93 citations as recorded by crossref.

1. Rainfall forecasting skill of GFS model at T1534 and T574 resolution over India during the monsoon season C. Sridevi et al. 10.1007/s00703-019-00672-x
2. 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
3. Hybrid Background Error Covariances for a Limited-Area Deterministic Weather Prediction System J. Bédard et al. 10.1175/WAF-D-19-0069.1
4. Forward sensitivity approach for estimating eddy viscosity closures in nonlinear model reduction S. Ahmed et al. 10.1103/PhysRevE.102.043302
5. Weakly coupled atmosphere–ocean data assimilation in the Canadian global prediction system (v1) S. Skachko et al. 10.5194/gmd-12-5097-2019
6. A parallel implementation of a 4DEnVar ensemble É. Arbogast et al. 10.1002/qj.3061
7. Scale-Dependent Background Error Covariance Localization: Evaluation in a Global Deterministic Weather Forecasting System J. Caron & M. Buehner 10.1175/MWR-D-17-0369.1
8. Particle filters for high‐dimensional geoscience applications: A review P. van Leeuwen et al. 10.1002/qj.3551
9. Unraveling the Mechanism of Extreme (More than 30 Sigma) Precipitation during August 2018 and 2019 over Kerala, India P. Mukhopadhyay et al. 10.1175/WAF-D-20-0162.1
10. Uncertainty Quantification of WRF Model for Rainfall Prediction over the Sichuan Basin, China Y. Du et al. 10.3390/atmos13050838
11. A review of operational methods of variational and ensemble‐variational data assimilation R. Bannister 10.1002/qj.2982
12. Development of a Hybrid En3DVar Data Assimilation System and Comparisons with 3DVar and EnKF for Radar Data Assimilation with Observing System Simulation Experiments R. Kong et al. 10.1175/MWR-D-17-0164.1
13. Using Icepack to reproduce ice mass balance buoy observations in landfast ice: improvements from the mushy-layer thermodynamics M. Plante et al. 10.5194/tc-18-1685-2024
14. Formulation and use of 3D‐hybrid and 4D‐hybrid ensemble covariances in the Météo‐France global data assimilation system L. Berre & E. Arbogast 10.1002/qj.4603
15. Handling non-linearity in radar data assimilation using the non-linear least squares enhanced POD-4DVar B. Zhang et al. 10.1007/s11430-015-0271-4
16. Estimation of Systematic Errors in the GFS Using Analysis Increments K. Bhargava et al. 10.1002/2017JD027423
17. A study on harmonizing total ozone assimilation with multiple sensors Y. Rochon et al. 10.5194/acp-19-9431-2019
18. Assimilation of Infrared Radiance Observations with Sensitivity to Land Surfaces in the Canadian Ensemble–Variational System S. Dutta et al. 10.1175/JAMC-D-15-0208.1
19. A Hierarchical Bayes Ensemble Kalman Filter M. Tsyrulnikov & A. Rakitko 10.1016/j.physd.2016.07.009
20. West African operational daily solar forecast errors and their link with meteorological conditions L. Clauzel et al. 10.1016/j.renene.2024.120101
21. Near-Surface Wind Observation Impact on Forecasts: Temporal Propagation of the Analysis Increment J. Bédard et al. 10.1175/MWR-D-16-0310.1
22. Implementation of Deterministic Weather Forecasting Systems Based on Ensemble–Variational Data Assimilation at Environment Canada. Part II: The Regional System J. Caron et al. 10.1175/MWR-D-14-00353.1
23. The Impact of Incremental Analysis Update on Regional Simulations for Typhoons Y. Ge et al. 10.1029/2022MS003084
24. Assimilation of radar radial velocity data with the WRF hybrid 4DEnVar system for the prediction of hurricane Ike (2008) F. Shen et al. 10.1016/j.atmosres.2019.104771
