194/essd-16-5243-2024, https://doi.org/10.5194/essd-16-5243-2024, 2024
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The energy reaching Earth's surface from the Sun is a quantity of great importance for the climate system and for many applications. SARAH-3 is a satellite-based climate data record of surface solar radiation parameters. It is generated and distributed by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF). SARAH-3 covers more than 4 decades and provides a high spatial and temporal resolution, and its validation shows good accuracy and stability.
Thomas Fiolleau and Rémy Roca
Earth Syst. Sci. Data, 16, 4021–4050, https://doi.org/10.5194/essd-16-4021-2024, https://doi.org/10.5194/essd-16-4021-2024, 2024
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This paper presents a database of tropical deep convective systems over the 2012–2020 period, built from a cloud-tracking algorithm called TOOCAN, which has been applied to homogenized infrared observations from a fleet of geostationary satellites. This database aims to analyze the tropical deep convective systems, the evolution of their associated characteristics over their life cycle, their organization, and their importance in the hydrological and energy cycle.
Bing Li, Shunlin Liang, Han Ma, Guanpeng Dong, Xiaobang Liu, Tao He, and Yufang Zhang
Earth Syst. Sci. Data, 16, 3795–3819, https://doi.org/10.5194/essd-16-3795-2024, https://doi.org/10.5194/essd-16-3795-2024, 2024
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This study describes 1 km all-weather instantaneous and daily mean land surface temperature (LST) datasets on the global scale during 2000–2020. It is the first attempt to synergistically estimate all-weather instantaneous and daily mean LST data on a long global-scale time series. The generated datasets were evaluated by the observations from in situ stations and other LST datasets, and the evaluation indicated that the dataset is sufficiently reliable.
Qi Zhang, Chiyuan Miao, Jiajia Su, Jiaojiao Gou, Jinlong Hu, Xi Zhao, and Ye Xu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-270, https://doi.org/10.5194/essd-2024-270, 2024
Revised manuscript accepted for ESSD
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Our study introduces CHM_Drought, an advanced meteorological drought dataset covering mainland China, offering detailed insights from 1961 to 2022 at a spatial resolution of 0.1°. This dataset incorporates six key drought indices, including multi-scale versions, facilitating early detection and monitoring of droughts. Through the provision of consistent and reliable data, CHM_Drought enhances our understanding of drought patterns, aiding in effective water management and agricultural planning.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
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During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
Yaoming Ma, Zhipeng Xie, Yingying Chen, Shaomin Liu, Tao Che, Ziwei Xu, Lunyu Shang, Xiaobo He, Xianhong Meng, Weiqiang Ma, Baiqing Xu, Huabiao Zhao, Junbo Wang, Guangjian Wu, and Xin Li
Earth Syst. Sci. Data, 16, 3017–3043, https://doi.org/10.5194/essd-16-3017-2024, https://doi.org/10.5194/essd-16-3017-2024, 2024
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Current models and satellites struggle to accurately represent the land–atmosphere (L–A) interactions over the Tibetan Plateau. We present the most extensive compilation of in situ observations to date, comprising 17 years of data on L–A interactions across 12 sites. This quality-assured benchmark dataset provides independent validation to improve models and remote sensing for the region, and it enables new investigations of fine-scale L–A processes and their mechanistic drivers.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, https://doi.org/10.5194/essd-16-2701-2024, 2024
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This paper describes multifrequency radar observations of clouds and precipitation during the EPCAPE campaign. The data sets were obtained from CloudCube, a Ka-, W-, and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals. This data collection provides a unique opportunity to study hydrometeors with diameters in the millimeter and submillimeter size range that can be used to better understand the drop size distribution within clouds and precipitation.
