Articles | Volume 19, issue 10
https://doi.org/10.5194/tc-19-4237-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-19-4237-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Oct 2025
Research article |
| 06 Oct 2025
| 06 Oct 2025
Retrieval and validation of total seasonal liquid water amounts in the percolation zone of the Greenland ice sheet using L-band radiometry
Alamgir Hossan
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
Andreas Colliander
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
Baptiste Vandecrux
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Nicole-Jeanne Schlegel
NOAA/OAR Geophysical Fluid Dynamics Laboratory (GFDL), Princeton, New Jersey, United States
Joel Harper
Department of Geosciences, University of Montana, Missoula, Montana, United States
Shawn Marshall
Environment and Climate Change Canada, Gatineau, Quebec J8Y 3Z4, Canada
Julie Z. Miller
EarthSAR, LLC, Salt Lake City, Utah, United States
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, United States
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Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
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Fernando S. Paolo, Alex S. Gardner, Chad A. Greene, Johan Nilsson, Michael P. Schodlok, Nicole-Jeanne Schlegel, and Helen A. Fricker
The Cryosphere, 17, 3409–3433, https://doi.org/10.5194/tc-17-3409-2023, https://doi.org/10.5194/tc-17-3409-2023, 2023
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Alex S. Gardner, Nicole-Jeanne Schlegel, and Eric Larour
Geosci. Model Dev., 16, 2277–2302, https://doi.org/10.5194/gmd-16-2277-2023, https://doi.org/10.5194/gmd-16-2277-2023, 2023
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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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Joshua K. Cuzzone, Nicolás E. Young, Mathieu Morlighem, Jason P. Briner, and Nicole-Jeanne Schlegel
The Cryosphere, 16, 2355–2372, https://doi.org/10.5194/tc-16-2355-2022, https://doi.org/10.5194/tc-16-2355-2022, 2022
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Blake A. Castleman, Nicole-Jeanne Schlegel, Lambert Caron, Eric Larour, and Ala Khazendar
The Cryosphere, 16, 761–778, https://doi.org/10.5194/tc-16-761-2022, https://doi.org/10.5194/tc-16-761-2022, 2022
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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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Julie Z. Miller, Riley Culberg, David G. Long, Christopher A. Shuman, Dustin M. Schroeder, and Mary J. Brodzik
The Cryosphere, 16, 103–125, https://doi.org/10.5194/tc-16-103-2022, https://doi.org/10.5194/tc-16-103-2022, 2022
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Chang-Hwan Park, Aaron Berg, Michael H. Cosh, Andreas Colliander, Andreas Behrendt, Hida Manns, Jinkyu Hong, Johan Lee, Runze Zhang, and Volker Wulfmeyer
Hydrol. Earth Syst. Sci., 25, 6407–6420, https://doi.org/10.5194/hess-25-6407-2021, https://doi.org/10.5194/hess-25-6407-2021, 2021
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Joel Harper, Toby Meierbachtol, Neil Humphrey, Jun Saito, and Aidan Stansberry
The Cryosphere, 15, 5409–5421, https://doi.org/10.5194/tc-15-5409-2021, https://doi.org/10.5194/tc-15-5409-2021, 2021
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We use surface and borehole measurements to investigate the generation and fate of basal meltwater in the ablation zone of western Greenland. The rate of basal meltwater generation at borehole study sites increases by up to 20 % over the winter period. Accommodation of all basal meltwater by expansion of isolated subglacial cavities is implausible. Other sinks for water do not likely balance basal meltwater generation, implying water evacuation through a connected drainage system in winter.
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.
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.
Naomi E. Ochwat, Shawn J. Marshall, Brian J. Moorman, Alison S. Criscitiello, and Luke Copland
The Cryosphere, 15, 2021–2040, https://doi.org/10.5194/tc-15-2021-2021, https://doi.org/10.5194/tc-15-2021-2021, 2021
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In May 2018 we drilled into Kaskawulsh Glacier to study how it is being affected by climate warming and used models to investigate the evolution of the firn since the 1960s. We found that the accumulation zone has experienced increased melting that has refrozen as ice layers and has formed a perennial firn aquifer. These results better inform climate-induced changes on northern glaciers and variables to take into account when estimating glacier mass change using remote-sensing methods.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
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This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
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
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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.
Nataniel M. Holtzman, Leander D. L. Anderegg, Simon Kraatz, Alex Mavrovic, Oliver Sonnentag, Christoforos Pappas, Michael H. Cosh, Alexandre Langlois, Tarendra Lakhankar, Derek Tesser, Nicholas Steiner, Andreas Colliander, Alexandre Roy, and Alexandra G. Konings
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Microwave radiation coming from Earth's land surface is affected by both soil moisture and the water in plants that cover the soil. We measured such radiation with a sensor elevated above a forest canopy while repeatedly measuring the amount of water stored in trees at the same location. Changes in the microwave signal over time were closely related to tree water storage changes. Satellites with similar sensors could thus be used to monitor how trees in an entire region respond to drought.
Rogier van der Velde, Andreas Colliander, Michiel Pezij, Harm-Jan F. Benninga, Rajat Bindlish, Steven K. Chan, Thomas J. Jackson, Dimmie M. D. Hendriks, Denie C. M. Augustijn, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 473–495, https://doi.org/10.5194/hess-25-473-2021, https://doi.org/10.5194/hess-25-473-2021, 2021
Short summary
Short summary
NASA’s SMAP satellite provides estimates of the amount of water in the soil. With measurements from a network of 20 monitoring stations, the accuracy of these estimates has been studied for a 4-year period. We found an agreement between satellite and in situ estimates in line with the mission requirements once the large mismatches associated with rapidly changing water contents, e.g. soil freezing and rainfall, are excluded.
