22 citations as recorded by crossref.

1. A 3D ensemble variational data assimilation scheme for the limited‐area AROME model: Formulation and preliminary results T. Montmerle et al. 10.1002/qj.3334
2. Comparison of Hybrid-4DEnVar and Hybrid-4DVar Data Assimilation Methods for Global NWP A. Lorenc et al. 10.1175/MWR-D-14-00195.1
3. An Adaptive Variance Adjustment Strategy for a Static Background Error Covariance Matrix—Part I: Verification in the Lorenz-96 Model L. Huang et al. 10.3390/app15126399
4. Numerical Simulation of Ocean Circulation with Ultrahigh Spatial Resolution G. Korotaev & V. Shutyaev 10.1134/S000143382003010X
5. Optimized Localization and Hybridization to Filter Ensemble-Based Covariances B. Ménétrier & T. Auligné 10.1175/MWR-D-15-0057.1
6. A review of operational methods of variational and ensemble‐variational data assimilation R. Bannister 10.1002/qj.2982
7. Assimilation of Doppler Radar Data with an Ensemble 3DEnVar Approach to Improve Convective Forecasting S. Gao et al. 10.1007/s00376-020-0081-z
8. Use of Microwave Radiances from Metop-C and Fengyun-3 C/D Satellites for a Northern European Limited-area Data Assimilation System M. Lindskog et al. 10.1007/s00376-021-0326-5
9. Data assimilation in the geosciences: An overview of methods, issues, and perspectives A. Carrassi et al. 10.1002/wcc.535
10. Improving Background Error Covariances in a 3D Ensemble–Variational Data Assimilation System for Regional NWP J. Caron et al. 10.1175/MWR-D-18-0248.1
11. Towards a Data-Derived Observation Error Covariance Matrix for Satellite Measurements Y. Liu et al. 10.3390/rs11151770
12. Impact of non‐stationarity on hybrid ensemble filters: A study with a doubly stochastic advection‐diffusion‐decay model M. Tsyrulnikov & A. Rakitko 10.1002/qj.3556
13. All-sky infrared radiance data assimilation of FY-4A AGRI with different physical parameterizations for the prediction of an extremely heavy rainfall event D. Xu et al. 10.1016/j.atmosres.2023.106898
14. Efficient Regional Hybrid Ensemble-Variational Data Assimilation using the Global-Ensemble-Model-Augmented Error Covariance for Numerical Weather Prediction over Eastern China Y. Wang et al. 10.3390/atmos11040365
15. A comparison between EDA-EnVar and ETKF-EnVar data assimilation techniques using radar observations at convective scales through a case study of Hurricane Ike (2008) F. Shen et al. 10.1007/s00703-017-0544-7
16. Methods for Observation Data Assimilation in Problems of Physics of Atmosphere and Ocean V. Shutyaev 10.1134/S0001433819010080
17. On the Use of Cost-Effective Valid-Time-Shifting (VTS) Method to Increase Ensemble Size in the GFS Hybrid 4DEnVar System B. Huang & X. Wang 10.1175/MWR-D-18-0009.1
18. Application of 3-D ensemble variational data assimilation to a Baltic Sea reanalysis 19892013 L. Axell & Y. Liu 10.3402/tellusa.v68.24220
19. The Role of Weather Radar in Rainfall Estimation and Its Application in Meteorological and Hydrological Modelling—A Review Z. Sokol et al. 10.3390/rs13030351
20. Applying Time-Expended Sampling to Ensemble Assimilation of Remote-Sensing Data for Short-Term Predictions of Thunderstorms H. Zhang et al. 10.3390/rs15092358
21. Four-dimensional ensemble variational (4D-En-Var) data assimilation for the HIgh Resolution Limited Area Model (HIRLAM) N. Gustafsson & J. Bojarova 10.5194/npg-21-745-2014
22. Regional Ensemble–Variational Data Assimilation Using Global Ensemble Forecasts W. Wu et al. 10.1175/WAF-D-16-0045.1