Articles | Volume 19, issue 8
https://doi.org/10.5194/tc-19-2963-2025
https://doi.org/10.5194/tc-19-2963-2025
Research article
 | 
12 Aug 2025
Research article |  | 12 Aug 2025

Bias in modeled Greenland Ice Sheet melt revealed by ASCAT

Anna Puggaard, Nicolaj Hansen, Ruth Mottram, Thomas Nagler, Stefan Scheiblauer, Sebastian B. Simonsen, Louise S. Sørensen, Jan Wuite, and Anne M. Solgaard

Related authors

Evaluating surface mass balance variability from climate models using GPS Bedrock Vertical Time Series data
Jenan Rajavarathan, Matt King, Christopher Watson, and Nicolaj Hansen
The Cryosphere, 20, 5099–5113, https://doi.org/10.5194/tc-20-5099-2026,https://doi.org/10.5194/tc-20-5099-2026, 2026
Short summary
Mélange, landfast sea ice, ice velocities: What controls seasonal calving rates in North West Greenland?
Sofie Hedetoft, Olivia Bang Brinck, Ruth Mottram, Andrea M. U. Gierisch, Steffen Malskær Olsen, Martin Olesen, Nicolaj Hansen, Anders Anker Bjørk, Erik Loebel, Anne Solgaard, and Peter Thejll
The Cryosphere, 20, 5071–5098, https://doi.org/10.5194/tc-20-5071-2026,https://doi.org/10.5194/tc-20-5071-2026, 2026
Short summary
SnowGalileo: A Pre-trained Earth Observation Transformer for Daily, 100 m Fractional Snow Cover Mapping
Marlena Reil, Julia Kaltenborn, Donovan J. M. Allum, Francis Pelletier, Sebastian Roessler, Samip Shrestha, Zhibang Lv, John Truckenbrodt, Gabriele Schwaizer, Thomas Nagler, John W. Pomeroy, Christopher B. Marsh, Benoit Montpetit, Tobias Jonas, Gabriel Tseng, David Rolnick, Andreas J. Dietz, and Celia A. Baumhoer
EGUsphere, https://doi.org/10.5194/egusphere-2026-3833,https://doi.org/10.5194/egusphere-2026-3833, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
A State-Space Model for Monitoring Greenland Ice Sheet Surface Elevation Change from CryoSat-2
Natalia H. Andersen, Sebastian B. Simonsen, Karina Nielsen, Mai Winstrup, Baptiste Vandecrux, Hui Gao, Beata Csatho, Anton Schenk, and Louise Sandberg Sørensen
The Cryosphere, 20, 4327–4344, https://doi.org/10.5194/tc-20-4327-2026,https://doi.org/10.5194/tc-20-4327-2026, 2026
Short summary
Assessing the effect of land cover on ISBA snow water equivalent and land surface temperature simulations over Europe
Oscar Rojas-Munoz, Constantin Ardilouze, Bertrand Bonan, Diane Tzanos, Darren Ghent, Céline Lamarche, Thomas Nagler, and Jean-Christophe Calvet
The Cryosphere, 20, 4099–4115, https://doi.org/10.5194/tc-20-4099-2026,https://doi.org/10.5194/tc-20-4099-2026, 2026
Short summary

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. a
Antwerpen, R. M., Tedesco, M., Fettweis, X., Alexander, P., and van de Berg, W. J.: Assessing bare-ice albedo simulated by MAR over the Greenland ice sheet (2000–2021) and implications for meltwater production estimates, The Cryosphere, 16, 4185–4199, https://doi.org/10.5194/tc-16-4185-2022, 2022. a
Ashcraft, I. S. and Long, D. G.: 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. a, b, c
Box, J. E., Fettweis, X., Stroeve, J. C., Tedesco, M., Hall, D. K., and Steffen, K.: Greenland ice sheet albedo feedback: thermodynamics and atmospheric drivers, The Cryosphere, 6, 821–839, https://doi.org/10.5194/tc-6-821-2012, 2012. a, b, c
Brangers, I., Lievens, H., Miège, C., Demuzere, M., Brucker, L., and De Lannoy, G. J. M.: Sentinel 1 detects firn aquifers in the Greenland Ice Sheet, Geophys. Res. Lett., 47, e2019GL085192, https://doi.org/10.1029/2019GL085192, 2020. a
Download
Short summary
Regional climate models are currently the only source for assessing the melt volume of the Greenland Ice Sheet on a global scale. This study compares the modeled melt volume with observations from weather stations and melt extent observed from the Advanced SCATterometer (ASCAT) to assess the performance of the models. It highlights the importance of critically evaluating model outputs with high-quality satellite measurements to improve the understanding of variability among models.
Share