Articles | Volume 10, issue 1
https://doi.org/10.5194/tc-10-103-2016
https://doi.org/10.5194/tc-10-103-2016
Research article
 | 
18 Jan 2016
Research article |  | 18 Jan 2016

Feasibility of improving a priori regional climate model estimates of Greenland ice sheet surface mass loss through assimilation of measured ice surface temperatures

M. Navari, S. A. Margulis, S. M. Bateni, M. Tedesco, P. Alexander, and X. Fettweis

Related authors

Modelling snowpack on ice surfaces with the ORCHIDEE land surface model: Application to the Greenland ice sheet
Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, Nina Raoult, and Xavier Fettweis
EGUsphere, https://doi.org/10.5194/egusphere-2024-285,https://doi.org/10.5194/egusphere-2024-285, 2024
Short summary
Coupling MAR (Modèle Atmosphérique Régional) with PISM (Parallel Ice Sheet Model) mitigates the positive melt–elevation feedback
Alison Delhasse, Johanna Beckmann, Christoph Kittel, and Xavier Fettweis
The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024,https://doi.org/10.5194/tc-18-633-2024, 2024
Short summary
Recent warming trends of the Greenland ice sheet documented by historical firn and ice temperature observations and machine learning
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024,https://doi.org/10.5194/tc-18-609-2024, 2024
Short summary
Cloud- and ice-albedo feedbacks drive greater Greenland Ice Sheet sensitivity to warming in CMIP6 than in CMIP5
Idunn Aamnes Mostue, Stefan Hofer, Trude Storelvmo, and Xavier Fettweis
The Cryosphere, 18, 475–488, https://doi.org/10.5194/tc-18-475-2024,https://doi.org/10.5194/tc-18-475-2024, 2024
Short summary
Advancing Arctic sea ice remote sensing with AI and deep learning: now and future
Wenwen Li, Chia-Yu Hsu, and Marco Tedesco
EGUsphere, https://doi.org/10.5194/egusphere-2023-2831,https://doi.org/10.5194/egusphere-2023-2831, 2024
Short summary

Related subject area

Greenland
Modelling present and future rock wall permafrost distribution in the Sisimiut mountain area, West Greenland
Marco Marcer, Pierre-Allain Duvillard, Soňa Tomaškovičová, Steffen Ringsø Nielsen, André Revil, and Thomas Ingeman-Nielsen
The Cryosphere, 18, 1753–1771, https://doi.org/10.5194/tc-18-1753-2024,https://doi.org/10.5194/tc-18-1753-2024, 2024
Short summary
Subglacial valleys preserved in the highlands of south and east Greenland record restricted ice extent during past warmer climates
Guy J. G. Paxman, Stewart S. R. Jamieson, Aisling M. Dolan, and Michael J. Bentley
The Cryosphere, 18, 1467–1493, https://doi.org/10.5194/tc-18-1467-2024,https://doi.org/10.5194/tc-18-1467-2024, 2024
Short summary
Coupling MAR (Modèle Atmosphérique Régional) with PISM (Parallel Ice Sheet Model) mitigates the positive melt–elevation feedback
Alison Delhasse, Johanna Beckmann, Christoph Kittel, and Xavier Fettweis
The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024,https://doi.org/10.5194/tc-18-633-2024, 2024
Short summary
Cloud- and ice-albedo feedbacks drive greater Greenland Ice Sheet sensitivity to warming in CMIP6 than in CMIP5
Idunn Aamnes Mostue, Stefan Hofer, Trude Storelvmo, and Xavier Fettweis
The Cryosphere, 18, 475–488, https://doi.org/10.5194/tc-18-475-2024,https://doi.org/10.5194/tc-18-475-2024, 2024
Short summary
Evaluating different geothermal heat-flow maps as basal boundary conditions during spin-up of the Greenland ice sheet
Tong Zhang, William Colgan, Agnes Wansing, Anja Løkkegaard, Gunter Leguy, William H. Lipscomb, and Cunde Xiao
The Cryosphere, 18, 387–402, https://doi.org/10.5194/tc-18-387-2024,https://doi.org/10.5194/tc-18-387-2024, 2024
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, 1995.
Al-Yaari, A., Wigneron, J.-P., Ducharne, A., Kerr, Y., de Rosnay, P., de Jeu, R., Govind, A., Al Bitar, A., Albergel, C., Muñoz-Sabater, J., Richaume, P., and Mialon, A.: Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to Land Data Assimilation System estimates, Remote Sens. Environ., 149, 181–195, https://doi.org/10.1016/j.rse.2014.04.006, 2014.
Andreadis, K. M. and Lettenmaier, D. P.: Assimilating remotely sensed snow observations into a macroscale hydrology model, Adv. Water Resour., 29, 872–886, https://doi.org/10.1016/j.advwatres.2005.08.004, 2006.
Bamber, J. L. and Layberry, R. L.: 1. Measurement, data reduction, and errors ice sheet was reestimated and found to have a value at a sample, J. Geophys. Res., 106, 33773–33780, 2001.
Bateni, S., Huang, C., and Margulis, S.: Feasibility of Characterizing Snowpack and the Freeze–Thaw State of Underlying Soil Using Multifrequency Active/Passive Microwave Data, IEEE T. Geosci. Remote, 51, 4085–4102, 2013.
Download
Short summary
An ensemble batch smoother was used to assess the feasibility of generating a reanalysis estimate of the Greenland ice sheet (GrIS) surface mass fluxes (SMF) via integrating measured ice surface temperatures with a regional climate model estimate. The results showed that assimilation of IST were able to overcome uncertainties in meteorological forcings that drive the GrIS surface processes. We showed that the proposed methodology is able to generate posterior reanalysis estimates of the SMF.