23 citations as recorded by crossref.

1. Background error covariances for a BlendVar assimilation system A. Bučánek & R. Brožková https://doi.org/10.1080/16000870.2017.1355718
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3. Estimation of Flow-Dependent Unbalanced Variances in Four-Dimensional Variational Data Assimilation 士. 侯 https://doi.org/10.12677/AG.2020.107063
4. On Applying Large-Scale Correction to Limited-Area Numerical Weather Prediction Models A. Dipankar et al. https://doi.org/10.3390/atmos13071142
5. Constraining the Large‐Scale Analysis of a Regional Rapid‐Update‐Cycle System for Short‐Term Convective Precipitation Forecasting X. Tang et al. https://doi.org/10.1029/2018JD030190
6. Survey of data assimilation methods for convective‐scale numerical weather prediction at operational centres N. Gustafsson et al. https://doi.org/10.1002/qj.3179
7. Introducing large‐scale analysis constraints in regional hybrid EnVar data assimilation for the prediction of triple typhoons Y. Wang et al. https://doi.org/10.1002/qj.4671
8. A Dynamic Blending Scheme to Mitigate Large‐Scale Bias in Regional Models J. Feng et al. https://doi.org/10.1029/2019MS001754
9. Dynamic Downscaling Simulation and Projection of Precipitation Extremes Over China Under a Shared Socioeconomic Pathway Scenario N. Luo et al. https://doi.org/10.1029/2022JD037133
10. A Combined Approach to Improving the Regional Model Forecasts for the Rainy Season in China Y. Zhao et al. https://doi.org/10.1175/MWR-D-17-0037.1
11. SINGV‐DA: A data assimilation system for convective‐scale numerical weather prediction over Singapore B. Heng et al. https://doi.org/10.1002/qj.3774
12. Assessing the impact of a NWP warm‐start system on model spin‐up over tropical Africa J. Warner et al. https://doi.org/10.1002/qj.4429
13. Impact of assimilating GOES imager clear‐sky radiance with a rapid refresh assimilation system for convection‐permitting forecast over Mexico C. Yang et al. https://doi.org/10.1002/2016JD026436
14. An Implementation of Full Cycle Strategy Using Dynamic Blending for Rapid Refresh Short-range Weather Forecasting in China J. Feng et al. https://doi.org/10.1007/s00376-021-0316-7
15. An improved method for dynamical extended-range forecasting of persistent severe rainfall based on the coupling of MPAS-A and regional models Y. Zhang et al. https://doi.org/10.1016/j.atmosres.2024.107908
16. Validation of ash cloud modelling with satellite retrievals: a case study of the 16–17 June 1996 Mount Ruapehu eruption J. Liu et al. https://doi.org/10.1007/s11069-015-1753-3
17. Evaluation and Bias Correction in WRF Model Forecasting of Precipitation and Potential Evapotranspiration T. Bughici et al. https://doi.org/10.1175/JHM-D-18-0160.1
18. Model Sensitivity Evaluation for 3DVAR Data Assimilation Applied on WRF with a Nested Domain Configuration M. Lam & J. Fung https://doi.org/10.3390/atmos12060682
19. Comparing Partial and Continuously Cycling Ensemble Kalman Filter Data Assimilation Systems for Convection-Allowing Ensemble Forecast Initialization C. Schwartz et al. https://doi.org/10.1175/WAF-D-21-0069.1
20. Improving the regional model forecasting of persistent severe rainfall over the Yangtze River Valley using the spectral nudging and update cycle methods: a case study Y. Zhao et al. https://doi.org/10.1002/asl.731
21. Assessing the Accuracy of 3D-VAR in Supercell Thunderstorm Forecasting: A Regional Background Error Covariance Study I. Samos et al. https://doi.org/10.3390/atmos14111611
22. Blending of global and regional ensembles in cycling hybrid ensemble-variational data assimilation for the convection-permitting prediction of typhoon Merbok (2017) X. Qian et al. https://doi.org/10.1016/j.atmosres.2024.107502
23. Flow-Dependent Large-Scale Blending for Limited-Area Ensemble Data Assimilation S. Nakashita & T. Enomoto https://doi.org/10.16993/tellusa.4089