Articles | Volume 17, issue 18
https://doi.org/10.5194/gmd-17-6987-2024
https://doi.org/10.5194/gmd-17-6987-2024
Model description paper
 | 
19 Sep 2024
Model description paper |  | 19 Sep 2024

Design and performance of ELSA v2.0: an isochronal model for ice-sheet layer tracing

Therese Rieckh, Andreas Born, Alexander Robinson, Robert Law, and Gerrit Gülle

Related authors

Review Article: Antarctica’s internal architecture: Towards a radiostratigraphically-informed age–depth model of the Antarctic ice sheets
Robert G. Bingham, Julien A. Bodart, Marie G. P. Cavitte, Ailsa Chung, Rebecca J. Sanderson, Johannes C. R. Sutter, Olaf Eisen, Nanna B. Karlsson, Joseph A. MacGregor, Neil Ross, Duncan A. Young, David W. Ashmore, Andreas Born, Winnie Chu, Xiangbin Cui, Reinhard Drews, Steven Franke, Vikram Goel, John W. Goodge, A. Clara J. Henry, Antoine Hermant, Benjamin H. Hills, Nicholas Holschuh, Michelle R. Koutnik, Gwendolyn J.-M. C. Leysinger Vieli, Emma J. Mackie, Elisa Mantelli, Carlos Martín, Felix S. L. Ng, Falk M. Oraschewski, Felipe Napoleoni, Frédéric Parrenin, Sergey V. Popov, Therese Rieckh, Rebecca Schlegel, Dustin M. Schroeder, Martin J. Siegert, Xueyuan Tang, Thomas O. Teisberg, Kate Winter, Shuai Yan, Harry Davis, Christine F. Dow, Tyler J. Fudge, Tom A. Jordan, Bernd Kulessa, Kenichi Matsuoka, Clara J. Nyqvist, Maryam Rahnemoonfar, Matthew R. Siegfried, Shivangini Singh, Verjan Višnjević, Rodrigo Zamora, and Alexandra Zuhr
EGUsphere, https://doi.org/10.5194/egusphere-2024-2593,https://doi.org/10.5194/egusphere-2024-2593, 2024
Short summary
Evaluating two methods of estimating error variances using simulated data sets with known errors
Therese Rieckh and Richard Anthes
Atmos. Meas. Tech., 11, 4309–4325, https://doi.org/10.5194/amt-11-4309-2018,https://doi.org/10.5194/amt-11-4309-2018, 2018
Short summary
Estimating observation and model error variances using multiple data sets
Richard Anthes and Therese Rieckh
Atmos. Meas. Tech., 11, 4239–4260, https://doi.org/10.5194/amt-11-4239-2018,https://doi.org/10.5194/amt-11-4239-2018, 2018
Short summary
Evaluating tropospheric humidity from GPS radio occultation, radiosonde, and AIRS from high-resolution time series
Therese Rieckh, Richard Anthes, William Randel, Shu-Peng Ho, and Ulrich Foelsche
Atmos. Meas. Tech., 11, 3091–3109, https://doi.org/10.5194/amt-11-3091-2018,https://doi.org/10.5194/amt-11-3091-2018, 2018
Short summary
Reducing representativeness and sampling errors in radio occultation–radiosonde comparisons
Shay Gilpin, Therese Rieckh, and Richard Anthes
Atmos. Meas. Tech., 11, 2567–2582, https://doi.org/10.5194/amt-11-2567-2018,https://doi.org/10.5194/amt-11-2567-2018, 2018
Short summary

Related subject area

Cryosphere
CMIP6 models overestimate sea ice melt, growth and conduction relative to ice mass balance buoy estimates
Alex E. West and Edward W. Blockley
Geosci. Model Dev., 18, 3041–3064, https://doi.org/10.5194/gmd-18-3041-2025,https://doi.org/10.5194/gmd-18-3041-2025, 2025
Short summary
Coupling framework (1.0) for the Úa (2023b) ice sheet model and the FESOM-1.4 z-coordinate ocean model in an Antarctic domain
Ole Richter, Ralph Timmermann, G. Hilmar Gudmundsson, and Jan De Rydt
Geosci. Model Dev., 18, 2945–2960, https://doi.org/10.5194/gmd-18-2945-2025,https://doi.org/10.5194/gmd-18-2945-2025, 2025
Short summary
A gradient-boosted tree framework to model the ice thickness of the world's glaciers (IceBoost v1.1)
Niccolò Maffezzoli, Eric Rignot, Carlo Barbante, Troels Petersen, and Sebastiano Vascon
Geosci. Model Dev., 18, 2545–2568, https://doi.org/10.5194/gmd-18-2545-2025,https://doi.org/10.5194/gmd-18-2545-2025, 2025
Short summary
Towards deep-learning solutions for classification of automated snow height measurements (CleanSnow v1.0.2)
Jan Svoboda, Marc Ruesch, David Liechti, Corinne Jones, Michele Volpi, Michael Zehnder, and Jürg Schweizer
Geosci. Model Dev., 18, 1829–1849, https://doi.org/10.5194/gmd-18-1829-2025,https://doi.org/10.5194/gmd-18-1829-2025, 2025
Short summary
Quantitative sub-ice and marine tracing of Antarctic sediment provenance (TASP v1.0)
James W. Marschalek, Edward Gasson, Tina van de Flierdt, Claus-Dieter Hillenbrand, Martin J. Siegert, and Liam Holder
Geosci. Model Dev., 18, 1673–1708, https://doi.org/10.5194/gmd-18-1673-2025,https://doi.org/10.5194/gmd-18-1673-2025, 2025
Short summary

Cited articles

AntArchitecture: Archiving and interrogating Antarctica's internal structure from radar sounding, in: Workshop to establish scientific goals, working practices, and funding routes, Tech. rep., School of GeoSciences, 2017. a
Born, A.: Tracer transport in an isochronal ice sheet model, J. Glaciol., 63, 22–38, https://doi.org/10.1017/jog.2016.111, 2017. a, b, c, d
Born, A. and Robinson, A.: Modeling the Greenland englacial stratigraphy, The Cryosphere, 15, 4539–4556, https://doi.org/10.5194/tc-15-4539-2021, 2021. a, b, c
Brondex, J., Gillet-Chaulet, F., and Gagliardini, O.: Sensitivity of centennial mass loss projections of the Amundsen basin to the friction law, The Cryosphere, 13, 177–195, https://doi.org/10.5194/tc-13-177-2019, 2019. a
Cavitte, M. G. P., Young, D. A., Mulvaney, R., Ritz, C., Greenbaum, J. S., Ng, G., Kempf, S. D., Quartini, E., Muldoon, G. R., Paden, J., Frezzotti, M., Roberts, J. L., Tozer, C. R., Schroeder, D. M., and Blankenship, D. D.: A detailed radiostratigraphic data set for the central East Antarctic Plateau spanning from the Holocene to the mid-Pleistocene, Earth Syst. Sci. Data, 13, 4759–4777, https://doi.org/10.5194/essd-13-4759-2021, 2021. a
Download
Short summary
We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. It creates layers of snow accumulation at fixed times during the simulation, which are used to model the internal stratification of the ice sheet. Together with reconstructed isochrones from radiostratigraphy data, ELSA can be used to assess ice sheet models and to improve their parameterization. ELSA can be used coupled to an ice sheet model or forced with its output.
Share