Francesca Lappin, Gijs de Boer, Petra Klein, Jonathan Hamilton, Michelle Spencer, Radiance Calmer, Antonio R. Segales, Michael Rhodes, Tyler M. Bell, Justin Buchli, Kelsey Britt, Elizabeth Asher, Isaac Medina, Brian Butterworth, Leia Otterstatter, Madison Ritsch, Bryony Puxley, Angelina Miller, Arianna Jordan, Ceu Gomez-Faulk, Elizabeth Smith, Steven Borenstein, Troy Thornberry, Brian Argrow, and Elizabeth Pillar-Little
Earth Syst. Sci. Data, 16, 2525–2541, https://doi.org/10.5194/essd-16-2525-2024, https://doi.org/10.5194/essd-16-2525-2024, 2024
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This article provides an overview of the lower-atmospheric dataset collected by two uncrewed aerial systems near the Gulf of Mexico coastline south of Houston, TX, USA, as part of the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. The data were collected through boundary layer transitions, through sea breeze circulations, and in the pre- and near-storm environment to understand how these processes influence the coastal environment.
Kaixu Bai, Ke Li, Liuqing Shao, Xinran Li, Chaoshun Liu, Zhengqiang Li, Mingliang Ma, Di Han, Yibing Sun, Zhe Zheng, Ruijie Li, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data, 16, 2425–2448, https://doi.org/10.5194/essd-16-2425-2024, https://doi.org/10.5194/essd-16-2425-2024, 2024
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A global gap-free high-resolution air pollutant dataset (LGHAP v2) was generated to provide spatially contiguous AOD and PM2.5 concentration maps with daily 1 km resolution from 2000 to 2021. This gap-free dataset has good data accuracies compared to ground-based AOD and PM2.5 concentration observations, which is a reliable database to advance aerosol-related studies and trigger multidisciplinary applications for environmental management, health risk assessment, and climate change analysis.
Finn Burgemeister, Marco Clemens, and Felix Ament
Earth Syst. Sci. Data, 16, 2317–2332, https://doi.org/10.5194/essd-16-2317-2024, https://doi.org/10.5194/essd-16-2317-2024, 2024
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Knowledge of small-scale rainfall variability is needed for hydro-meteorological applications in urban areas. Therefore, we present an open-access data set covering reanalyzed radar reflectivities and rainfall estimates measured by a weather radar at high spatio-temporal resolution in the urban environment of Hamburg between 2013 and 2021. We describe the data reanalysis, outline the measurement’s performance for long time periods, and discuss open issues and limitations of the data set.
Nicola Bodini, Mike Optis, Stephanie Redfern, David Rosencrans, Alex Rybchuk, Julie K. Lundquist, Vincent Pronk, Simon Castagneri, Avi Purkayastha, Caroline Draxl, Raghavendra Krishnamurthy, Ethan Young, Billy Roberts, Evan Rosenlieb, and Walter Musial
Earth Syst. Sci. Data, 16, 1965–2006, https://doi.org/10.5194/essd-16-1965-2024, https://doi.org/10.5194/essd-16-1965-2024, 2024
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This article presents the 2023 National Offshore Wind data set (NOW-23), an updated resource for offshore wind information in the US. It replaces the Wind Integration National Dataset (WIND) Toolkit, offering improved accuracy through advanced weather prediction models. The data underwent regional tuning and validation and can be accessed at no cost.
Longhu Chen, Qinqin Wang, Guofeng Zhu, Xinrui Lin, Dongdong Qiu, Yinying Jiao, Siyu Lu, Rui Li, Gaojia Meng, and Yuhao Wang
Earth Syst. Sci. Data, 16, 1543–1557, https://doi.org/10.5194/essd-16-1543-2024, https://doi.org/10.5194/essd-16-1543-2024, 2024
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We have compiled data regarding stable precipitation isotopes from 842 sampling points throughout the Eurasian continent since 1961, accumulating a total of 51 753 data records. The collected data have undergone pre-processing and statistical analysis. We also analysed the spatiotemporal distribution of stable precipitation isotopes across the Eurasian continent and their interrelationships with meteorological elements.
Valentin Wiener, Marie-Laure Roussel, Christophe Genthon, Étienne Vignon, Jacopo Grazioli, and Alexis Berne
Earth Syst. Sci. Data, 16, 821–836, https://doi.org/10.5194/essd-16-821-2024, https://doi.org/10.5194/essd-16-821-2024, 2024
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This paper presents 7 years of data from a precipitation radar deployed at the Dumont d'Urville station in East Antarctica. The main characteristics of the dataset are outlined in a short statistical study. Interannual and seasonal variability are also investigated. Then, we extensively describe the processing method to retrieve snowfall profiles from the radar data. Lastly, a brief comparison is made with two climate models as an application example of the dataset.