25. Object-Based Verification of GSI EnKF and Hybrid En3DVar Radar Data Assimilation and Convection-Allowing Forecasts within a Warn-on-Forecast Framework L. Chen et al. 10.1175/WAF-D-20-0180.1
26. Survey of data assimilation methods for convective‐scale numerical weather prediction at operational centres N. Gustafsson et al. 10.1002/qj.3179
27. Unraveling the socio-environmental drivers during the early COVID-19 pandemic in China A. Alaniz et al. 10.1007/s11356-023-27969-0
28. Was the extreme rainfall that caused the August 2022 flood in Pakistan predictable? I. Malik et al. 10.1088/2752-5295/acfa1a
29. Optimized Localization and Hybridization to Filter Ensemble-Based Covariances B. Ménétrier & T. Auligné 10.1175/MWR-D-15-0057.1
30. Improving spatial localization in 4DEnVar G. Desroziers et al. 10.1002/qj.2898
31. Hybrid ensemble 4DVar assimilation of stratospheric ozone using a global shallow water model D. Allen et al. 10.5194/acp-16-8193-2016
32. Hybrid 4DVAR with a Local Ensemble Tangent Linear Model: Application to the Shallow-Water Model D. Allen et al. 10.1175/MWR-D-16-0184.1
33. A comparison of variational, ensemble-based, and hybrid data assimilation methods over East Asia for two one-month periods E. Yang & H. Kim 10.1016/j.atmosres.2020.105257
34. PyDA: A Hands-On Introduction to Dynamical Data Assimilation with Python S. Ahmed et al. 10.3390/fluids5040225
35. The Near-Real-Time SCALE-LETKF System: A Case of the September 2015 Kanto-Tohoku Heavy Rainfall G. Lien et al. 10.2151/sola.2017-001
36. Tensor Formulation of Ensemble-Based Background Error Covariance Matrix Factorization T. Ishibashi 10.1175/MWR-D-15-0014.1
37. An Ensemble Kalman Filter for Numerical Weather Prediction Based on Variational Data Assimilation: VarEnKF M. Buehner et al. 10.1175/MWR-D-16-0106.1
38. To what extent is your data assimilation scheme designed to find the posterior mean, the posterior mode or something else? D. Hodyss et al. 10.3402/tellusa.v68.30625
39. A Fast and Generic Method to Identify Parameters in Complex and Embedded Geophysical Models: The Example of Turbulent Mixing in the Ocean C. Aldebert et al. 10.1029/2020MS002245
40. Rapid troposphere tomography using adaptive simultaneous iterative reconstruction technique W. Zhang et al. 10.1007/s00190-020-01386-4
41. Using a Cost-Effective Approach to Increase Background Ensemble Member Size within the GSI-Based EnVar System for Improved Radar Analyses and Forecasts of Convective Systems N. Gasperoni et al. 10.1175/MWR-D-21-0148.1
42. Real Data Assimilation Using the Local Ensemble Transform Kalman Filter (LETKF) System for a Global Non-hydrostatic NWP model on the Cubed-sphere S. Shin et al. 10.1007/s13143-018-0022-2
43. Block Krylov methods for accelerating ensembles of variational data assimilations F. Mercier et al. 10.1002/qj.3329
44. Towards ensemble data assimilation for the Environment Canada Regional Ice Prediction System A. Shlyaeva et al. 10.1002/qj.2712
45. Regional Ensemble–Variational Data Assimilation Using Global Ensemble Forecasts W. Wu et al. 10.1175/WAF-D-16-0045.1
46. A New Approach for Estimating the Observation Impact in Ensemble–Variational Data Assimilation M. Buehner et al. 10.1175/MWR-D-17-0252.1
47. 100 Years of Progress in Forecasting and NWP Applications S. Benjamin et al. 10.1175/AMSMONOGRAPHS-D-18-0020.1
48. An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble‐Based Assimilation Methods H. Zhang & X. Tian 10.1002/2017JD027999