Seyedmohammad Mousavi, Andreas Colliander, Julie Z. Miller, and John S. Kimball
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-297, https://doi.org/10.5194/tc-2020-297, 2020
Manuscript not accepted for further review
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
Short summary
Short summary
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.
Cited articles
Abdalati, W. and Steffen, K.: Passive microwave-derived snow melt regions on the Greenland Ice Sheet, Geophys. Res. Lett., 22, 787–790, https://doi.org/10.1029/95GL00433, 1995.
Abdalati, W. and Steffen, K.: Snowmelt on the Greenland ice sheet as derived from passive microwave satellite data, J. Climate, 10, 165–175, https://doi.org/10.1175/1520-0442(1997)010<0165:SOTGIS>2.0.CO;2, 1997.
Abdalati, W. and Steffen, K.: Greenland Ice Sheet melt extent: 1979–1999, J. Geophys. Res.-Atmos., 106, 33983–33988, https://doi.org/10.1029/2001JD900181, 2001.
Ashcraft, I. and Long, D.: Comparison of methods for melt detection over greenland using active and passive Microwave measurements, Int. J. Remote Sens., 27, 2469–2488, https://doi.org/10.1080/01431160500534465, 2006.
Brodzik, M. J., Long, D. G., and Hardman, M. A.: SMAP Radiometer Twice-Daily rSIR-Enhanced EASE-Grid 2.0 Brightness Temperatures (NSIDC-0738, Version 2), Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/YAMX52BXFL10, 2021.
Calonne, N., Milliancourt, L., Burr, A., Philip, A., Martin, C. L., Flin, F., and Geindreau, C.: Thermal Conductivity of Snow, Firn, and Porous Ice From 3-D Image-Based Computations, Geophys. Res. Lett., 46, 13079–13089, https://doi.org/10.1029/2019GL085228, 2019.
Chaubell, J., Yueh, S., Peng, J., Dunbar, S., Chan, S., Chen, F., Piepmeier, J., Bindlish, R., Entekhabi, D., and O'Neill, P.: Soil Moisture Active Passive (SMAP) Algorithm Theoretical Basis Document: SMAP L1(B/C) Enhanced Radiometer Brightness Temperature Data Product, 1, 1–32, 2018.
Chaubell, J., Chan, S., Dunbar, R. S., Peng, J., and Yueh, S.: SMAP Enhanced L1C Radiometer Half-Orbit 9 km EASE-Grid Brightness Temperatures, Version 3, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/XB8K63YM4U8O 2020.
Citterio, M. and Ahlstrøm, A. P.: Brief communication “The aerophotogrammetric map of Greenland ice masses”, The Cryosphere, 7, 445–449, https://doi.org/10.5194/tc-7-445-2013, 2013.
Colbeck, S. C.: Theory of Metamorphism of Wet Snow, US Army Corps Eng. Cold Reg. Res. Eng. Lab. Res. Rep., 88, 5475–5482, 1973.
Colbeck, S. C.: The capillary effects on water percolation in homogeneous snow, J. Glaciol., 13, 85–97, https://doi.org/10.3189/s002214300002339x, 1974.
Coléou, C. and Lesaffre, B.: Irreducible water saturation in snow: experimental results in a cold laboratory, Ann. Glaciol., 26, 64–68, https://doi.org/10.3189/1998aog26-1-64-68, 1998.
Colliander, A., Mousavi, M., Marshall, S., Samimi, S., Kimball, J. S., Miller, J. Z., Johnson, J., and Burgin, M.: Ice Sheet Surface and Subsurface Melt Water Discrimination Using Multi-Frequency Microwave Radiometry, Geophys. Res. Lett., 49, e2021GL096599, https://doi.org/10.1029/2021GL096599, 2022a.
Colliander, A., Mousavi, M., Misra, S., Brown, S., Kimball, J. S., Miller, J., Johnson, J., and Burgin, M.: Ice Sheet Melt Water Profile Mapping Using Multi-Frequency Microwave Radiometry, Int. Geosci. Remote Sens. Symp., July 2022, 4178–4181, https://doi.org/10.1109/IGARSS46834.2022.9883717, 2022b.
Colliander, A., Mousavi, M., Kimball, J. S., Miller, J. Z., and Burgin, M.: Spatial and temporal differences in surface and subsurface meltwater distribution over Greenland ice sheet using multi-frequency passive microwave observations, Remote Sens. Environ., 295, 113705, https://doi.org/10.1016/j.rse.2023.113705, 2023.
Colliander, A., Hossan, A., Harper, J., Vandecrux, B., Miller, J., Schlegel, N., Marshall, S., and Donlon, C.: Towards Ice Sheet and Ice Shelf Meltwater Profile Retrieval from Copernicus Imaging Microwave Radiometer (CIMR), EGU General Assembly 2024, Vienna, Austria, 14–19 April 2024, EGU24-12972, https://doi.org/10.5194/egusphere-egu24-12972, 2024.
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.
Cooper, M. G. and Smith, L. C.: Satellite remote sensing of the Greenland Ice Sheet Ablation Zone: A review, Remote Sens., 11, 17–21, https://doi.org/10.3390/rs11202405, 2019.
Covi, F., Hock, R., and Reijmer, C. H.: Challenges in modeling the energy balance and melt in the percolation zone of the Greenland ice sheet, J. Glaciol., 69, 164–178, https://doi.org/10.1017/jog.2022.54, 2023.
Culberg, R., Schroeder, D. M., and Chu, W.: Extreme melt season ice layers reduce firn permeability across Greenland, Nat. Commun., 12, 1–9, https://doi.org/10.1038/s41467-021-22656-5, 2021.