Ling Yuan, Xuelong Chen, Yaoming Ma, Cunbo Han, Binbin Wang, and Weiqiang Ma
Earth Syst. Sci. Data, 16, 775–801, https://doi.org/10.5194/essd-16-775-2024, https://doi.org/10.5194/essd-16-775-2024, 2024
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Accurately monitoring and understanding the spatial–temporal variability of evapotranspiration (ET) components over the Tibetan Plateau (TP) remains difficult. Here, 37 years (1982–2018) of monthly ET component data for the TP was produced, and the data are consistent with measurements. The annual average ET for the TP was about 0.93 (± 0.037) × 103 Gt yr−1. The rate of increase of the ET was around 0.96 mm yr−1. The increase in the ET can be explained by warming and wetting of the climate.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
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Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Hadleigh D. Thompson, Julie M. Thériault, Stephen J. Déry, Ronald E. Stewart, Dominique Boisvert, Lisa Rickard, Nicolas R. Leroux, Matteo Colli, and Vincent Vionnet
Earth Syst. Sci. Data, 15, 5785–5806, https://doi.org/10.5194/essd-15-5785-2023, https://doi.org/10.5194/essd-15-5785-2023, 2023
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The Saint John River experiment on Cold Season Storms was conducted in northwest New Brunswick, Canada, to investigate the types of precipitation that can lead to ice jams and flooding along the river. We deployed meteorological instruments, took precipitation measurements and photographs of snowflakes, and launched weather balloons. These data will help us to better understand the atmospheric conditions that can affect local communities and townships downstream during the spring melt season.
Raghavendra Krishnamurthy, Gabriel García Medina, Brian Gaudet, William I. Gustafson Jr., Evgueni I. Kassianov, Jinliang Liu, Rob K. Newsom, Lindsay M. Sheridan, and Alicia M. Mahon
Earth Syst. Sci. Data, 15, 5667–5699, https://doi.org/10.5194/essd-15-5667-2023, https://doi.org/10.5194/essd-15-5667-2023, 2023
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Our understanding and ability to observe and model air–sea processes has been identified as a principal limitation to our ability to predict future weather. Few observations exist offshore along the coast of California. To improve our understanding of the air–sea transition zone and support the wind energy industry, two buoys with state-of-the-art equipment were deployed for 1 year. In this article, we present details of the post-processing, algorithms, and analyses.
Giovanni Chellini, Rosa Gierens, Kerstin Ebell, Theresa Kiszler, Pavel Krobot, Alexander Myagkov, Vera Schemann, and Stefan Kneifel
Earth Syst. Sci. Data, 15, 5427–5448, https://doi.org/10.5194/essd-15-5427-2023, https://doi.org/10.5194/essd-15-5427-2023, 2023
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We present a comprehensive quality-controlled dataset of remote sensing observations of low-level mixed-phase clouds (LLMPCs) taken at the high Arctic site of Ny-Ålesund, Svalbard, Norway. LLMPCs occur frequently in the Arctic region, and substantially warm the surface. However, our understanding of microphysical processes in these clouds is incomplete. This dataset includes a comprehensive set of variables which allow for extensive investigation of such processes in LLMPCs at the site.
Emma L. Robinson, Chris Huntingford, Valyaveetil Shamsudheen Semeena, and James M. Bullock
Earth Syst. Sci. Data, 15, 5371–5401, https://doi.org/10.5194/essd-15-5371-2023, https://doi.org/10.5194/essd-15-5371-2023, 2023
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CHESS-SCAPE is a suite of high-resolution climate projections for the UK to 2080, derived from United Kingdom Climate Projections 2018 (UKCP18), designed to support climate impact modelling. It contains four realisations of four scenarios of future greenhouse gas levels (RCP2.6, 4.5, 6.0 and 8.5), with and without bias correction to historical data. The variables are available at 1 km resolution and a daily time step, with monthly, seasonal and annual means and 20-year mean-monthly time slices.