49. An OSSE-Based Evaluation of Hybrid Variational–Ensemble Data Assimilation for the NCEP GFS. Part II: 4DEnVar and Hybrid Variants D. Kleist & K. Ide 10.1175/MWR-D-13-00350.1
50. Implementation of Deterministic Weather Forecasting Systems Based on Ensemble–Variational Data Assimilation at Environment Canada. Part I: The Global System M. Buehner et al. 10.1175/MWR-D-14-00354.1
51. Precision and convergence speed of the ensemble Kalman filter-based parameter estimation: setting parameter uncertainty for reliable and efficient estimation K. Sueki et al. 10.1186/s40645-022-00504-4
52. The Local Ensemble Tangent Linear Model: an enabler for coupled model 4D‐Var C. Bishop et al. 10.1002/qj.2986
53. Dependence on initial conditions versus model formulations for medium‐range forecast error variations L. Magnusson et al. 10.1002/qj.3545
54. Satellite Flood Inundation Assessment and Forecast Using SMAP and Landsat J. Du et al. 10.1109/JSTARS.2021.3092340
55. Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta) B. Jung et al. 10.5194/gmd-17-3879-2024
56. International challenge to predict the impact of radioxenon releases from medical isotope production on a comprehensive nuclear test ban treaty sampling station P. Eslinger et al. 10.1016/j.jenvrad.2016.03.001
57. Evaluating the Forecast Impact of Assimilating ATOVS Radiance With the Regional System of Multigrid NLS‐4DVar Data Assimilation for Numerical Weather Prediction (SNAP) H. Zhang & X. Tian 10.1029/2020MS002407
58. Comparison of Hybrid-4DEnVar and Hybrid-4DVar Data Assimilation Methods for Global NWP A. Lorenc et al. 10.1175/MWR-D-14-00195.1
59. Contributions of natural and anthropogenic sources to ambient ammonia in the Athabasca Oil Sands and north-western Canada C. Whaley et al. 10.5194/acp-18-2011-2018
60. Assimilating All-sky Infrared Radiances from Himawari-8 Using the 3DVar Method for the Prediction of a Severe Storm over North China D. Xu et al. 10.1007/s00376-020-0219-z
61. Integrated Hybrid Data Assimilation for an Ensemble Kalman Filter 10.1175/MWR-D-21-0002.1
62. A Second-Order Exact Ensemble Square Root Filter for Nonlinear Data Assimilation J. Tödter & B. Ahrens 10.1175/MWR-D-14-00108.1
63. A geo‐statistical observation operator for the assimilation of near‐surface wind data J. Bédard et al. 10.1002/qj.2569
64. Development of an Operational Hybrid Data Assimilation System at KIAPS I. Kwon et al. 10.1007/s13143-018-0029-8
65. International challenge to model the long-range transport of radioxenon released from medical isotope production to six Comprehensive Nuclear-Test-Ban Treaty monitoring stations C. Maurer et al. 10.1016/j.jenvrad.2018.01.030
66. Impact of hybrid GSI analysis using ETR ensembles V. Prasad & C. Johny 10.1007/s12040-016-0673-2
67. The Advantages of Hybrid 4DEnVar in the Context of the Forecast Sensitivity to Initial Conditions H. Song et al. 10.1002/2017JD027598
68. High-Resolution NWP Forecast Precipitation Comparison over Complex Terrain of the Sierras de Córdoba during RELAMPAGO-CACTI G. Casaretto et al. 10.1175/WAF-D-21-0006.1
69. Ensemble analysis and forecast of ecosystem indicators in the North Atlantic using ocean colour observations and prior statistics from a stochastic NEMO–PISCES simulator M. Popov et al. 10.5194/os-20-155-2024
70. Sensitivities of the NCEP Global Forecast System J. Wang et al. 10.1175/MWR-D-18-0239.1
71. Scale-dependent background-error covariance localisation M. Buehner & A. Shlyaeva 10.3402/tellusa.v67.28027
