13 citations as recorded by crossref.

1. Estimation of the state and parameters in ice sheet model using an ensemble Kalman filter and Observing System Simulation Experiments Y. Choi et al. https://doi.org/10.5194/tc-19-5423-2025
2. Brief communication: Inferring Glacier Equilibrium Line Altitudes in the Europe Alps with FROST O. Herrmann et al. https://doi.org/10.5194/tc-20-3817-2026
3. Data assimilation for moving mesh methods with an application to ice sheet modelling B. Bonan et al. https://doi.org/10.5194/npg-24-515-2017
4. A data assimilation framework that uses the Kullback-Leibler divergence S. Pimentel et al. https://doi.org/10.1371/journal.pone.0256584
5. State-parameter estimation approach for data-driven wildland fire spread modeling: Application to the 2012 RxCADRE S5 field-scale experiment C. Zhang et al. https://doi.org/10.1016/j.firesaf.2019.03.009
6. The Potential of the Ensemble Kalman Filter to Improve Glacier Modeling L. Knudsen et al. https://doi.org/10.1007/s44007-024-00116-y
7. Comparison of adjoint and nudging methods to initialise ice sheet model basal conditions C. Mosbeux et al. https://doi.org/10.5194/gmd-9-2549-2016
8. HYPERDIFFERENTIAL SENSITIVITY ANALYSIS IN THE CONTEXT OF BAYESIAN INFERENCE APPLIED TO ICE-SHEET PROBLEMS W. Reese et al. https://doi.org/10.1615/Int.J.UncertaintyQuantification.2023047605
9. Flow speed within the Antarctic ice sheet and its controls inferred from satellite observations R. Arthern et al. https://doi.org/10.1002/2014JF003239
10. Robust reconstruction of glacier beds using transient 2D assimilation with Stokes S. Cook et al. https://doi.org/10.1017/jog.2023.26
11. Assimilation of surface observations in a transient marine ice sheet model using an ensemble Kalman filter F. Gillet-Chaulet https://doi.org/10.5194/tc-14-811-2020
12. Simulating surface height and terminus position for marine outlet glaciers using a level set method with data assimilation M. Hossain et al. https://doi.org/10.1016/j.jcp.2022.111766
13. Assimilating near-real-time mass balance stake readings into a model ensemble using a particle filter J. Landmann et al. https://doi.org/10.5194/tc-15-5017-2021