Motoshi Nishimura, Teruo Aoki, Masashi Niwano, Sumito Matoba, Tomonori Tanikawa, Tetsuhide Yamasaki, Satoru Yamaguchi, and Koji Fujita
Earth Syst. Sci. Data, 15, 5207–5226, https://doi.org/10.5194/essd-15-5207-2023, https://doi.org/10.5194/essd-15-5207-2023, 2023
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We presented the method of data quality checks and the dataset for two ground weather observations in northwest Greenland. We found that the warm and clear weather conditions in the 2015, 2019, and 2020 summers caused the snowmelt and the decline in surface reflectance of solar radiation at a low-elevated site (SIGMA-B; 944 m), but those were not seen at the high-elevated site (SIGMA-A; 1490 m). We hope that our data management method and findings will help climate scientists.
Shaomin Liu, Ziwei Xu, Tao Che, Xin Li, Tongren Xu, Zhiguo Ren, Yang Zhang, Junlei Tan, Lisheng Song, Ji Zhou, Zhongli Zhu, Xiaofan Yang, Rui Liu, and Yanfei Ma
Earth Syst. Sci. Data, 15, 4959–4981, https://doi.org/10.5194/essd-15-4959-2023, https://doi.org/10.5194/essd-15-4959-2023, 2023
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We present a suite of observational datasets from artificial and natural oases–desert systems that consist of long-term turbulent flux and auxiliary data, including hydrometeorological, vegetation, and soil parameters, from 2012 to 2021. We confirm that the 10-year, long-term dataset presented in this study is of high quality with few missing data, and we believe that the data will support ecological security and sustainable development in oasis–desert areas.
Gina C. Jozef, Robert Klingel, John J. Cassano, Björn Maronga, Gijs de Boer, Sandro Dahlke, and Christopher J. Cox
Earth Syst. Sci. Data, 15, 4983–4995, https://doi.org/10.5194/essd-15-4983-2023, https://doi.org/10.5194/essd-15-4983-2023, 2023
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Observations from the MOSAiC expedition relating to lower-atmospheric temperature, wind, stability, moisture, and surface radiation budget from radiosondes, a meteorological tower, radiation station, and ceilometer were compiled to create a dataset which describes the thermodynamic and kinematic state of the central Arctic lower atmosphere between October 2019 and September 2020. This paper describes the methods used to develop this lower-atmospheric properties dataset.
Karl-Göran Karlsson, Martin Stengel, Jan Fokke Meirink, Aku Riihelä, Jörg Trentmann, Tom Akkermans, Diana Stein, Abhay Devasthale, Salomon Eliasson, Erik Johansson, Nina Håkansson, Irina Solodovnik, Nikos Benas, Nicolas Clerbaux, Nathalie Selbach, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 15, 4901–4926, https://doi.org/10.5194/essd-15-4901-2023, https://doi.org/10.5194/essd-15-4901-2023, 2023
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This paper presents a global climate data record on cloud parameters, radiation at the surface and at the top of atmosphere, and surface albedo. The temporal coverage is 1979–2020 (42 years) and the data record is also continuously updated until present time. Thus, more than four decades of climate parameters are provided. Based on CLARA-A3, studies on distribution of clouds and radiation parameters can be made and, especially, investigations of climate trends and evaluation of climate models.
Boyang Jiao, Yucheng Su, Qingxiang Li, Veronica Manara, and Martin Wild
Earth Syst. Sci. Data, 15, 4519–4535, https://doi.org/10.5194/essd-15-4519-2023, https://doi.org/10.5194/essd-15-4519-2023, 2023
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This paper develops an observational integrated and homogenized global-terrestrial (except for Antarctica) SSRIH station. This is interpolated into a 5° × 5° SSRIH grid and reconstructed into a long-term (1955–2018) global land (except for Antarctica) 5° × 2.5° SSR anomaly dataset (SSRIH20CR) by an improved partial convolutional neural network deep-learning method. SSRIH20CR yields trends of −1.276 W m−2 per decade over the dimming period and 0.697 W m−2 per decade over the brightening period.