Ebrahimi, S. and Marshall, S. J.: Surface energy balance sensitivity to meteorological variability on Haig Glacier, Canadian Rocky Mountains, The Cryosphere, 10, 2799–2819, https://doi.org/10.5194/tc-10-2799-2016, 2016.
Elachi, C. and Van Zyl, J. J.: Introduction to the Physics and Techniques of Remote Sensing, John Wiley & Sons, 159–189 pp., https://doi.org/10.1002/9781119523048.ch5, 2021.
Entekhabi, D., Njoku, E. G., O'Neill, P. E., Kellogg, K. H., Crow, W. T., Edelstein, W. N., Entin, J. K., Goodman, S. D., Jackson, T. J., Johnson, J., Kimball, J., Piepmeier, J. R., Koster, R. D., Martin, N., McDonald, K. C., Moghaddam, M., Moran, S., Reichle, R., Shi, J. C., Spencer, M. W., Thurman, S. W., Tsang, L., and Van Zyl, J.: The soil moisture active passive (SMAP) mission, Proc. IEEE, 98, 704–716, https://doi.org/10.1109/JPROC.2010.2043918, 2010.
Fausto, R. S., van As, D., Mankoff, K. D., Vandecrux, B., Citterio, M., Ahlstrøm, A. P., Andersen, S. B., Colgan, W., Karlsson, N. B., Kjeldsen, K. K., Korsgaard, N. J., Larsen, S. H., Nielsen, S., Pedersen, A. Ø., Shields, C. L., Solgaard, A. M., and Box, J. E.: Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station data, Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, 2021.
Fettweis, X., van Ypersele, J. P., Gallée, H., Lefebre, F., and Lefebvre, W.: The 1979–2005 Greenland ice sheet melt extent from passive microwave data using an improved version of the melt retrieval XPGR algorithm, Geophys. Res. Lett., 34, L05502, https://doi.org/10.1029/2006GL028787, 2007.
Fettweis, X., Tedesco, M., van den Broeke, M., and Ettema, J.: Melting trends over the Greenland ice sheet (1958–2009) from spaceborne microwave data and regional climate models, The Cryosphere, 5, 359–375, https://doi.org/10.5194/tc-5-359-2011, 2011.
Fettweis, X., Hofer, S., Krebs-Kanzow, U., Amory, C., Aoki, T., Berends, C. J., Born, A., Box, J. E., Delhasse, A., Fujita, K., Gierz, P., Goelzer, H., Hanna, E., Hashimoto, A., Huybrechts, P., Kapsch, M.-L., King, M. D., Kittel, C., Lang, C., Langen, P. L., Lenaerts, J. T. M., Liston, G. E., Lohmann, G., Mernild, S. H., Mikolajewicz, U., Modali, K., Mottram, R. H., Niwano, M., Noël, B., Ryan, J. C., Smith, A., Streffing, J., Tedesco, M., van de Berg, W. J., van den Broeke, M., van de Wal, R. S. W., van Kampenhout, L., Wilton, D., Wouters, B., Ziemen, F., and Zolles, T.: GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet, The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, 2020.
Gardner, A. S., Schlegel, N.-J., and Larour, E.: Glacier Energy and Mass Balance (GEMB): a model of firn processes for cryosphere research, Geosci. Model Dev., 16, 2277–2302, https://doi.org/10.5194/gmd-16-2277-2023, 2023.
Greene, C. A., Gwyther, D. E., and Blankenship, D. D.: Antarctic Mapping Tools for MATLAB, Comput. Geosci., 104, 151–157, https://doi.org/10.1016/j.cageo.2016.08.003, 2017.
Greene, C. A., Gardner, A. S., Wood, M., and Cuzzone, J. K.: Ubiquitous acceleration in Greenland Ice Sheet calving from 1985 to 2022, Nature, 625, 523–528, https://doi.org/10.1038/s41586-023-06863-2, 2024.
Hall, D. K., Nghiem, S. V., Schaaf, C. B., DiGirolamo, N. E., and Neumann, G.: Evaluation of surface and near-surface melt characteristics on the Greenland ice sheet using MODIS and QuikSCAT data, J. Geophys. Res.-Earth Surf., 114, 1–13, https://doi.org/10.1029/2009JF001287, 2009.
Hallikainen, M. T., Ulaby, F. T., and Abdelrazik, M.: Dielectric Properties of Snow in the 3 To 37 Ghz Range, IEEE Trans. Antennas Propag., AP-34, 1329–1340, https://doi.org/10.1109/tap.1986.1143757, 1986.
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.
Heilig, A., Eisen, O., MacFerrin, M., Tedesco, M., and Fettweis, X.: Seasonal monitoring of melt and accumulation within the deep percolation zone of the Greenland Ice Sheet and comparison with simulations of regional climate modeling, The Cryosphere, 12, 1851–1866, https://doi.org/10.5194/tc-12-1851-2018, 2018.
Herron, M. M. and Langway, C. C.: Firn densification: an empirical model, J. Glaciol., 25, 373–385, 1980.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hoffman, M. J., Catania, G. A., Neumann, T. A., Andrews, L. C., and Rumrill, J. A.: Links between acceleration, melting, and supraglacial lake drainage of the western Greenland Ice Sheet, J. Geophys. Res.-Earth Surf., 116, 1–16, https://doi.org/10.1029/2010JF001934, 2011.
Hossan, A.: Retrieval and Validation of Total Seasonal Liquid Water Amounts in the Percolation Zone of Greenland Ice Sheet Using L-band Radiometry (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.13800047, 2024.