72. Development of an Early Warning and Incident Response System for the Protection of Visitors from Natural Hazards in Important Outdoor Sites in Greece C. Psaroudakis et al. 10.3390/su13095143
73. An OSSE-Based Evaluation of Hybrid Variational–Ensemble Data Assimilation for the NCEP GFS. Part I: System Description and 3D-Hybrid Results D. Kleist & K. Ide 10.1175/MWR-D-13-00351.1
74. Data assimilation in the geosciences: An overview of methods, issues, and perspectives A. Carrassi et al. 10.1002/wcc.535
75. Impact of Coupling with an Ice–Ocean Model on Global Medium-Range NWP Forecast Skill G. Smith et al. 10.1175/MWR-D-17-0157.1
76. Third international challenge to model the medium- to long-range transport of radioxenon to four Comprehensive Nuclear-Test-Ban Treaty monitoring stations C. Maurer et al. 10.1016/j.jenvrad.2022.106968
77. 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
78. An ensemble-variational inversion system for the estimation of ammonia emissions using CrIS satellite ammonia retrievals M. Sitwell et al. 10.5194/acp-22-6595-2022
79. Relationships among Four-Dimensional Hybrid Ensemble–Variational Data Assimilation Algorithms with Full and Approximate Ensemble Covariance Localization C. Liu & M. Xue 10.1175/MWR-D-15-0203.1
80. 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
81. Impacts of satellite data assimilation with different model vertical levels on QPFs downstream of the Tibetan Plateau Z. Qin & X. Zou 10.1007/s00703-020-00765-y
82. Evaluation of the Four-Dimensional Ensemble-Variational Hybrid Data Assimilation with Self-Consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts S. Zhang & Z. Pu 10.3390/atmos11091007
83. On Oceanic Initial State Errors in the Ensemble Data Assimilation for a Coupled General Circulation Model Y. Chen et al. 10.1029/2022MS003106
84. Assimilation of Wheat and Soil States into the APSIM-Wheat Crop Model: A Case Study Y. Zhang et al. 10.3390/rs14010065
85. Implementation of Scale-Dependent Background-Error Covariance Localization in the Canadian Global Deterministic Prediction System J. Caron & M. Buehner 10.1175/WAF-D-22-0055.1
86. A Four‐Dimensional Ensemble‐Variational (4DEnVar) Data Assimilation System Based on GRAPES‐GFS: System Description and Primary Tests S. Zhu et al. 10.1029/2021MS002737
87. A hybrid approach to generating search subspaces in dynamically constrained 4-dimensional data assimilation M. Yaremchuk et al. 10.1016/j.ocemod.2017.08.003
88. Estimation of the Added Value of the Absolute Calibration of GPS Radio Occultation Data for Numerical Weather Prediction J. Aparicio & S. Laroche 10.1175/MWR-D-14-00153.1
89. Non-Gaussian Deterministic Assimilation of Radar-Derived Precipitation Accumulations M. Buehner & D. Jacques 10.1175/MWR-D-19-0199.1
90. JMA Operational Hourly Hybrid 3DVar with Singular Vector-Based Mesoscale Ensemble Prediction System S. YOKOTA et al. 10.2151/jmsj.2024-006
91. Comparison between Four-Dimensional LETKF and Ensemble-Based Variational Data Assimilation with Observation Localization S. Yokota et al. 10.2151/sola.2016-019
92. Improvement of the Snow Depth in the Common Land Model by Coupling a Two-Dimensional Deterministic Ensemble Model with a Variational Hybrid Snow Cover Fraction Data Assimilation Scheme and a New Observation Operator J. Xu et al. 10.1175/JHM-D-16-0149.1
93. Estimation of regional-scale near real time reference evapotranspiration using remote sensing and weather data to improve agriculture advisory A. Soni et al. 10.1007/s12145-023-01197-z