Articles | Volume 18, issue 4
https://doi.org/10.5194/tc-18-1925-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-18-1925-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Apr 2024
Research article |
| 26 Apr 2024
| 26 Apr 2024
A cold laboratory hyperspectral imaging system to map grain size and ice layer distributions in firn cores
Graduate Program of Hydrologic Sciences, University of Nevada, Reno, Reno, NV, USA
Department of Geological Sciences and Engineering, University of Nevada, Reno, Reno, NV, USA
Kaitlin M. Keegan
Department of Geological Sciences and Engineering, University of Nevada, Reno, Reno, NV, USA
S. McKenzie Skiles
Department of Geography, University of Utah, Salt Lake City, UT, USA
Christopher P. Donahue
Department of Geography, Earth and Environmental Sciences, University of Northern British Columbia, Prince George, BC, Canada
Erich C. Osterberg
Department of Earth Sciences, Dartmouth College, Hanover, NH, USA
Robert L. Hawley
Department of Earth Sciences, Dartmouth College, Hanover, NH, USA
Hans-Peter Marshall
Department of Geosciences, Boise State University, Boise, ID, USA
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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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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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James Dillon, Christopher Donahue, Evan Schehrer, Karl Birkeland, and Kevin Hammonds
The Cryosphere, 18, 2557–2582, https://doi.org/10.5194/tc-18-2557-2024, https://doi.org/10.5194/tc-18-2557-2024, 2024
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The Cryosphere, 18, 575–592, https://doi.org/10.5194/tc-18-575-2024, https://doi.org/10.5194/tc-18-575-2024, 2024
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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
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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.
Jack Tarricone, Ryan W. Webb, Hans-Peter Marshall, Anne W. Nolin, and Franz J. Meyer
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Aaron Chesler, Dominic Winski, Karl Kreutz, Bess Koffman, Erich Osterberg, David Ferris, Zayta Thundercloud, Joseph Mohan, Jihong Cole-Dai, Mark Wells, Michael Handley, Aaron Putnam, Katherine Anderson, and Natalie Harmon
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Ice core microparticle data typically use geometry assumptions to calculate particle mass and flux. We use dynamic particle imaging, a novel technique for ice core dust analyses, combined with traditional laser particle counting and Coulter counter techniques to assess particle shape in the South Pole Ice Core (SPC14) spanning 50–16 ka. Our results suggest that particles are dominantly ellipsoidal in shape and that spherical assumptions overestimate particle mass and flux.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
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Zachary Fair, Mark Flanner, Adam Schneider, and S. McKenzie Skiles
The Cryosphere, 16, 3801–3814, https://doi.org/10.5194/tc-16-3801-2022, https://doi.org/10.5194/tc-16-3801-2022, 2022
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Snow grain size is important to determine the age and structure of snow, but it is difficult to measure. Snow grain size can be found from airborne and spaceborne observations by measuring near-infrared energy reflected from snow. In this study, we use the SNICAR radiative transfer model and a Monte Carlo model to examine how snow grain size measurements change with snow structure and solar zenith angle. We show that improved understanding of these variables improves snow grain size precision.
Leung Tsang, Michael Durand, Chris Derksen, Ana P. Barros, Do-Hyuk Kang, Hans Lievens, Hans-Peter Marshall, Jiyue Zhu, Joel Johnson, Joshua King, Juha Lemmetyinen, Melody Sandells, Nick Rutter, Paul Siqueira, Anne Nolin, Batu Osmanoglu, Carrie Vuyovich, Edward Kim, Drew Taylor, Ioanna Merkouriadi, Ludovic Brucker, Mahdi Navari, Marie Dumont, Richard Kelly, Rhae Sung Kim, Tien-Hao Liao, Firoz Borah, and Xiaolan Xu
The Cryosphere, 16, 3531–3573, https://doi.org/10.5194/tc-16-3531-2022, https://doi.org/10.5194/tc-16-3531-2022, 2022
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Snow water equivalent (SWE) is of fundamental importance to water, energy, and geochemical cycles but is poorly observed globally. Synthetic aperture radar (SAR) measurements at X- and Ku-band can address this gap. This review serves to inform the broad snow research, monitoring, and application communities about the progress made in recent decades to move towards a new satellite mission capable of addressing the needs of the geoscience researchers and users.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
Earth Syst. Sci. Data, 14, 3915–3945, https://doi.org/10.5194/essd-14-3915-2022, https://doi.org/10.5194/essd-14-3915-2022, 2022
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The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
Hans Lievens, Isis Brangers, Hans-Peter Marshall, Tobias Jonas, Marc Olefs, and Gabriëlle De Lannoy
The Cryosphere, 16, 159–177, https://doi.org/10.5194/tc-16-159-2022, https://doi.org/10.5194/tc-16-159-2022, 2022
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Snow depth observations at high spatial resolution from the Sentinel-1 satellite mission are presented over the European Alps. The novel observations can improve our knowledge of seasonal snow mass in areas with complex topography, where satellite-based estimates are currently lacking, and benefit a number of applications including water resource management, flood forecasting, and numerical weather prediction.
Christopher Donahue, S. McKenzie Skiles, and Kevin Hammonds
The Cryosphere, 16, 43–59, https://doi.org/10.5194/tc-16-43-2022, https://doi.org/10.5194/tc-16-43-2022, 2022
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The amount of water within a snowpack is important information for predicting snowmelt and wet-snow avalanches. From within a controlled laboratory, the optimal method for measuring liquid water content (LWC) at the snow surface or along a snow pit profile using near-infrared imagery was determined. As snow samples melted, multiple models to represent wet-snow reflectance were assessed against a more established LWC instrument. The best model represents snow as separate spheres of ice and water.
Mark G. Flanner, Julian B. Arnheim, Joseph M. Cook, Cheng Dang, Cenlin He, Xianglei Huang, Deepak Singh, S. McKenzie Skiles, Chloe A. Whicker, and Charles S. Zender
Geosci. Model Dev., 14, 7673–7704, https://doi.org/10.5194/gmd-14-7673-2021, https://doi.org/10.5194/gmd-14-7673-2021, 2021
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We present the technical formulation and evaluation of a publicly available code and web-based model to simulate the spectral albedo of snow. Our model accounts for numerous features of the snow state and ambient conditions, including the the presence of light-absorbing matter like black and brown carbon, mineral dust, volcanic ash, and snow algae. Carbon dioxide snow, found on Mars, is also represented. The model accurately reproduces spectral measurements of clean and contaminated snow.