Houtz, D., Naderpour, R., Schwank, M., and Steffen, K.: Snow wetness and density retrieved from L-band satellite radiometer observations over a site in the West Greenland ablation zone, Remote Sens. Environ., 235, 111361, https://doi.org/10.1016/j.rse.2019.111361, 2019.
Houtz, D., Mätzler, C., Naderpour, R., Schwank, M., and Steffen, K.: Quantifying Surface Melt and Liquid Water on the Greenland Ice Sheet using L-band Radiometry, Remote Sens. Environ., 256, 112341, https://doi.org/10.1016/j.rse.2021.112341, 2021.
How, P., Lund, M. C., Ahlstrøm, A. P., Andersen, S. B., Box, J. E., Citterio, M., Colgan, W. T., Fausto, R. S., Karlsson, N. B., Jakobsen, J., Jakobsgaard, H. T., Larsen, S. H., Mankoff, K. D., Nielsen, R. B., Rutishauser, A., Shield, C. L., Solgaard, A. M., Stevens, I. T., van As, D., Vandecrux, B., Abermann, J., Bjørk, A. A., Langley, K., Lea, J., and Prinz, R.: PROMICE and GC-Net automated weather station data in Greenland, GEUS Dataverse, V26 [data set], https://doi.org/10.22008/FK2/IW73UU, 2022.
Howat, I. M., Negrete, A., and Smith, B. E.: The Greenland Ice Mapping Project (GIMP) land classification and surface elevation data sets, The Cryosphere, 8, 1509–1518, doi10.5194/tc-8-1509-2014, 2014.
Jay Zwally, H.: Microwave Emissivity and Accumulation Rate of Polar Firn, J. Glaciol., 18, 195–215, https://doi.org/10.3189/s0022143000021304, 1977.
Jezek, K. C., Johnson, J. T., Tan, S., Tsang, L., Andrews, M. J., Brogioni, M., MacElloni, G., Durand, M., Chen, C. C., Belgiovane, D. J., Duan, Y., Yardim, C., Li, H., Bringer, A., Leuski, V., and Aksoy, M.: 500–2000-MHz Brightness Temperature Spectra of the Northwestern Greenland Ice Sheet, IEEE T. Geosci. Remote, 56, 1485–1496, https://doi.org/10.1109/TGRS.2017.2764381, 2018.
Jin, Y.: Radiative transfer theory at satellite-borne SSM/I channels and remote sensing data analysis, Sci. China, Ser. E Technol. Sci., 40, 644–652, https://doi.org/10.1007/bf02916850, 1997.
Jin, Y.-Q.: Electromagnetic Scattering Modelling for Quantitative Remote Sensing, World Scientific, 348 pp., https://doi.org/10.1142/2253, 1994.
Jullien, N., Tedstone, A. J., Machguth, H., Karlsson, N. B., and Helm, V.: Greenland Ice Sheet Ice Slab Expansion and Thickening, Geophys. Res. Lett., 50, 1–9, https://doi.org/10.1029/2022GL100911, 2023.
Khan, S. A., Aschwanden, A., Bjørk, A. A., Wahr, J., Kjeldsen, K. K., and Kjaær, K. H.: Greenland ice sheet mass balance: A review, Reports Prog. Phys., 78, 046801, https://doi.org/10.1088/0034-4885/78/4/046801, 2015.
Khan, S. A., Bamber, J. L., Rignot, E., Helm, V., Aschwanden, A., Holland, D. M., van den Broeke, M., King, M., Noël, B., Truffer, M., Humbert, A., Colgan, W., Vijay, S., and Kuipers Munneke, P.: Greenland Mass Trends From Airborne and Satellite Altimetry During 2011–2020, J. Geophys. Res.-Earth Surf., 127, 1–20, https://doi.org/10.1029/2021JF006505, 2022.
Kilic, L., Prigent, C., Aires, F., Boutin, J., Heygster, G., Tonboe, R. T., Roquet, H., Jimenez, C., and Donlon, C.: Expected Performances of the Copernicus Imaging Microwave Radiometer (CIMR) for an All-Weather and High Spatial Resolution Estimation of Ocean and Sea Ice Parameters, J. Geophys. Res.-Ocean., 123, 7564–7580, https://doi.org/10.1029/2018JC014408, 2018.
Long, D. G., Brodzik, M. J., and Hardman, M. A.: Enhanced-Resolution SMAP Brightness Temperature Image Products, IEEE T. Geosci. Remote, 57, 4151–4163, https://doi.org/10.1109/TGRS.2018.2889427, 2019.
Long, D. G., Brodzik, M. J., and Hardman, M.: Evaluating the effective resolution of enhanced resolution SMAP brightness temperature image products, Front. Remote Sens., 4, 1–10, https://doi.org/10.3389/frsen.2023.1073765, 2023.
MacFerrin, M., Machguth, H., As, D. van, Charalampidis, C., Stevens, C. M., Heilig, A., Vandecrux, B., Langen, P. L., Mottram, R., Fettweis, X., Broeke, M. R. va. den, 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.
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. Chang., 6, 390–393, https://doi.org/10.1038/nclimate2899, 2016.
Mätzler, C.: Thermal microwave radiation: Applications for remote sensing, IEE Electromagnetic Waves Series, Vol. 52, London, UK, 2006.
Marshall, S.: MATLAB code for firn thermodynamic and hydrological modelling, Borealis, V2 [code], https://doi.org/10.5683/SP2/WRWJAZ, 2021.
