14 citations as recorded by crossref.

1. Ensemble Kalman Filters for State Estimation and Prediction of Two-Time Scale Nonlinear Systems With Application to Gas Turbine Engines N. Daroogheh et al. 10.1109/TCST.2018.2870044
2. Using the ensemble Kalman filter to estimate multiplicative model parameters X. Yang & T. Delsole 10.1111/j.1600-0870.2009.00407.x
3. Two-Stage Filtering for Joint State-Parameter Estimation N. Santitissadeekorn & C. Jones 10.1175/MWR-D-14-00176.1
4. An approach to estimating and extrapolating model error based on inverse problem methods: towards accurate numerical weather prediction S. Hu et al. 10.1088/1674-1056/23/8/089201
5. Improving surface soil moisture retrievals through a novel assimilation algorithm to estimate both model and observation errors J. Tian et al. 10.1016/j.rse.2021.112802
6. Progress in integrating remote sensing data and hydrologic modeling X. Xu et al. 10.1177/0309133314536583
7. Inferred variables in data assimilation: quantifying sensitivity to inaccurate error statistics M. JUCKES & B. LAWRENCE 10.1111/j.1600-0870.2008.00376.x
8. Reducing Forecast Errors Due to Model Imperfections Using Ensemble Kalman Filtering H. Koyama & M. Watanabe 10.1175/2010MWR3067.1
9. Identification of an optimal derivatives approximation by variational data assimilation E. Kazantsev 10.1016/j.jcp.2009.09.018
10. Localized adaptive inflation in ensemble data assimilation for a radiation belt model H. Godinez & J. Koller 10.1029/2012SW000767
11. A Stochastic Approximation-Langevinized Ensemble Kalman Filter Algorithm for State Space Models with Unknown Parameters T. Dong et al. 10.1080/10618600.2022.2107531
12. Data assimilation for identification of cardiovascular network characteristics R. Lal et al. 10.1002/cnm.2824
13. A hybrid space approach for ensemble‐based 4‐D variational data assimilation A. Shao et al. 10.1029/2009JD012032
14. Estimation of Data Assimilation Error: A Shallow-Water Model Study A. Vlasenko et al. 10.1175/MWR-D-13-00205.1