Joachim Meyer, McKenzie Skiles, Jeffrey Deems, Kat Boremann, and David Shean
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-281, https://doi.org/10.5194/hess-2021-281, 2021
Revised manuscript not accepted
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Seasonally accumulated snow in the mountains forms a natural water reservoir which is challenging to measure in the rugged and remote terrain. Here, we use overlapping aerial images that model surface elevations using software to map snow depth by calculating the difference in surface elevations between two dates, one with snow and one without. Results demonstrate the utility of aerial images to improve our ability to capture the amount of water held as snow in remote and inaccessible locations.
Ahmad Hojatimalekshah, Zachary Uhlmann, Nancy F. Glenn, Christopher A. Hiemstra, Christopher J. Tennant, Jake D. Graham, Lucas Spaete, Arthur Gelvin, Hans-Peter Marshall, James P. McNamara, and Josh Enterkine
The Cryosphere, 15, 2187–2209, https://doi.org/10.5194/tc-15-2187-2021, https://doi.org/10.5194/tc-15-2187-2021, 2021
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We describe the relationships between snow depth, vegetation canopy, and local-scale processes during the snow accumulation period using terrestrial laser scanning (TLS). In addition to topography and wind, our findings suggest the importance of fine-scale tree structure, species type, and distributions on snow depth. Snow depth increases from the canopy edge toward the open areas, but wind and topographic controls may affect this trend. TLS data are complementary to wide-area lidar surveys.
Ian E. McDowell, Neil F. Humphrey, Joel T. Harper, and Toby W. Meierbachtol
The Cryosphere, 15, 897–907, https://doi.org/10.5194/tc-15-897-2021, https://doi.org/10.5194/tc-15-897-2021, 2021
Short summary
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Ice temperature controls rates of internal deformation and the onset of basal sliding. To identify heat transfer mechanisms and englacial heat sources within Greenland's ablation zone, we examine a 2–3-year continuous temperature record from nine full-depth boreholes. Thermal decay after basal crevasses release heat in the near-basal ice likely produces the observed cooling. Basal crevasses in Greenland can affect the basal ice rheology and indicate a potentially complex basal hydrologic system.
Rhae Sung Kim, Sujay Kumar, Carrie Vuyovich, Paul Houser, Jessica Lundquist, Lawrence Mudryk, Michael Durand, Ana Barros, Edward J. Kim, Barton A. Forman, Ethan D. Gutmann, Melissa L. Wrzesien, Camille Garnaud, Melody Sandells, Hans-Peter Marshall, Nicoleta Cristea, Justin M. Pflug, Jeremy Johnston, Yueqian Cao, David Mocko, and Shugong Wang
The Cryosphere, 15, 771–791, https://doi.org/10.5194/tc-15-771-2021, https://doi.org/10.5194/tc-15-771-2021, 2021
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High SWE uncertainty is observed in mountainous and forested regions, highlighting the need for high-resolution snow observations in these regions. Substantial uncertainty in snow water storage in Tundra regions and the dominance of water storage in these regions points to the need for high-accuracy snow estimation. Finally, snow measurements during the melt season are most needed at high latitudes, whereas observations at near peak snow accumulations are most beneficial over the midlatitudes.
Joachim Meyer, S. McKenzie Skiles, Jeffrey Deems, Kat Bormann, and David Shean
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-34, https://doi.org/10.5194/tc-2021-34, 2021
Manuscript not accepted for further review
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Snow that accumulates seasonally in mountains forms a natural water reservoir and is difficult to measure in the rugged and remote landscapes. Here, we use modern software that models surface elevations from overlapping aerial images to map snow depth by calculating the difference in surface elevations between two dates, one with snow and one without. Results demonstrate the potential value of aerial images for understanding the amount of water held as snow in remote and inaccessible locations.
Jenna A. Epifanio, Edward J. Brook, Christo Buizert, Jon S. Edwards, Todd A. Sowers, Emma C. Kahle, Jeffrey P. Severinghaus, Eric J. Steig, Dominic A. Winski, Erich C. Osterberg, Tyler J. Fudge, Murat Aydin, Ekaterina Hood, Michael Kalk, Karl J. Kreutz, David G. Ferris, and Joshua A. Kennedy
Clim. Past, 16, 2431–2444, https://doi.org/10.5194/cp-16-2431-2020, https://doi.org/10.5194/cp-16-2431-2020, 2020
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A new ice core drilled at the South Pole provides a 54 000-year paleo-environmental record including the composition of the past atmosphere. This paper describes the gas chronology for the South Pole ice core, based on a high-resolution methane record. The new gas chronology, in combination with the existing ice age scale from Winski et al. (2019), allows a model-independent reconstruction of the delta age record.
Miguel A. Aguayo, Alejandro N. Flores, James P. McNamara, Hans-Peter Marshall, and Jodi Mead
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-451, https://doi.org/10.5194/hess-2020-451, 2020
Manuscript not accepted for further review
Alexandra Giese, Aaron Boone, Patrick Wagnon, and Robert Hawley
The Cryosphere, 14, 1555–1577, https://doi.org/10.5194/tc-14-1555-2020, https://doi.org/10.5194/tc-14-1555-2020, 2020
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Rocky debris on glacier surfaces is known to affect the melt of mountain glaciers. Debris can be dry or filled to varying extents with liquid water and ice; whether debris is dry, wet, and/or icy affects how efficiently heat is conducted through debris from its surface to the ice interface. Our paper presents a new energy balance model that simulates moisture phase, evolution, and location in debris. ISBA-DEB is applied to West Changri Nup glacier in Nepal to reveal important physical processes.
Colin R. Meyer, Kaitlin M. Keegan, Ian Baker, and Robert L. Hawley
The Cryosphere, 14, 1449–1458, https://doi.org/10.5194/tc-14-1449-2020, https://doi.org/10.5194/tc-14-1449-2020, 2020
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We describe snow compaction laboratory data with a new mathematical model. Using a compression device that is similar to a French press with snow instead of coffee grounds, Wang and Baker (2013) compacted numerous snow samples of different densities at a constant velocity to determine the force required for snow compaction. Our mathematical model for compaction includes airflow through snow and predicts the required force, in agreement with the experimental data.