Medley, B., Neumann, T. A., Zwally, H. J., Smith, B. E., and Stevens, C. M.: Simulations of firn processes over the Greenland and Antarctic ice sheets: 1980–2021, The Cryosphere, 16, 3971–4011, https://doi.org/10.5194/tc-16-3971-2022, 2022.
Meyer, C. R. and Hewitt, I. J.: A continuum model for meltwater flow through compacting snow, The Cryosphere, 11, 2799–2813, https://doi.org/10.5194/tc-11-2799-2017, 2017.
Mikkelsen, A. B., Hubbard, A., MacFerrin, M., Box, J. E., Doyle, S. H., Fitzpatrick, A., Hasholt, B., Bailey, H. L., Lindbäck, K., and Pettersson, R.: Extraordinary runoff from the Greenland ice sheet in 2012 amplified by hypsometry and depleted firn retention, The Cryosphere, 10, 1147–1159, https://doi.org/10.5194/tc-10-1147-2016, 2016.
Miller, J. Z., Long, D. G., Jezek, K. C., Johnson, J. T., Brodzik, M. J., Shuman, C. A., Koenig, L. S., and Scambos, T. A.: Brief communication: Mapping Greenland's perennial firn aquifers using enhanced-resolution L-band brightness temperature image time series, The Cryosphere, 14, 2809–2817, https://doi.org/10.5194/tc-14-2809-2020, 2020a.
Miller, J. Z., Culberg, R., Long, D. G., Shuman, C. A., Schroeder, D. M., and Brodzik, M. J.: An empirical algorithm to map perennial firn aquifers and ice slabs within the Greenland Ice Sheet using satellite L-band microwave radiometry, The Cryosphere, 16, 103–125, https://doi.org/10.5194/tc-16-103-2022, 2022a.
Miller, J. Z., Long, D. G., Shuman, C. A., Culberg, R., Hardman, M., and Brodzik, M. J.: Mapping Firn Saturation Over Greenland Using NASA's Soil Moisture Active Passive Satellite, IEEE J. Sel. Top. Appl. Earth Obs., 15, 3714–3729, https://doi.org/10.1109/JSTARS.2022.3154968, 2022b.
Miller, O., Solomon, D. K., Miège, C., Koenig, L., Forster, R., Schmerr, N., Ligtenberg, S. R. M., Legchenko, A., Voss, C. I., Montgomery, L., and McConnell, J. R.: Hydrology of a Perennial Firn Aquifer in Southeast Greenland: An Overview Driven by Field Data, Water Resour. Res., 56, e2019WR026348, https://doi.org/10.1029/2019WR026348, 2020b.
Montgomery, L. N., Schmerr, N., Burdick, S., Forster, R. R., Koenig, L., Legchenko, A., Ligtenberg, S., Miège, C., Miller, O. L., and Solomon, D. K.: Investigation of firn aquifer structure in southeastern Greenland using active source seismology, Front. Earth Sci., 5, 1–12, https://doi.org/10.3389/feart.2017.00010, 2017.
Mote, T. L.: Greenland surface melt trends 1973–2007: Evidence of a large increase in 2007, Geophys. Res. Lett., 34, 1–5, https://doi.org/10.1029/2007GL031976, 2007.
Mote, T. L. and Anderson, M. R.: Variations in snowpack melt on the Greenland ice sheet based on passive-microwave measurements, J. Glaciol., 41, 51–60, https://doi.org/10.1017/S0022143000017755, 1995.
Mouginot, J., Rignot, E., Bjørk, A. A., van den Broeke, M., Millan, R., Morlighem, M., Noël, B., Scheuchl, B., and Wood, M.: Forty-six years of Greenland Ice Sheet mass balance from 1972 to 2018, P. Natl. Acad. Sci. USA, 116, 9239–9244, https://doi.org/10.1073/pnas.1904242116, 2019.
Mousavi, M., Colliander, A., Miller, J. Z., Entekhabi, D., Johnson, J. T., Shuman, C. A., Kimball, J. S., and Courville, Z. R.: Evaluation of Surface Melt on the Greenland Ice Sheet Using SMAP L-Band Microwave Radiometry, IEEE J. Sel. Top. Appl. Earth Obs., 14, 11439–11449, https://doi.org/10.1109/JSTARS.2021.3124229, 2021.
Mousavi, M., Colliander, A., Miller, J., and Kimball, J. S.: A Novel Approach to Map the Intensity of Surface Melting on the Antarctica Ice Sheet Using SMAP L-Band Microwave Radiometry, IEEE J. Sel. Top. Appl. Earth Obs., 15, 1724–1743, https://doi.org/10.1109/JSTARS.2022.3147430, 2022.
Naderpour, R., Houtz, D., and Schwank, M.: Snow wetness retrieved from close-range L-band radiometry in the western Greenland ablation zone, J. Glaciol., 67, 27–38, https://doi.org/10.1017/jog.2020.79, 2021.
Nghiem, S. V., Steffen, K., Kwok, R., and Tsai, W. Y.: Detection of snowmelt regions on the Greenland ice sheet using diurnal backscatter change, J. Glaciol., 47, 539–547, https://doi.org/10.3189/172756501781831738, 2001.
Noël, B., van de Berg, W. J., Machguth, H., Lhermitte, S., Howat, I., Fettweis, X., and van den Broeke, M. R.: A daily, 1 km resolution data set of downscaled Greenland ice sheet surface mass balance (1958–2015), The Cryosphere, 10, 2361–2377, https://doi.org/10.5194/tc-10-2361-2016, 2016.