Lukas Frank, Marius Opsanger Jonassen, Teresa Remes, Florina Roana Schalamon, and Agnes Stenlund
Earth Syst. Sci. Data, 15, 4219–4234, https://doi.org/10.5194/essd-15-4219-2023, https://doi.org/10.5194/essd-15-4219-2023, 2023
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The Isfjorden Weather Information Network (IWIN) provides continuous meteorological near-surface observations from Isfjorden in Svalbard. The network combines permanent automatic weather stations on lighthouses along the coast line with mobile stations on board small tourist cruise ships regularly trafficking the fjord during spring to autumn. All data are available online in near-real time. Besides their scientific value, IWIN data crucially enhance the safety of field activities in the region.
Jingya Han, Chiyuan Miao, Jiaojiao Gou, Haiyan Zheng, Qi Zhang, and Xiaoying Guo
Earth Syst. Sci. Data, 15, 3147–3161, https://doi.org/10.5194/essd-15-3147-2023, https://doi.org/10.5194/essd-15-3147-2023, 2023
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Constructing a high-quality, long-term daily precipitation dataset is essential to current hydrometeorology research. This study aims to construct a long-term daily precipitation dataset with different spatial resolutions based on 2839 gauge observations. The constructed precipitation dataset shows reliable quality compared with the other available precipitation products and is expected to facilitate the advancement of drought monitoring, flood forecasting, and hydrological modeling.
Christian Borger, Steffen Beirle, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3023–3049, https://doi.org/10.5194/essd-15-3023-2023, https://doi.org/10.5194/essd-15-3023-2023, 2023
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This study presents a long-term data set of monthly mean total column water vapour (TCWV) based on measurements of the Ozone Monitoring Instrument (OMI) covering the time range from January 2005 to December 2020. We describe how the TCWV values are retrieved from UV–Vis satellite spectra and demonstrate that the OMI TCWV data set is in good agreement with various different reference data sets. Moreover, we also show that it fulfills typical stability requirements for climate data records.
Jonathan Demaeyer, Jonas Bhend, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, and Stéphane Vannitsem
Earth Syst. Sci. Data, 15, 2635–2653, https://doi.org/10.5194/essd-15-2635-2023, https://doi.org/10.5194/essd-15-2635-2023, 2023
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A benchmark dataset is proposed to compare different statistical postprocessing methods used in forecasting centers to properly calibrate ensemble weather forecasts. This dataset is based on ensemble forecasts covering a portion of central Europe and includes the corresponding observations. Examples on how to download and use the data are provided, a set of evaluation methods is proposed, and a first benchmark of several methods for the correction of 2 m temperature forecasts is performed.
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data, 15, 2445–2464, https://doi.org/10.5194/essd-15-2445-2023, https://doi.org/10.5194/essd-15-2445-2023, 2023
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We present the first 1 km, daily, global climate dataset for climate impact studies. We show that the high-resolution data have a decreased bias and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
Elisa Adirosi, Federico Porcù, Mario Montopoli, Luca Baldini, Alessandro Bracci, Vincenzo Capozzi, Clizia Annella, Giorgio Budillon, Edoardo Bucchignani, Alessandra Lucia Zollo, Orietta Cazzuli, Giulio Camisani, Renzo Bechini, Roberto Cremonini, Andrea Antonini, Alberto Ortolani, Samantha Melani, Paolo Valisa, and Simone Scapin
Earth Syst. Sci. Data, 15, 2417–2429, https://doi.org/10.5194/essd-15-2417-2023, https://doi.org/10.5194/essd-15-2417-2023, 2023
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The paper describes the database of 1 min drop size distribution (DSD) of atmospheric precipitation collected by the Italian disdrometer network over the last 10 years. These data are useful for several applications that range from climatological, meteorological and hydrological uses to telecommunications, agriculture and conservation of cultural heritage exposed to precipitation. Descriptions of the processing and of the database organization, along with some examples, are provided.
Jinfang Yin, Xudong Liang, Yanxin Xie, Feng Li, Kaixi Hu, Lijuan Cao, Feng Chen, Haibo Zou, Feng Zhu, Xin Sun, Jianjun Xu, Geli Wang, Ying Zhao, and Juanjuan Liu
Earth Syst. Sci. Data, 15, 2329–2346, https://doi.org/10.5194/essd-15-2329-2023, https://doi.org/10.5194/essd-15-2329-2023, 2023
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A collection of regional reanalysis datasets has been produced. However, little attention has been paid to East Asia, and there are no long-term, physically consistent regional reanalysis data available. The East Asia Reanalysis System was developed using the WRF model and GSI data assimilation system. A 39-year (1980–2018) reanalysis dataset is available for the East Asia region, at a high temporal (of 3 h) and spatial resolution (of 12 km), for mesoscale weather and regional climate studies.