Joseph M. Cook, Andrew J. Tedstone, Christopher Williamson, Jenine McCutcheon, Andrew J. Hodson, Archana Dayal, McKenzie Skiles, Stefan Hofer, Robert Bryant, Owen McAree, Andrew McGonigle, Jonathan Ryan, Alexandre M. Anesio, Tristram D. L. Irvine-Fynn, Alun Hubbard, Edward Hanna, Mark Flanner, Sathish Mayanna, Liane G. Benning, Dirk van As, Marian Yallop, James B. McQuaid, Thomas Gribbin, and Martyn Tranter
The Cryosphere, 14, 309–330, https://doi.org/10.5194/tc-14-309-2020, https://doi.org/10.5194/tc-14-309-2020, 2020
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Melting of the Greenland Ice Sheet (GrIS) is a major source of uncertainty for sea level rise projections. Ice-darkening due to the growth of algae has been recognized as a potential accelerator of melting. This paper measures and models the algae-driven ice melting and maps the algae over the ice sheet for the first time. We estimate that as much as 13 % total runoff from the south-western GrIS can be attributed to these algae, showing that they must be included in future mass balance models.
Gabriel Lewis, Erich Osterberg, Robert Hawley, Hans Peter Marshall, Tate Meehan, Karina Graeter, Forrest McCarthy, Thomas Overly, Zayta Thundercloud, and David Ferris
The Cryosphere, 13, 2797–2815, https://doi.org/10.5194/tc-13-2797-2019, https://doi.org/10.5194/tc-13-2797-2019, 2019
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We present accumulation records from sixteen 22–32 m long firn cores and 4436 km of ground-penetrating radar, covering the past 20–60 years of accumulation, collected across the western Greenland Ice Sheet percolation zone. Trends from both radar and firn cores, as well as commonly used regional climate models, show decreasing accumulation over the 1996–2016 period.
Dominic A. Winski, Tyler J. Fudge, David G. Ferris, Erich C. Osterberg, John M. Fegyveresi, Jihong Cole-Dai, Zayta Thundercloud, Thomas S. Cox, Karl J. Kreutz, Nikolas Ortman, Christo Buizert, Jenna Epifanio, Edward J. Brook, Ross Beaudette, Jeffrey Severinghaus, Todd Sowers, Eric J. Steig, Emma C. Kahle, Tyler R. Jones, Valerie Morris, Murat Aydin, Melinda R. Nicewonger, Kimberly A. Casey, Richard B. Alley, Edwin D. Waddington, Nels A. Iverson, Nelia W. Dunbar, Ryan C. Bay, Joseph M. Souney, Michael Sigl, and Joseph R. McConnell
Clim. Past, 15, 1793–1808, https://doi.org/10.5194/cp-15-1793-2019, https://doi.org/10.5194/cp-15-1793-2019, 2019
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A deep ice core was recently drilled at the South Pole to understand past variations in the Earth's climate. To understand the information contained within the ice, we present the relationship between the depth and age of the ice in the South Pole Ice Core. We found that the oldest ice in our record is from 54 302 ± 519 years ago. Our results show that, on average, 7.4 cm of snow falls at the South Pole each year.
Alexandra Giese, Steven Arcone, Robert Hawley, Gabriel Lewis, and Patrick Wagnon
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-60, https://doi.org/10.5194/tc-2019-60, 2019
Preprint withdrawn
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This manuscript defines a novel method of determining the depth of debris on a debris-covered glacier using 960 MHz Ground-Penetrating Radar, under circumstances which prevent the detection of a coherent reflection at the debris-ice interface. Our method was verified using full-scale debris-analog experiments and uses internal scattering within the debris layer. We use this method to measure debris thickness on Changri Nup Glacier, in the Nepal Himalaya.
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.
Nancy A. N. Bertler, Howard Conway, Dorthe Dahl-Jensen, Daniel B. Emanuelsson, Mai Winstrup, Paul T. Vallelonga, James E. Lee, Ed J. Brook, Jeffrey P. Severinghaus, Taylor J. Fudge, Elizabeth D. Keller, W. Troy Baisden, Richard C. A. Hindmarsh, Peter D. Neff, Thomas Blunier, Ross Edwards, Paul A. Mayewski, Sepp Kipfstuhl, Christo Buizert, Silvia Canessa, Ruzica Dadic, Helle A. Kjær, Andrei Kurbatov, Dongqi Zhang, Edwin D. Waddington, Giovanni Baccolo, Thomas Beers, Hannah J. Brightley, Lionel Carter, David Clemens-Sewall, Viorela G. Ciobanu, Barbara Delmonte, Lukas Eling, Aja Ellis, Shruthi Ganesh, Nicholas R. Golledge, Skylar Haines, Michael Handley, Robert L. Hawley, Chad M. Hogan, Katelyn M. Johnson, Elena Korotkikh, Daniel P. Lowry, Darcy Mandeno, Robert M. McKay, James A. Menking, Timothy R. Naish, Caroline Noerling, Agathe Ollive, Anaïs Orsi, Bernadette C. Proemse, Alexander R. Pyne, Rebecca L. Pyne, James Renwick, Reed P. Scherer, Stefanie Semper, Marius Simonsen, Sharon B. Sneed, Eric J. Steig, Andrea Tuohy, Abhijith Ulayottil Venugopal, Fernando Valero-Delgado, Janani Venkatesh, Feitang Wang, Shimeng Wang, Dominic A. Winski, V. Holly L. Winton, Arran Whiteford, Cunde Xiao, Jiao Yang, and Xin Zhang
Clim. Past, 14, 193–214, https://doi.org/10.5194/cp-14-193-2018, https://doi.org/10.5194/cp-14-193-2018, 2018
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Temperature and snow accumulation records from the annually dated Roosevelt Island Climate Evolution (RICE) ice core show that for the past 2 700 years, the eastern Ross Sea warmed, while the western Ross Sea showed no trend and West Antarctica cooled. From the 17th century onwards, this dipole relationship changed. Now all three regions show concurrent warming, with snow accumulation declining in West Antarctica and the eastern Ross Sea.
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.
Kelly M. Brunt, Robert L. Hawley, Eric R. Lutz, Michael Studinger, John G. Sonntag, Michelle A. Hofton, Lauren C. Andrews, and Thomas A. Neumann
The Cryosphere, 11, 681–692, https://doi.org/10.5194/tc-11-681-2017, https://doi.org/10.5194/tc-11-681-2017, 2017
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This manuscript presents an analysis of NASA airborne lidar data based on in situ GPS measurements from the interior of the Greenland Ice Sheet. Results show that for two airborne altimeters, surface elevation biases are less than 0.12 m and measurement precisions are 0.09 m or better. The study concludes that two NASA airborne lidars are sufficiently characterized to form part of a satellite data validation strategy, specifically for ICESat-2, scheduled to launch in 2018.