Otosaka, I. N., Shepherd, A., Ivins, E. R., Schlegel, N.-J., Amory, C., van den Broeke, M. R., Horwath, M., Joughin, I., King, M. D., Krinner, G., Nowicki, S., Payne, A. J., Rignot, E., Scambos, T., Simon, K. M., Smith, B. E., Sørensen, L. S., Velicogna, I., Whitehouse, P. L., A, G., Agosta, C., Ahlstrøm, A. P., Blazquez, A., Colgan, W., Engdahl, M. E., Fettweis, X., Forsberg, R., Gallée, H., Gardner, A., Gilbert, L., Gourmelen, N., Groh, A., Gunter, B. C., Harig, C., Helm, V., Khan, S. A., Kittel, C., Konrad, H., Langen, P. L., Lecavalier, B. S., Liang, C.-C., Loomis, B. D., McMillan, M., Melini, D., Mernild, S. H., Mottram, R., Mouginot, J., Nilsson, J., Noël, B., Pattle, M. E., Peltier, W. R., Pie, N., Roca, M., Sasgen, I., Save, H. V., Seo, K.-W., Scheuchl, B., Schrama, E. J. O., Schröder, L., Simonsen, S. B., Slater, T., Spada, G., Sutterley, T. C., Vishwakarma, B. D., van Wessem, J. M., Wiese, D., van der Wal, W., and Wouters, B.: Mass balance of the Greenland and Antarctic ice sheets from 1992 to 2020, Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, 2023.
Paolo, F. S., Gardner, A. S., Greene, C. A., Nilsson, J., Schodlok, M. P., Schlegel, N.-J., and Fricker, H. A.: Widespread slowdown in thinning rates of West Antarctic ice shelves, The Cryosphere, 17, 3409–3433, https://doi.org/10.5194/tc-17-3409-2023, 2023.
Picard, G., Brucker, L., Roy, A., Dupont, F., Fily, M., Royer, A., and Harlow, C.: Simulation of the microwave emission of multi-layered snowpacks using the Dense Media Radiative transfer theory: the DMRT-ML model, Geosci. Model Dev., 6, 1061–1078, https://doi.org/10.5194/gmd-6-1061-2013, 2013.
Picard, G., Leduc-Leballeur, M., Banwell, A. F., Brucker, L., and Macelloni, G.: The sensitivity of satellite microwave observations to liquid water in the Antarctic snowpack, The Cryosphere, 16, 5061–5083, https://doi.org/10.5194/tc-16-5061-2022, 2022.
Piepmeier, J. R., Focardi, P., Horgan, K. A., Knuble, J., Ehsan, N., Lucey, J., Brambora, C., Brown, P. R., Hoffman, P. J., French, R. T., Mikhaylov, R. L., Kwack, E. Y., Slimko, E. M., Dawson, D. E., Hudson, D., Peng, J., Mohammed, P. N., De Amici, G., Freedman, A. P., Medeiros, J., Sacks, F., Estep, R., Spencer, M. W., Chen, C. W., Wheeler, K. B., Edelstein, W. N., O'Neill, P. E., and Njoku, E. G.: SMAP L-Band Microwave Radiometer: Instrument Design and First Year on Orbit, IEEE T. Geosci. Remote, 55, 1954–1966, https://doi.org/10.1109/TGRS.2016.2631978, 2017.
Poinar, K. and Andrews, L. C.: Challenges in predicting Greenland supraglacial lake drainages at the regional scale, The Cryosphere, 15, 1455–1483, https://doi.org/10.5194/tc-15-1455-2021, 2021.
Samimi, S., Marshall, S. J., and MacFerrin, M.: Meltwater Penetration Through Temperate Ice Layers in the Percolation Zone at DYE-2, Greenland Ice Sheet, Geophys. Res. Lett., 47, 1–9, https://doi.org/10.1029/2020GL089211, 2020.
Samimi, S., Marshall, S. J., Vandecrux, B., and MacFerrin, M.: Time-Domain Reflectometry Measurements and Modeling of Firn Meltwater Infiltration at DYE-2, Greenland, J. Geophys. Res.-Earth Surf., 126, e2021JF006295, https://doi.org/10.1029/2021JF006295, 2021.
Schoof, C.: Ice-sheet acceleration driven by melt supply variability, Nature, 468, 803–806, https://doi.org/10.1038/nature09618, 2010.
Schwank, M. and Naderpour, R.: Snow density and ground permittivity retrieved from L-band radiometry: Melting effects, Remote Sens., 10, 1–26, https://doi.org/10.3390/rs10020354, 2018.
Schwank, M., Rautiainen, K., Mätzler, C., Stähli, M., Lemmetyinen, J., Pulliainen, J., Vehviläinen, J., Kontu, A., Ikonen, J., Ménard, C. B., Drusch, M., Wiesmann, A., and Wegmüller, U.: Model for microwave emission of a snow-covered ground with focus on L band, Remote Sens. Environ., 154, 180–191, https://doi.org/10.1016/j.rse.2014.08.029, 2014.