John Erik Engström, Lennart Wern, Sverker Hellström, Erik Kjellström, Chunlüe Zhou, Deliang Chen, and Cesar Azorin-Molina
Earth Syst. Sci. Data, 15, 2259–2277, https://doi.org/10.5194/essd-15-2259-2023, https://doi.org/10.5194/essd-15-2259-2023, 2023
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Newly digitized wind speed observations provide data from the time period from around 1920 to the present, enveloping one full century of wind measurements. The results of this work enable the investigation of the historical variability and trends in surface wind speed in Sweden for
the last century.
Ulrike Herzschuh, Thomas Böhmer, Chenzhi Li, Manuel Chevalier, Raphaël Hébert, Anne Dallmeyer, Xianyong Cao, Nancy H. Bigelow, Larisa Nazarova, Elena Y. Novenko, Jungjae Park, Odile Peyron, Natalia A. Rudaya, Frank Schlütz, Lyudmila S. Shumilovskikh, Pavel E. Tarasov, Yongbo Wang, Ruilin Wen, Qinghai Xu, and Zhuo Zheng
Earth Syst. Sci. Data, 15, 2235–2258, https://doi.org/10.5194/essd-15-2235-2023, https://doi.org/10.5194/essd-15-2235-2023, 2023
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Climate reconstruction from proxy data can help evaluate climate models. We present pollen-based reconstructions of mean July temperature, mean annual temperature, and annual precipitation from 2594 pollen records from the Northern Hemisphere, using three reconstruction methods (WA-PLS, WA-PLS_tailored, and MAT). Since no global or hemispheric synthesis of quantitative precipitation changes are available for the Holocene so far, this dataset will be of great value to the geoscientific community.
Aart Overeem, Else van den Besselaar, Gerard van der Schrier, Jan Fokke Meirink, Emiel van der Plas, and Hidde Leijnse
Earth Syst. Sci. Data, 15, 1441–1464, https://doi.org/10.5194/essd-15-1441-2023, https://doi.org/10.5194/essd-15-1441-2023, 2023
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EURADCLIM is a new precipitation dataset covering a large part of Europe. It is based on weather radar data to provide local precipitation information every hour and combined with rain gauge data to obtain good precipitation estimates. EURADCLIM provides a much better reference for validation of weather model output and satellite precipitation datasets. It also allows for climate monitoring and better evaluation of extreme precipitation events and their impact (landslides, flooding).
Alfonso Ferrone and Alexis Berne
Earth Syst. Sci. Data, 15, 1115–1132, https://doi.org/10.5194/essd-15-1115-2023, https://doi.org/10.5194/essd-15-1115-2023, 2023
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This article presents the datasets collected between November 2019 and February 2020 in the vicinity of the Belgian research base Princess Elisabeth Antarctica. Five meteorological radars, a multi-angle snowflake camera, three weather stations, and two radiometers have been deployed at five sites, up to a maximum distance of 30 km from the base. Their varied locations allow the study of spatial variability in snowfall and its interaction with the complex terrain in the region.
José Dias Neto, Louise Nuijens, Christine Unal, and Steven Knoop
Earth Syst. Sci. Data, 15, 769–789, https://doi.org/10.5194/essd-15-769-2023, https://doi.org/10.5194/essd-15-769-2023, 2023
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This paper describes a dataset from a novel experimental setup to retrieve wind speed and direction profiles, combining cloud radars and wind lidar. This setup allows retrieving profiles from near the surface to the top of clouds. The field campaign occurred in Cabauw, the Netherlands, between September 13th and October 3rd 2021. This paper also provides examples of applications of this dataset (e.g. studying atmospheric turbulence, validating numerical atmospheric models).