Thomas B. Overly, Robert L. Hawley, Veit Helm, Elizabeth M. Morris, and Rohan N. Chaudhary
The Cryosphere, 10, 1679–1694, https://doi.org/10.5194/tc-10-1679-2016, https://doi.org/10.5194/tc-10-1679-2016, 2016
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We demonstrate that snow accumulation rates across the Greenland Ice Sheet, determined from RADAR layers and modeled snow density profiles, are identical to ground-based measurements of snow accumulation. Three regional climate models underestimate snow accumulation compared to RADAR layer estimates. Using RADAR increases spatial coverage and improves accuracy of snow accumulation estimates. Incorporating our results into climate models may reduce uncertainty of sea-level rise estimates.
M. P. Lüthi, C. Ryser, L. C. Andrews, G. A. Catania, M. Funk, R. L. Hawley, M. J. Hoffman, and T. A. Neumann
The Cryosphere, 9, 245–253, https://doi.org/10.5194/tc-9-245-2015, https://doi.org/10.5194/tc-9-245-2015, 2015
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We analyze the thermal structure of the Greenland Ice Sheet with a heat flow model. New borehole measurements indicate that more heat is stored within the ice than would be expected from heat diffusion alone. We conclude that temperate paleo-firn and cyro-hydrologic warming are essential processes that explain the measurements.
L. Gray, D. Burgess, L. Copland, R. Cullen, N. Galin, R. Hawley, and V. Helm
The Cryosphere, 7, 1857–1867, https://doi.org/10.5194/tc-7-1857-2013, https://doi.org/10.5194/tc-7-1857-2013, 2013
B. F. Morriss, R. L. Hawley, J. W. Chipman, L. C. Andrews, G. A. Catania, M. J. Hoffman, M. P. Lüthi, and T. A. Neumann
The Cryosphere, 7, 1869–1877, https://doi.org/10.5194/tc-7-1869-2013, https://doi.org/10.5194/tc-7-1869-2013, 2013
Related subject area
Discipline: Ice sheets | Subject: Instrumentation
Brief communication: RADIX (Rapid Access Drilling and Ice eXtraction) dust logger test in the EastGRIP hole
Array processing in cryoseismology: a comparison to network-based approaches at an Antarctic ice stream
Progress of the RADIX (Rapid Access Drilling and Ice eXtraction) fast-access drilling system
High-accuracy UAV photogrammetry of ice sheet dynamics with no ground control
Autonomous ice sheet surface mass balance measurements from cosmic rays
Jakob Schwander, Thomas Franziskus Stocker, Remo Walther, Samuel Marending, Tobias Erhardt, Chantal Zeppenfeld, and Jürg Jost
EGUsphere, https://doi.org/10.5194/egusphere-2024-372, https://doi.org/10.5194/egusphere-2024-372, 2024
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The RADIX optical dust logger is part of the exploratory 20-mm drilling system of the University of Bern. The logger is inserted into the borehole after drilling. The temperature, inclination and compass sensors were successfully tested, but not the dust sensor, because no RADIX hole reached down to the required bubble-free ice. In June 2023, we tested the logger with an adapter for the large East GRIP deep borehole. An excellent dust record was obtained for the Late Glacial/Holocene.
Thomas Samuel Hudson, Alex M. Brisbourne, Sofia-Katerina Kufner, J.-Michael Kendall, and Andy M. Smith
The Cryosphere, 17, 4979–4993, https://doi.org/10.5194/tc-17-4979-2023, https://doi.org/10.5194/tc-17-4979-2023, 2023
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Earthquakes (or icequakes) at glaciers can shed light on fundamental glacier processes. These include glacier slip, crevassing, and imaging ice structure. To date, most studies use networks of seismometers, primarily sensitive to icequakes within the spatial extent of the network. However, arrays of seismometers allow us to detect icequakes at far greater distances. Here, we investigate the potential of such array-processing methods for studying icequakes at glaciers.
Jakob Schwander, Thomas F. Stocker, Remo Walther, and Samuel Marending
The Cryosphere, 17, 1151–1164, https://doi.org/10.5194/tc-17-1151-2023, https://doi.org/10.5194/tc-17-1151-2023, 2023
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RADIX (Rapid Access Drilling and Ice eXtraction) is a fast-access ice-drilling system for prospecting future deep-drilling sites on glaciers and polar ice sheets. It consists of a 40 mm rapid firn drill, a 20 mm deep drill and a logger. The maximum depth range of RADIX is 3100 m by design. The nominal drilling speed is on the order of 40 m h-1. The 15 mm diameter logger provides data on the hole inclination and direction and measures temperature and dust in the ice surrounding the borehole.
Thomas R. Chudley, Poul Christoffersen, Samuel H. Doyle, Antonio Abellan, and Neal Snooke
The Cryosphere, 13, 955–968, https://doi.org/10.5194/tc-13-955-2019, https://doi.org/10.5194/tc-13-955-2019, 2019
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Unmanned Aerial Vehicles (UAVs) are increasingly common tools in the geosciences, but their use requires good ground control in order to make accurate georeferenced models. This is difficult in applications such as glaciology, where access to study sites can be hazardous. We show that a new technique utilising on-board GPS post-processing can match and even improve on ground-control-based methods, and, as a result, can produce accurate glacier velocity fields even on an inland ice sheet.
Ian M. Howat, Santiago de la Peña, Darin Desilets, and Gary Womack
The Cryosphere, 12, 2099–2108, https://doi.org/10.5194/tc-12-2099-2018, https://doi.org/10.5194/tc-12-2099-2018, 2018
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In this paper we present the first application of cosmic ray neutron sensing for continuously measuring in situ accumulation on an ice sheet. We validate these results with manual snow coring and snow stake measurements, showing that the cosmic ray observations are of similar if not better accuracy. We also present our observations of variability in accumulation over 24 months at Summit Camp, Greenland. We conclude that cosmic ray sensing has a high potential for measuring surface mass balance.