Shepherd, A., Ivins, E., Rignot, E., Smith, B., van den Broeke, M., Velicogna, I., Whitehouse, P., Briggs, K., Joughin, I., Krinner, G., Nowicki, S., Payne, T., Scambos, T., Schlegel, N., A, G., Agosta, C., Ahlstrøm, A., Babonis, G., Barletta, V. R., Bjørk, A. A., Blazquez, A., Bonin, J., Colgan, W., Csatho, B., Cullather, R., Engdahl, M. E., Felikson, D., Fettweis, X., Forsberg, R., Hogg, A. E., Gallee, H., Gardner, A., Gilbert, L., Gourmelen, N., Groh, A., Gunter, B., Hanna, E., Harig, C., Helm, V., Horvath, A., Horwath, M., Khan, S., Kjeldsen, K. K., Konrad, H., Langen, P. L., Lecavalier, B., Loomis, B., Luthcke, S., McMillan, M., Melini, D., Mernild, S., Mohajerani, Y., Moore, P., Mottram, R., Mouginot, J., Moyano, G., Muir, A., Nagler, T., Nield, G., Nilsson, J., Noël, B., Otosaka, I., Pattle, M. E., Peltier, W. R., Pie, N., Rietbroek, R., Rott, H., Sandberg Sørensen, L., Sasgen, I., Save, H., Scheuchl, B., Schrama, E., Schröder, L., Seo, K. W., Simonsen, S. B., Slater, T., Spada, G., Sutterley, T., Talpe, M., Tarasov, L., van de Berg, W. J., van der Wal, W., van Wessem, M., Vishwakarma, B. D., Wiese, D., Wilton, D., Wagner, T., Wouters, B., and Wuite, J.: Mass balance of the Greenland Ice Sheet from 1992 to 2018, Nature, 579, 233–239, https://doi.org/10.1038/s41586-019-1855-2, 2020.
Smith, L. C., Yang, K., Pitcher, L. H., Overstreet, B. T., Chu, V. W., Rennermalm, Å. K., Ryan, J. C., Cooper, M. G., Gleason, C. J., Tedesco, M., Jeyaratnam, J., Van As, D., van den Broeke, M. R., Van De Berg, W. J., Noël, B., Langen, P. L., Cullather, R. I., Zhao, B., Willis, M. J., Hubbard, A., Box, J. E., Jenner, B. A., and Behar, A. E.: Direct measurements of meltwater runoff on the Greenland ice sheet surface, P. Natl. Acad. Sci. USA, 114, E10622–E10631, https://doi.org/10.1073/pnas.1707743114, 2017.
Steffen, K. and Box, J. E.: Surface climatology of the Greenland Ice Sheet: Greenland Climate Network 1995–1999, J. Geophys. Res., 106, 33951–33964, https://doi.org/10.1029/2001JD900161, 2001.
Steffen, K., Box, J. E., and Abdalati, W.: Greenland climate network: GC-Net, US Army Cold Reg. Reatt. Eng. (CRREL), CRREL Spec. Rep., 98–103, 1996.
Steger, C. R., Reijmer, C. H., and van den Broeke, M. R.: The modelled liquid water balance of the Greenland Ice Sheet, The Cryosphere, 11, 2507–2526, https://doi.org/10.5194/tc-11-2507-2017, 2017.
Sturm, M., Holmgren, J., König, M., and Morris, K.: The thermal conductivity of seasonal snow, J. Glaciol., 43, 26–41, https://doi.org/10.1017/S0022143000002781, 1997.
Sundal, A. V., Shepherd, A., Nienow, P., Hanna, E., Palmer, S., and Huybrechts, P.: Melt-induced speed-up of Greenland ice sheet offset by efficient subglacial drainage, Nature, 469, 521–524, https://doi.org/10.1038/nature09740, 2011.
Tedesco, M.: Snowmelt detection over the Greenland ice sheet from SSM/I brightness temperature daily variations, Geophys. Res. Lett., 34, 1–6, https://doi.org/10.1029/2006GL028466, 2007.
Tedesco, M.: Assessment and development of snowmelt retrieval algorithms over Antarctica from K-band spaceborne brightness temperature (1979–2008), Remote Sens. Environ., 113, 979–997, https://doi.org/10.1016/j.rse.2009.01.009, 2009.
Tedesco, M., Abdalati, W., and Zwally, H. J.: Persistent surface snowmelt over Antarctica (1987–2006) from 19.35 GHz brightness temperatures, Geophys. Res. Lett., 34, 1–6, https://doi.org/10.1029/2007GL031199, 2007.
Tedstone, A. J. and Machguth, H.: Increasing surface runoff from Greenland's firn areas, Nat. Clim. Chang., 12, 672–676, https://doi.org/10.1038/s41558-022-01371-z, 2022.
Thompson-Munson, M., Wever, N., Stevens, C. M., Lenaerts, J. T. M., and Medley, B.: An evaluation of a physics-based firn model and a semi-empirical firn model across the Greenland Ice Sheet (1980–2020), The Cryosphere, 17, 2185–2209, https://doi.org/10.5194/tc-17-2185-2023, 2023.
Tsang, L., Chen, C.-T., Chang, A. T. C., Guo, J., and Ding, K.-H.: Dense media radiative transfer theory based on quasicrystalline approximation with applications to passive microwave remote sensing of snow, Radio Sci., 35, 731–749, https://doi.org/10.1029/1999RS002270, 2000.
Ulaby, F. and Long, D.: Microwave Radar and Radiometric Remote Sensing, Microw. Radar Radiom. Remote Sens., https://doi.org/10.3998/0472119356, 2014.
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.
Vandecrux, B., Mottram, R., Langen, P. L., Fausto, R. S., Olesen, M., Stevens, C. M., Verjans, V., Leeson, A., Ligtenberg, S., Kuipers Munneke, P., Marchenko, S., van Pelt, W., Meyer, C. R., Simonsen, S. B., Heilig, A., Samimi, S., Marshall, S., Machguth, H., MacFerrin, M., Niwano, M., Miller, O., Voss, C. I., and Box, J. E.: The firn meltwater Retention Model Intercomparison Project (RetMIP): evaluation of nine firn models at four weather station sites on the Greenland ice sheet, The Cryosphere, 14, 3785–3810, https://doi.org/10.5194/tc-14-3785-2020, 2020.