Peng Yuan, Geoffrey Blewitt, Corné Kreemer, William C. Hammond, Donald Argus, Xungang Yin, Roeland Van Malderen, Michael Mayer, Weiping Jiang, Joseph Awange, and Hansjörg Kutterer
Earth Syst. Sci. Data, 15, 723–743, https://doi.org/10.5194/essd-15-723-2023, https://doi.org/10.5194/essd-15-723-2023, 2023
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We developed a 5 min global integrated water vapour (IWV) product from 12 552 ground-based GPS stations in 2020. It contains more than 1 billion IWV estimates. The dataset is an enhanced version of the existing operational GPS IWV dataset from the Nevada Geodetic Laboratory. The enhancement is reached by using accurate meteorological information from ERA5 for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. The dataset is recommended for high-accuracy applications.
Yaozhi Jiang, Kun Yang, Youcun Qi, Xu Zhou, Jie He, Hui Lu, Xin Li, Yingying Chen, Xiaodong Li, Bingrong Zhou, Ali Mamtimin, Changkun Shao, Xiaogang Ma, Jiaxin Tian, and Jianhong Zhou
Earth Syst. Sci. Data, 15, 621–638, https://doi.org/10.5194/essd-15-621-2023, https://doi.org/10.5194/essd-15-621-2023, 2023
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Our work produces a long-term (1979–2020) high-resolution (1/30°, daily) precipitation dataset for the Third Pole (TP) region by merging an advanced atmospheric simulation with high-density rain gauge (more than 9000) observations. Validation shows that the produced dataset performs better than the currently widely used precipitation datasets in the TP. This dataset can be used for hydrological, meteorological and ecological studies in the TP.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
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Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Hui Zhang, Ming Luo, Yongquan Zhao, Lijie Lin, Erjia Ge, Yuanjian Yang, Guicai Ning, Jing Cong, Zhaoliang Zeng, Ke Gui, Jing Li, Ting On Chan, Xiang Li, Sijia Wu, Peng Wang, and Xiaoyu Wang
Earth Syst. Sci. Data, 15, 359–381, https://doi.org/10.5194/essd-15-359-2023, https://doi.org/10.5194/essd-15-359-2023, 2023
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We generate the first monthly high-resolution (1 km) human thermal index collection (HiTIC-Monthly) in China over 2003–2020, in which 12 human-perceived temperature indices are generated by LightGBM. The HiTIC-Monthly dataset has a high accuracy (R2 = 0.996, RMSE = 0.693 °C, MAE = 0.512 °C) and describes explicit spatial variations for fine-scale studies. It is freely available at https://zenodo.org/record/6895533 and https://data.tpdc.ac.cn/disallow/036e67b7-7a3a-4229-956f-40b8cd11871d.
Jun Qin, Weihao Pan, Min He, Ning Lu, Ling Yao, Hou Jiang, and Chenghu Zhou
Earth Syst. Sci. Data, 15, 331–344, https://doi.org/10.5194/essd-15-331-2023, https://doi.org/10.5194/essd-15-331-2023, 2023
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To enrich a glacial surface air temperature (SAT) product of a long time series, an ensemble learning model is constructed to estimate monthly SATs from satellite land surface temperatures at a spatial resolution of 1 km, and long-term glacial SATs from 1961 to 2020 are reconstructed using a Bayesian linear regression. This product reveals the overall warming trend and the spatial heterogeneity of warming on TP glaciers and helps to monitor glacier warming, analyze glacier evolution, etc.
Tao Zhang, Yuyu Zhou, Kaiguang Zhao, Zhengyuan Zhu, Gang Chen, Jia Hu, and Li Wang
Earth Syst. Sci. Data, 14, 5637–5649, https://doi.org/10.5194/essd-14-5637-2022, https://doi.org/10.5194/essd-14-5637-2022, 2022
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We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and Tmin) dataset (2003–2020) using a novel statistical model. The average root mean square errors ranged from 1.20 to 2.44 °C for Tmax and 1.69 to 2.39 °C for Tmin. The gridded global air temperature dataset is of great use in a variety of studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting.