Cited articles
Adolph, A. C. and Albert, M. R.: Gas diffusivity and permeability through the firn column at Summit, Greenland: measurements and comparison to microstructural properties, The Cryosphere, 8, 319–328, https://doi.org/10.5194/tc-8-319-2014, 2014. a, b
Alley, R.: Texture of Polar Firn for Remote Sensing, Ann. Glaciol., 9, 1–4, https://doi.org/10.3189/S0260305500200670, 1997. a
Alley, R. B.: Concerning the deposition and diagenesis of strata in polar firn, J. Glaciol., 34, 283–290, https://doi.org/10.3189/S0022143000007024, 1988. a
Alley, R. B., Bolzan, J. F., and Whillans, I. M.: Polar Firn Densification and Grain Growth, Ann. Glaciol., 3, 7–11, https://doi.org/10.3189/S0260305500002433, 1982. a
Avanzi, F., Hirashima, H., Yamaguchi, S., Katsushima, T., and De Michele, C.: Observations of capillary barriers and preferential flow in layered snow during cold laboratory experiments, The Cryosphere, 10, 2013–2026, https://doi.org/10.5194/tc-10-2013-2016, 2016. a
Avanzi, F., Petrucci, G., Matzl, M., Schneebeli, M., and De Michele, C.: Early formation of preferential flow in a homogeneous snowpack observed by micro-CT, Water Resour. Res., 53, 3713–3729, https://doi.org/10.1002/2016WR019502, 2017. a
Banwell, A. F., Wever, N., Dunmire, D., and Picard, G.: Quantifying Antarctic-Wide Ice-Shelf Surface Melt Volume Using Microwave and Firn Model Data: 1980 to 2021, Geophys. Res. Lett., 50, e2023GL102744, https://doi.org/10.1029/2023GL102744, 2023. a
Baunach, T., Fierz, C., Satyawali, P. K., and Schneebeli, M.: A model for kinetic grain growth, Ann. Glaciol., 32, 1–6, https://doi.org/10.3189/172756401781819427, 2001. a
Bohn, N., Painter, T. H., Thompson, D. R., Carmon, N., Susiluoto, J., Turmon, M. J., Helmlinger, M. C., Green, R. O., Cook, J. M., and Guanter, L.: Optimal estimation of snow and ice surface parameters from imaging spectroscopy measurements, Remote Sens. Environ., 265, 112613, https://doi.org/10.1016/j.rse.2021.112613, 2021. a
Bohren, C. F. and Beschta, R. L.: Snowpack albedo and snow density, Cold Reg. Sci. Technol., 1, 47–50, https://doi.org/10.1016/0165-232X(79)90018-1, 1979. a
Brucker, L., Picard, G., and Fily, M.: Snow grain-size profiles deduced from microwave snow emissivities in Antarctica, J. Glaciol., 56, 514–526, https://doi.org/10.3189/002214310792447806, 2010. a
Brun, E.: Investigation on Wet-Snow Metamorphism in Respect of Liquid-Water Content, Ann. Glaciol., 13, 22–26, https://doi.org/10.3189/S0260305500007576, 1989. a, b, c
Charalampidis, C., van As, D., Colgan, W. T., Fausto, R. F., MacFerrin, M., and Machguth, H.: Thermal tracing of retained meltwater in the lower accumulation area of the Southwestern Greenland ice sheet, Ann. Glaciol., 57, 1–10, https://doi.org/10.1017/aog.2016.2, 2016. a, b, c
Cogley, J. G., Hock, R., Rasmussen, L. A., Arendt, A. A., Bauder, A., Jansson, P., Braithwaite, R., Kaser, G., Möller, M., Nicholson, L., and Zemp, M.: Glossary of glacier mass balance and related terms, IHP-VII Technical Documents in Hydrology No. 86, IACS Contribution No. 2, UNESCO-IHP, Paris, https://unesdoc.unesco.org/ark:/48223/pf0000192525 (last access: 15 March 2024), 2011. a, b
Colbeck, S. C.: An overview of seasonal snow metamorphism, Rev. Geophys., 20, 45–61, https://doi.org/10.1029/RG020i001p00045, 1982. a, b
Colosio, P., Tedesco, M., Ranzi, R., and Fettweis, X.: Surface melting over the Greenland ice sheet derived from enhanced resolution passive microwave brightness temperatures (1979–2019), The Cryosphere, 15, 2623–2646, https://doi.org/10.5194/tc-15-2623-2021, 2021. a
Courville, Z. R., Albert, M. R., Fahnestock, M. A., Cathles IV, L. M., and Shuman, C. A.: Impacts of an accumulation hiatus on the physical properties of firn at a low-accumulation polar site, J. Geophys. Res.-Earth, 112, F02030, https://doi.org/10.1029/2005JF000429, 2007. a
Donahue, C., Skiles, S. M., and Hammonds, K.: Mapping liquid water content in snow at the millimeter scale: an intercomparison of mixed-phase optical property models using hyperspectral imaging and in situ measurements, The Cryosphere, 16, 43–59, https://doi.org/10.5194/tc-16-43-2022, 2022. a, b
Dunmire, D., Banwell, A. F., Wever, N., Lenaerts, J. T. M., and Datta, R. T.: Contrasting regional variability of buried meltwater extent over 2 years across the Greenland Ice Sheet, The Cryosphere, 15, 2983–3005, https://doi.org/10.5194/tc-15-2983-2021, 2021. a
Eiriksson, D., Whitson, M., Luce, C. H., Marshall, H.-P., Bradford, J., Benner, S. G., Black, T., Hetrick, H., and McNamara, J. P.: An evaluation of the hydrologic relevance of lateral flow in snow at hillslope and catchment scales, Hydrol. Process., 27, 640–654, https://doi.org/10.1002/hyp.9666, 2013. a
Flanner, M. G., Zender, C. S., Randerson, J. T., and Rasch, P. J.: Present-day climate forcing and response from black carbon in snow, J. Geophys. Res.-Atmos., 112, D11202, https://doi.org/10.1029/2006JD008003, 2007. a
Freitag, J., Wilhelms, F., and Kipfstuhl, S.: Microstructure-dependent densification of polar firn derived from X-ray microtomography, J. Glaciol., 50, 243–250, https://doi.org/10.3189/172756504781830123, 2004. a
Gow, A. J.: On the Rates of Growth of Grains and Crystals in South Polar Firn, J. Glaciol., 8, 241–252, https://doi.org/10.3189/S0022143000031233, 1969. a, b
