Estimation of the state and parameters in ice sheet model using an ensemble Kalman filter and Observing System Simulation Experiments

Choi, Youngmin; Petty, Alek; Felikson, Denis; Poterjoy, Jonathan

doi:https://doi.org/10.5194/tc-19-5423-2025

Articles | Volume 19, issue 11

https://doi.org/10.5194/tc-19-5423-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-19-5423-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 11

Research article

|

06 Nov 2025

Research article |

| 06 Nov 2025

Estimation of the state and parameters in ice sheet model using an ensemble Kalman filter and Observing System Simulation Experiments

Youngmin Choi, Alek Petty, Denis Felikson, and Jonathan Poterjoy

Data sets

Data for "Estimation of the state and parameters in ice sheet model using an ensemble Kalman filter and Observing System Simulation Experiments" Youngmin Choi et al. https://doi.org/10.5281/zenodo.14722078

Model code and software

The Data Assimilation Research Testbed (Version 11.8.0) DART https://doi.org/10.5065/D6WQ0202

Ice-sheet and Sea-level System Model source code ISSM Team https://github.com/ISSMteam/ISSM

Short summary

We combined numerical models with satellite observations using the ensemble Kalman filter to improve predictions of glacier states and their basal conditions. Our simulations show that incorporating more data generally improves prediction accuracy. We also tested different types of data and found that the high-resolution observations provide the greatest improvements. This method can help guide the design of future observing systems and improve long-term projections of ice sheet change.