42 citations as recorded by crossref.

1. Multiple-scale error growth in a convection-resolving model F. Uboldi & A. Trevisan 10.5194/npg-22-1-2015
2. Data assimilation in the geosciences: An overview of methods, issues, and perspectives A. Carrassi et al. 10.1002/wcc.535
3. Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error C. Grudzien et al. 10.5194/npg-25-633-2018
4. Structural origins and real-time predictors of intermittency A. Barone et al. 10.1063/5.0287572
5. Four-dimensional ensemble variational data assimilation and the unstable subspace M. Bocquet & A. Carrassi 10.1080/16000870.2017.1304504
6. Rank Deficiency of Kalman Error Covariance Matrices in Linear Time-Varying System With Deterministic Evolution K. Gurumoorthy et al. 10.1137/15M1025839
7. Mathematical foundations of hybrid data assimilation from a synchronization perspective S. Penny 10.1063/1.5001819
8. Model and data reduction for data assimilation: Particle filters employing projected forecasts and data with application to a shallow water model A. Albarakati et al. 10.1016/j.camwa.2021.05.026
9. Strongly Coupled Data Assimilation in Multiscale Media: Experiments Using a Quasi‐Geostrophic Coupled Model S. Penny et al. 10.1029/2019MS001652
10. Asymptotic properties of linear filter for deterministic processes A. Reddy et al. 10.1016/j.sysconle.2020.104676
11. Correlation-Cutoff Method for Covariance Localization in Strongly Coupled Data Assimilation T. Yoshida & E. Kalnay 10.1175/MWR-D-17-0365.1
12. Impacts of the Lagrangian Data Assimilation of Surface Drifters on Estimating Ocean Circulation during the Gulf of Mexico Grand Lagrangian Deployment L. Sun et al. 10.1175/MWR-D-21-0123.1
13. The onset of chaos in nonautonomous dissipative dynamical systems: a low-order ocean-model case study S. Pierini et al. 10.5194/npg-25-671-2018
14. Asymptotic Forecast Uncertainty and the Unstable Subspace in the Presence of Additive Model Error C. Grudzien et al. 10.1137/17M114073X
15. Application of a local attractor dimension to reduced space strongly coupled data assimilation for chaotic multiscale systems C. Quinn et al. 10.5194/npg-27-51-2020
16. New Trends in Ensemble Forecast Strategy: Uncertainty Quantification for Coarse-Grid Computational Fluid Dynamics V. Resseguier et al. 10.1007/s11831-020-09437-x
17. Recurrent neural network spectral method and its application in stable filtering problems Z. Sun et al. 10.1016/j.automatica.2024.112067
18. Predictability of Extreme Waves in the Lorenz-96 Model Near Intermittency and Quasi-Periodicity A. Sterk & D. van Kekem 10.1155/2017/9419024
19. An adjoint-free algorithm for conditional nonlinear optimal perturbations (CNOPs) via sampling B. Shi & G. Sun 10.5194/npg-30-263-2023
20. Interaction of Lyapunov vectors in the formulation of the nonlinear extension of the Kalman filter L. Palatella & A. Trevisan 10.1103/PhysRevE.91.042905
21. Integrating Recurrent Neural Networks With Data Assimilation for Scalable Data‐Driven State Estimation S. Penny et al. 10.1029/2021MS002843
22. Symmetries in the Lorenz-96 Model D. van Kekem & A. Sterk 10.1142/S0218127419500081
23. Detectability Conditions and State Estimation for Linear Time-Varying and Nonlinear Systems M. Tranninger et al. 10.1137/21M1429473
24. Filter accuracy for the Lorenz 96 model: Fixed versus adaptive observation operators K. Law et al. 10.1016/j.physd.2015.12.008
25. Particle filtering for chaotic dynamical systems using future right-singular vectors R. Beeson & N. Sri Namachchivaya 10.1007/s11071-020-05727-y
26. Detectability Analysis and Observer Design for Linear Time Varying Systems M. Tranninger et al. 10.1109/LCSYS.2019.2927549
27. Dynamics of real-time forecasting failure and recovery due to data gaps: A study using EnKF-based assimilation with the Lorenz model S. Wu & R. Wang 10.1016/j.envsoft.2024.106250
28. Predictability of extreme values in geophysical models A. Sterk et al. 10.5194/npg-19-529-2012
29. Finite Cascades of Pitchfork Bifurcations and Multistability in Generalized Lorenz-96 Models A. Pelzer & A. Sterk 10.3390/mca25040078
30. Nonlinear stability of traffic models and the use of Lyapunov vectors for estimating the traffic state L. Palatella et al. 10.1103/PhysRevE.88.022901
31. The EKF-AUS-NL algorithm implemented without the linear tangent model and in presence of parametric model error L. Palatella & F. Grasso 10.1016/j.softx.2018.01.001
32. Particle filters for data assimilation based on reduced‐order data models J. Maclean & E. Van Vleck 10.1002/qj.4001
33. The Hybrid Local Ensemble Transform Kalman Filter S. Penny 10.1175/MWR-D-13-00131.1
34. Travelling waves and their bifurcations in the Lorenz-96 model D. van Kekem & A. Sterk 10.1016/j.physd.2017.11.008
35. Ensemble Riemannian data assimilation: towards large-scale dynamical systems S. Tamang et al. 10.5194/npg-29-77-2022
36. Simulation of Complex Systems Using the Observed Data Based on Recurrent Artificial Neural Networks A. Seleznev et al. 10.1007/s11141-019-09945-2
37. Latent space data assimilation by using deep learning M. Peyron et al. 10.1002/qj.4153
38. Degenerate Kalman Filter Error Covariances and Their Convergence onto the Unstable Subspace M. Bocquet et al. 10.1137/16M1068712
39. Wave propagation in the Lorenz-96 model D. van Kekem & A. Sterk 10.5194/npg-25-301-2018
40. The role of model dynamics in ensemble Kalman filter performance for chaotic systems G. Ng et al. 10.1111/j.1600-0870.2011.00539.x
41. Lyapunov vectors and assimilation in the unstable subspace: theory and applications L. Palatella et al. 10.1088/1751-8113/46/25/254020
42. CHAOS AND WEATHER FORECASTING: THE ROLE OF THE UNSTABLE SUBSPACE IN PREDICTABILITY AND STATE ESTIMATION PROBLEMS A. TREVISAN & L. PALATELLA 10.1142/S0218127411030635