Graeter, K. A., Osterberg, E. C., Ferris, D. G., Hawley, R. L., Marshall, H. P., Lewis, G., Meehan, T., McCarthy, F., Overly, T., and Birkel, S. D.: Ice Core Records of West Greenland Melt and Climate Forcing, Geophys. Res. Lett., 45, 3164–3172, https://doi.org/10.1002/2017GL076641, 2018. a, b, c, d, e, f
Gregory, S. A., Albert, M. R., and Baker, I.: Impact of physical properties and accumulation rate on pore close-off in layered firn, The Cryosphere, 8, 91–105, https://doi.org/10.5194/tc-8-91-2014, 2014. a, b, c
Grenfell, T. C. and Warren, S. G.: Representation of a nonspherical ice particle by a collection of independent spheres for scattering and absorption of radiation, J. Geophys. Res.-Atmos., 104, 31697–31709, https://doi.org/10.1029/1999JD900496, 1999. a
Groot Zwaaftink, C. D., Cagnati, A., Crepaz, A., Fierz, C., Macelloni, G., Valt, M., and Lehning, M.: Event-driven deposition of snow on the Antarctic Plateau: analyzing field measurements with SNOWPACK, The Cryosphere, 7, 333–347, https://doi.org/10.5194/tc-7-333-2013, 2013. a
Harper, J., Humphrey, N., Pfeffer, W. T., Brown, J., and Fettweis, X.: Greenland ice-sheet contribution to sea-level rise buffered by meltwater storage in firn, Nature, 491, 240–243, https://doi.org/10.1038/nature11566, 2012. a, b
Harper, J., Saito, J., and Humphrey, N.: Cold Season Rain Event Has Impact on Greenland's Firn Layer Comparable to Entire Summer Melt Season, Geophys. Res. Lett., 50, e2023GL103654, https://doi.org/10.1029/2023GL103654, 2023. a
Harper, J. T. and Bradford, J. H.: Snow stratigraphy over a uniform depositional surface: spatial variability and measurement tools, Cold Reg. Sci. Technol., 37, 289–298, https://doi.org/10.1016/S0165-232X(03)00071-5, 2003. a
Hawley, R. L., Courville, Z. R., Kehrl, L. M., Lutz, E. R., Osterberg, E. C., Overly, T. B., and Wong, G. J.: Recent accumulation variability in northwest Greenland from ground-penetrating radar and shallow cores along the Greenland Inland Traverse, J. Glaciol., 60, 375–382, https://doi.org/10.3189/2014JoG13J141, 2014. a
Hirashima, H., Avanzi, F., and Wever, N.: Wet-Snow Metamorphism Drives the Transition From Preferential to Matrix Flow in Snow, Geophys. Res. Lett., 46, 14548–14557, https://doi.org/10.1029/2019GL084152, 2019. a
Hollin, J. T. and Cameron, R. L.: I.G.Y. Glaciological Work at Wilkes Station, Antarctica, J. Glaciol., 3, 833–843, https://doi.org/10.3189/S0022143000027209, 1961. a
Humphrey, N. F., Harper, J. T., and Meierbachtol, T. W.: Physical limits to meltwater penetration in firn, J. Glaciol., 67, 952–960, https://doi.org/10.1017/jog.2021.44, 2021. a, b, c
Katsushima, T., Yamaguchi, S., Kamakura, T., and Sato, A.: Experimental analysis of preferential flow in dry snowpack, Cold Reg. Sci. Technol., 85, 206–216, https://doi.org/10.1016/j.coldregions.2012.09.012, 2013. a
Keegan, K., Albert, M. R., and Baker, I.: The impact of ice layers on gas transport through firn at the North Greenland Eemian Ice Drilling (NEEM) site, Greenland, The Cryosphere, 8, 1801–1806, https://doi.org/10.5194/tc-8-1801-2014, 2014. a
Keenan, E., Wever, N., Dattler, M., Lenaerts, J. T. M., Medley, B., Kuipers Munneke, P., and Reijmer, C.: Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density, The Cryosphere, 15, 1065–1085, https://doi.org/10.5194/tc-15-1065-2021, 2021. a
Kipfstuhl, S., Faria, S. H., Azuma, N., Freitag, J., Hamann, I., Kaufmann, P., Miller, H., Weiler, K., and Wilhelms, F.: Evidence of dynamic recrystallization in polar firn, J. Geophys. Res.-Sol. Ea., 114, B05204, https://doi.org/10.1029/2008JB005583, 2009. a
Langlois, A., Royer, A., Montpetit, B., Picard, G., Brucker, L., Arnaud, L., Harvey-Collard, P., Fily, M., and Goïta, K.: On the relationship between snow grain morphology and in-situ near infrared calibrated reflectance photographs, Cold Reg. Sci. Technol., 61, 34–42, https://doi.org/10.1016/j.coldregions.2010.01.004, 2010. a
Lehning, M., Bartlet, P., Brown, B., Fierz, C., and Satyawali, P.: A physical SNOWPACK model for the Swiss avalanche warning: Part II. Snow microstructure, Cold Reg. Sci. Technol., 35, 147–167, https://doi.org/10.1016/S0165-232X(02)00073-3, 2002. a
Leppänen, L., Kontu, A., Vehviläinen, J., Lemmetyinen, J., and Pulliainen, J.: Comparison of traditional and optical grain-size field measurements with SNOWPACK simulations in a taiga snowpack, J. Glaciol., 61, 151–162, https://doi.org/10.3189/2015JoG14J026, 2015. a, b
Lewis, G.: In-situ snow accumulation, melt, and firn density records using ground penetrating radar and firn cores, western Greenland, 1955–2017, Arctic Data Center [data set], https://doi.org/10.18739/A25M62781, 2021. a, b
Lewis, G., Osterberg, E., Hawley, R., Marshall, H. P., Meehan, T., Graeter, K., McCarthy, F., Overly, T., Thundercloud, Z., and Ferris, D.: Recent precipitation decrease across the western Greenland ice sheet percolation zone, The Cryosphere, 13, 2797–2815, https://doi.org/10.5194/tc-13-2797-2019, 2019. a, b, c, d, e
Ligtenberg, S. R. M., Helsen, M. M., and van den Broeke, M. R.: An improved semi-empirical model for the densification of Antarctic firn, The Cryosphere, 5, 809–819, https://doi.org/10.5194/tc-5-809-2011, 2011. a