Vandecrux, B., Box, J. E., Wehrlé, A., Kokhanovsky, A. A., Picard, G., Niwano, M., Hörhold, M., Faber, A. K., and Steen-Larsen, H. C.: The Determination of the Snow Optical Grain Diameter and Snowmelt Area on the Greenland Ice Sheet Using Spaceborne Optical Observations, Remote Sens., 14, 932, https://doi.org/10.3390/rs14040932, 2022.
Vandecrux, B., Amory, C., Ahlstrøm, A. P., Akers, P. D., Albert, M., Alley, B., Arnaud, L., Bales, R., Benson, C., Box, J. E., Buizert, C., Charalampidis, C., Clerx, N., Covi, F., Denis, G., Dibb, J. E., Ding, M., Eisen, O., Fausto, R., Fernandoy, F., Freitag, J., Niwano, M., Osterberg, E., Otosaka, I., Picard, G., and Rennermalm, A.: The SUMup collaborative database: Surface mass balance , subsurface temperature and density measurements from the Greenland and Antarctic ice sheets, Arctic Data Center [data set], https://doi.org/10.18739/A2M61BR5M, 2023.
Vandecrux, B., Fausto, R. S., Box, J. E., Covi, F., Hock, R., Rennermalm, Å. K., Heilig, A., Abermann, J., van As, D., Bjerre, E., Fettweis, X., Smeets, P. C. J. P., Kuipers Munneke, P., van den Broeke, M. R., Brils, M., Langen, P. L., Mottram, R., and Ahlstrøm, A. P.: Recent warming trends of the Greenland ice sheet documented by historical firn and ice temperature observations and machine learning, The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, 2024a.
Vandecrux, B., Amory, C., Ahlstrøm, A. P., Akers, P. D., Albert, M., Alley, R. B., Alves de Castro, M., Arnaud, L., Baker, I., Bales, R., Benson, C., Box, J. E., Brucker, L., Buizert, C., Chandler, D., Charalampidis, C., Cherblanc, C., Clerx, N., Colgan, W., Covi, F., Dattler, M., Denis, G., Derksen, C., Dibb, J. E., Ding, M., Dixon, D., Eisen, O., Fahrner, D., Fausto, R., Favier, V., Fernandoy, F., Freitag, J., Gerland, S., Harper, J., Hawley, R. L., Heuer, J., Hock, R., Hou, S., How, P., Humphrey, N., Hubbard, B., Iizuka, Y., Isaksson, E., Kameda, T., Karlsson, N. B., Kawakami, K., Kjær, H. A., Kreutz, K., Kuipers Munneke, P., Lazzara, M., Lemeur, E., Lenaerts, J. T. M., Lewis, G., Ley Lindau, F. G., Lindsey-Clark, J., MacFerrin, M., Machguth, H., Magand, O., Mankoff, K. D., Marquetto, L., Martinerie, P., McConnell, J. R., Medley, B., Miège, C., Miles, K. E., Miller, O., Miller, H., Montgomery, L., Morris, E., Mosley-Thompson, E., Mulvaney, R., Niwano, M., Oerter, H., Osterberg, E., Otosaka, I., Picard, G., Polashenski, C., Reijmer, C., Rennermalm, A., Rutishauser, A.,Scanlan, K., Simoes, J. C., Simonsen, S. B., Smeets, P. C. J. P., Smith, A., Solgaard, A., Spencer, M., Steen-Larsen, H. C., Stevens, C. M., Sugiyama, S., Svensson, J., Tedesco, M., Thomas, E., Thompson-Munson, M., Tsutaki, S., van As, D., van den Broeke, M. R., van Tiggelen, M., Wang, Y., Wilhelms, F., Winstrup, M., Xiao, J., and Xiao, C.: The SUMup collaborative database: Surface mass balance, subsurface temperature and density measurements from the Greenland and Antarctic ice sheets (2024 release), version: urn:uuid:35eb18e0-8107-4458-bc62-3cb194bb395f, Arctic Data Center [data set], https://doi.org/10.18739/A2M61BR5M, 2024b.
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.
Verjans, V., Leeson, A. A., Stevens, C. M., MacFerrin, M., Noël, B., and van den Broeke, M. R.: Development of physically based liquid water schemes for Greenland firn-densification models, The Cryosphere, 13, 1819–1842, https://doi.org/10.5194/tc-13-1819-2019, 2019.
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.
Wismann, V.: Monitoring of seasonal snowmelt on Greenland with ERS scatterometer data, IEEE Trans. Geosci. Remote, 38, 1821–1826, https://doi.org/10.1109/36.851766, 2000.
Zeiger, P., Picard, G., Richaume, P., and Mialon, A.: Remote Sensing of Environment Resolution enhancement of SMOS brightness temperatures: Application to melt detection on the Antarctic and Greenland ice sheets, Remote Sens. Environ., 315, 114469, https://doi.org/10.1016/j.rse.2024.114469, 2024.
Zwally, H. J. and Fiegles, S.: Extent and duration of Antarctic surface melting, J. Glaciol., 40, 463–476, https://doi.org/10.3189/s0022143000012338, 1994.
Zwally, H. J., Abdalati, W., Herring, T., Larson, K., Saba, J., and Steffen, K.: Surface Melt – Induced Acceleration of Greenland Ice-Sheet Flow, Science, 297, 218–222, https://doi.org/10.1126/science.1072708, 2002.
Short summary
We used L-band observations from the Soil Moisture Active Passive (SMAP) mission to quantify the surface and subsurface liquid water amounts (LWAs) 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 the Greenland ice sheet (GrIS), which will advance our understanding of ice sheet physical processes for better projection of Greenland’s contribution to global sea level rise.
We used L-band observations from the Soil Moisture Active Passive (SMAP) mission to quantify the...