Benjamin Fersch, Andreas Wagner, Bettina Kamm, Endrit Shehaj, Andreas Schenk, Peng Yuan, Alain Geiger, Gregor Moeller, Bernhard Heck, Stefan Hinz, Hansjörg Kutterer, and Harald Kunstmann
Earth Syst. Sci. Data, 14, 5287–5307, https://doi.org/10.5194/essd-14-5287-2022, https://doi.org/10.5194/essd-14-5287-2022, 2022
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In this study, a comprehensive multi-disciplinary dataset for tropospheric water vapor was developed. Geodetic, photogrammetric, and atmospheric modeling and data fusion techniques were used to obtain maps of water vapor in a high spatial and temporal resolution. It could be shown that regional weather simulations for different seasons benefit from assimilating these maps and that the combination of the different observation techniques led to positive synergies.
Craig D. Smith, Eva Mekis, Megan Hartwell, and Amber Ross
Earth Syst. Sci. Data, 14, 5253–5265, https://doi.org/10.5194/essd-14-5253-2022, https://doi.org/10.5194/essd-14-5253-2022, 2022
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It is well understood that precipitation gauges underestimate the measurement of solid precipitation (snow) as a result of systematic bias caused by wind. Relationships between the wind speed and gauge catch efficiency of solid precipitation have been previously established and are applied to the hourly precipitation measurements made between 2001 and 2019 in the automated Environment and Climate Change Canada observation network. The adjusted data are available for download and use.
Zen Mariani, Laura Huang, Robert Crawford, Jean-Pierre Blanchet, Shannon Hicks-Jalali, Eva Mekis, Ludovick Pelletier, Peter Rodriguez, and Kevin Strawbridge
Earth Syst. Sci. Data, 14, 4995–5017, https://doi.org/10.5194/essd-14-4995-2022, https://doi.org/10.5194/essd-14-4995-2022, 2022
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Environment and Climate Change Canada (ECCC) commissioned two supersites in Iqaluit (64°N, 69°W) and Whitehorse (61°N, 135°W) to provide new and enhanced automated and continuous altitude-resolved meteorological observations as part of the Canadian Arctic Weather Science (CAWS) project. These observations are being used to test new technologies, provide recommendations to the optimal Arctic observing system, and evaluate and improve the performance of numerical weather forecast systems.
Eva Beele, Maarten Reyniers, Raf Aerts, and Ben Somers
Earth Syst. Sci. Data, 14, 4681–4717, https://doi.org/10.5194/essd-14-4681-2022, https://doi.org/10.5194/essd-14-4681-2022, 2022
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This paper presents crowdsourced data from the Leuven.cool network, a citizen science network of around 100 low-cost weather stations distributed across Leuven, Belgium. The temperature data have undergone a quality control (QC) and correction procedure. The procedure consists of three levels that remove implausible measurements while also correcting for between-station and station-specific temperature biases.
Auguste Gires, Jerry Jose, Ioulia Tchiguirinskaia, and Daniel Schertzer
Earth Syst. Sci. Data, 14, 3807–3819, https://doi.org/10.5194/essd-14-3807-2022, https://doi.org/10.5194/essd-14-3807-2022, 2022
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The Hydrology Meteorology and Complexity laboratory of École des Ponts ParisTech (https://hmco.enpc.fr) has made a data set of high-resolution atmospheric measurements (rainfall, wind, temperature, pressure, and humidity) available. It comes from a campaign carried out on a meteorological mast located on a wind farm in the framework of the Rainfall Wind Turbine or Turbulence project (RW-Turb; supported by the French National Research Agency – ANR-19-CE05-0022).
Bastian Kirsch, Cathy Hohenegger, Daniel Klocke, Rainer Senke, Michael Offermann, and Felix Ament
Earth Syst. Sci. Data, 14, 3531–3548, https://doi.org/10.5194/essd-14-3531-2022, https://doi.org/10.5194/essd-14-3531-2022, 2022
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Conventional observation networks are too coarse to resolve the horizontal structure of kilometer-scale atmospheric processes. We present the FESST@HH field experiment that took place in Hamburg (Germany) during summer 2020 and featured a dense network of 103 custom-built, low-cost weather stations. The data set is capable of providing new insights into the structure of convective cold pools and the nocturnal urban heat island and variations of local temperature fluctuations.
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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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