Linow, S., Hörhold, M. W., and Freitag, J.: Grain-size evolution of polar firn: a new empirical grain growth parameterization based on X-ray microcomputer tomography measurements, J. Glaciol., 58, 1245–1252, https://doi.org/10.3189/2012JoG11J256, 2012. a, b
MacFerrin, M., Machguth, H., van As, D., Charalampidis, C., Stevens, C. M., Heilig, A., Vandecrux, B., Langen, P. L., Mottram, R., Fettweis, X., van den Broeke, M. R., Pfeffer, W. T., Moussavi, M. S., and Abdalati, W.: Rapid expansion of Greenland’s low-permeability ice slabs, Nature, 573, 403–407, https://doi.org/10.1038/s41586-019-1550-3, 2019. a, b, c, d, e, f
Machguth, H., MacFerrin, M., van As, D., Box, J. E., Charalampidis, C., Colgan, W., Fausto, R. S., Meijer, H. A. J., Mosley-Thompson, E., and van de Wal, R. S. W.: Greenland meltwater storage in firn limited by near-surface ice formation, Nat. Clim. Change, 6, 390–393, https://doi.org/10.1038/nclimate2899, 2016. a
Maeno, N. and Ebinuma, T.: Pressure Sintering of Ice and Its Implication to the Densification of Snow at Polar Glaciers and Ice Sheets, J. Phys. Chem., 87, 4103–4110, https://doi.org/10.1021/j100244a023, 1983. a
Marsh, P. and Woo, M.-K.: Wetting front advance and freezing of meltwater within a snow cover: 1. Observations in the Canadian Arctic, Water Resour. Res., 20, 1853–1864, https://doi.org/10.1029/WR020i012p01853, 1984. a
Mätzler, C.: Autocorrelation functions of granular media with free arrangement of spheres, spherical shells or ellipsoids, J. Appl. Phys., 81, 1509–1517, https://doi.org/10.1063/1.363916, 1997. a
McDowell, I.: Effective grain size and ice layer data from the top 10 meters of the 2016–2017 Greenland Traverse for Accumulation and Climate Studies (GreenTrACS) firn cores, western Greenland Ice Sheet, Arctic Data Center [data set], https://doi.org/10.18739/A2J38KK2T, 2024. a
McDowell, I., Keegan, K., Osterberg, E., Hawley, R., and Marshall, H.-P.: Grain size and ice layer stratigraphy from the upper 10 meters of Cores 1-7 collected during the 2016 Greenland Traverse for Accumulation and Climate Studies (GreenTrACS), western Greenland, Arctic Data Center [data set], https://doi.org/10.18739/A24B2X61Z, 2022. a
McDowell, I. E., Albert, M. R., Lieblappen, S. A., and Keegan, K. M.: Local weather conditions create structural differences between shallow firn columns at Summit, Greenland and WAIS Divide, Antarctica, Atmosphere, 11, 1370, https://doi.org/10.3390/atmos11121370, 2020. a
McDowell, I. E., Keegan, K. M., Wever, N., Osterberg, E. C., Hawley, R. L., and Marshall, H.-P.: Firn core evidence of two-way feedback mechanisms between meltwater infiltration and firn microstructure from the western percolation zone of the Greenland Ice Sheet, J. Geophys. Res.-Earth, 128, e2022JF006752, https://doi.org/10.1029/2022JF006752, 2023. a, b, c, d, e, f, g, h, i, j, k
Meussen, B., Mahrenholtz, O., and Oerter, H.: Creep of polar firn, Cold Reg. Sci. Technol., 29, 177–200, https://doi.org/10.1016/S0165-232X(99)00018-X, 1999. a
Miège, C., Forster, R. R., Box, J. E., Burgess, E. W., McConnell, J. R., Pasteris, D. R., and Spikes, V. B.: Southeast Greenland high accumulation rates derived from firn cores and ground-penetrating radar, Ann. Glaciol., 54, 322–332, https://doi.org/10.3189/2013AoG63A358, 2013. a
Miège, C., Forster, R. R., Brucker, L., Koenig, L. S., Solomon, D. K., Paden, J. D., Box, J. E., Burgess, E. W., Miller, J. Z., McNerney, L., Brautigam, N., Fausto, R. S., and Gogineni, S.: Spatial extent and temporal variability of Greenland firn aquifers detected by ground and airborne radars, J. Geophys. Res.-Earth, 121, 2381–2398, https://doi.org/10.1002/2016JF003869, 2016. a, b
Nghiem, S. V., Hall, D. K., Mote, T. L., Tedesco, M., Albert, M. R., Keegan, K., Shuman, C. A., DiGirolamo, N. E., and Neumann, G.: The extreme melt across the Greenland ice sheet in 2012, Geophys. Res. Lett., 39, L20502, https://doi.org/10.1029/2012GL053611, 2012. a
Nilsson, J., Vallelonga, P., Simonsen, S. B., Sørensen, L. S., Forsberg, R., Dahl-Jensen, D., Hirabayashi, M., Goto-Azuma, K., Hvidberg, C. S., Kjær, H. A., and Satow, K.: Greenland 2012 melt event effects on CryoSat-2 radar altimetry, Geophys. Res. Lett., 42, 3919–3926, https://doi.org/10.1002/2015GL063296, 2015. a
Nolin, A. W. and Dozier, J.: Estimating snow grain size using AVIRIS data, Remote Sens. Environ., 44, 231–238, https://doi.org/10.1016/0034-4257(93)90018-S, 1993. a, b
Nolin, A. W. and Dozier, J.: A hyperspectral method for remotely sensing the grain size of snow, Remote Sens. Environ., 74, 207–216, https://doi.org/10.1016/S0034-4257(00)00111-5, 2000. a, b, c
Noël, B., Lenaerts, J. T. M., Lipscomb, W. H., Thayer-Calder, K., and van den Broeke, M. R.: Peak refreezing in the Greenland firn layer under future warming scenarios, Nat. Commun., 13, 6870, https://doi.org/10.1038/s41467-022-34524-x, 2022. a
Osterberg, E. C., Handley, M. J., Sneed, S. B., Mayewski, P. A., and Kreutz, K. J.: Continuous ice core melter system with discrete sampling for major ion, trace element, and stable isotope analyses, Environ. Sci. Technol., 40, 3355–3361, https://doi.org/10.1021/es052536w, 2006. a
Painter, T. H., Molotch, N. P., Cassidy, M., Flanner, M., and Steffen, K.: Contact spectroscopy for determination of stratigraphy of snow optical grain size, J. Glaciol., 53, 121–127, https://doi.org/10.3189/172756507781833947, 2007. a
Rennermalm, Å. K., Hock, R., Covi, F., Xiao, J., Corti, G., Kingslake, J., Leidman, S. Z., Miège, C., MacFerrin, M., Machguth, H., Osterberg, E., Kameda, T., and McConnell, J. R.: Shallow firn cores 1989–2019 in southwest Greenland's percolation zone reveal decreasing density and ice layer thickness after 2012, J. Glaciol., 68, 431–442, https://doi.org/10.1017/jog.2021.102, 2022. a, b
Rott, H., Sturm, K., and Miller, H.: Active and passive microwave signatures of Antarctic firn by means of field measurements and satellite data, Ann. Glaciol., 17, 337–343, https://doi.org/10.3189/S0260305500013070, 1993. a
Schwander, J. and Stauffer, B.: Age difference between polar ice and the air trapped in its bubbles, Nature, 311, 45–47, https://doi.org/10.1038/311045a0, 1984. a
Simonsen, S. B. and Sørensen, L. S.: Implications of changing scattering properties on Greenland ice sheet volume change from Cryosat-2 altimetry, Remote Sens. Environ., 190, 207–216, https://doi.org/10.1016/j.rse.2016.12.012, 2017. a
Skiles, S. M., Donahue, C. P., Hunsaker, A. G., and Jacobs, J. M.: UAV hyperspectral imaging for multiscale assessment of Landsat 9 snow grain size and albedo, Fronti. Remote Sens., 3, 1038287, https://doi.org/10.3389/frsen.2022.1038287, 2023. a
Sommers, A. N., Rajaram, H., Weber, E. P., MacFerrin, M. J., Colgan, W. T., and Stevens, C. M.: Inferring firn permeability from pneumatic testing: a case study on the Greenland ice sheet, Front. Earth Sci., 5, 20, https://doi.org/10.3389/feart.2017.00020, 2017. a
Spaulding, N. E., Meese, D. A., Baker, I., Mayewski, P. A., and Hamilton, G. S.: A new technique for firn grain-size measurement using SEM image analysis, J. Glaciol., 56, 12–19, https://doi.org/10.3189/002214310791190893, 2010. a
Steger, C. R., Reijmer, C. H., van den Broeke, M. R., Wever, N., Forster, R., Koenig, L., Kuipers Munneke, P., Lehning, M., Lhermitte, S., Ligtenberg, S. R. M., Miège, C., and Noël, B. P. Y.: Firn Meltwater Retention on the Greenland Ice Sheet: A Model Comparison, Front. Earth Sci., 5, 3, https://doi.org/10.3389/feart.2017.00003, 2017. a
Stoll, N., Eichler, J., Hörhold, M., Erhardt, T., Jensen, C., and Weikusat, I.: Microstructure, micro-inclusions, and mineralogy along the EGRIP ice core – Part 1: Localisation of inclusions and deformation patterns, The Cryosphere, 15, 5717–5737, https://doi.org/10.5194/tc-15-5717-2021, 2021. a
Taillandier, A.-S., Domine, F., Simpson, W. R., Sturm, M., and Douglas, T. A.: Rate of decrease of the specific surface area of dry snow: Isothermal and temperature gradient conditions, J. Geophys. Res.-Earth, 112, F03003, https://doi.org/10.1029/2006JF000514, 2007. a
Tedesco, M., Fettweis, X., van den Broeke, M. R., van de Wal, R. S. W., Smeets, C. J. P. P., van de Berg, W. J., Serreze, M. C., and Box, J. E.: The role of albedo and accumulation in the 2010 melting record in Greenland, Environ. Res. Lett., 6, 014005, https://doi.org/10.1088/1748-9326/6/1/014005, 2011. a
The Firn Symposium Team: Firn on ice sheets, Nat. Rev. Earth Environ., 5, 79–99, https://doi.org/10.1038/s43017-023-00507-9, 2024. a
Vandecrux, B., MacFerrin, M., Machguth, H., Colgan, W. T., van As, D., Heilig, A., Stevens, C. M., Charalampidis, C., Fausto, R. S., Morris, E. M., Mosley-Thompson, E., Koenig, L., Montgomery, L. N., Miège, C., Simonsen, S. B., Ingeman-Nielsen, T., and Box, J. E.: Firn data compilation reveals widespread decrease of firn air content in western Greenland, The Cryosphere, 13, 845–859, https://doi.org/10.5194/tc-13-845-2019, 2019. a
van den Broeke, M. R., Enderlin, E. M., Howat, I. M., Kuipers Munneke, P., Noël, B. P. Y., van de Berg, W. J., van Meijgaard, E., and Wouters, B.: On the recent contribution of the Greenland ice sheet to sea level change, The Cryosphere, 10, 1933–1946, https://doi.org/10.5194/tc-10-1933-2016, 2016. a
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012. a
Westhoff, J., Freitag, J., Orsi, A., Martinerie, P., Weikusat, I., Dyonisius, M., Faïn, X., Fourteau, K., and Blunier, T.: Combining traditional and novel techniques to increase our understanding of the lock-in depth of atmospheric gases in polar ice cores - results from the EastGRIP region, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-1904, 2023. a
Winther, J., Jespersen, M. N., and Liston, G. E.: Blue-ice areas in Antarctica derived from NOAA AVHRR satellite data, J. Glaciol., 47, 325–334, https://doi.org/10.3189/172756501781832386, 2001. a
Wiscombe, W. J. and Warren, S. G.: A Model for the Spectral Albedo of Snow. I: Pure Snow, J. Atmos. Sci., 37, 2712–2733, https://doi.org/10.1175/1520-0469(1980)037<2712:AMFTSA>2.0.CO;2, 1980. a, b
Short summary
Accurate knowledge of firn grain size is crucial for many ice sheet research applications. Unfortunately, collecting detailed measurements of firn grain size is difficult. We demonstrate that scanning firn cores with a near-infrared imager can quickly produce high-resolution maps of both grain size and ice layer distributions. We map grain size and ice layer stratigraphy in 14 firn cores from Greenland and document changes to grain size and ice layer content from the extreme melt summer of 2012.
Accurate knowledge of firn grain size is crucial for many ice sheet research applications....
