A Comparison of Hybrid Ensemble Transform Kalman Filter–Optimum Interpolation and Ensemble Square Root Filter Analysis Schemes
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Craig H. Bishop | Thomas M. Hamill | Xuguang Wang | Jeffrey S. Whitaker | J. Whitaker | T. Hamill | C. Bishop | Xuguang Wang
[1] P. Houtekamer,et al. Ensemble size, balance, and model-error representation in an ensemble Kalman filter , 2002 .
[2] Craig H. Bishop,et al. A comparison of ensemble‐transform Kalman‐filter targeting guidance with ECMWF and NRL total‐energy singular‐vector guidance , 2002 .
[3] G. Evensen. Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statistics , 1994 .
[4] Lars Peter Riishojgaard,et al. A direct way of specifying flow‐dependent background error correlations for meteorological analysis systems , 1998 .
[5] Arnold W. Heemink,et al. A Hybrid Kalman Filter Algorithm for Large-Scale Atmospheric Chemistry Data Assimilation , 2007 .
[6] Roger Daley,et al. NAVDAS: Formulation and Diagnostics , 2001 .
[7] P. L. Houtekamer,et al. Ensemble Kalman filtering , 2005 .
[8] Eugenia Kalnay,et al. Ensemble Forecasting at NMC: The Generation of Perturbations , 1993 .
[9] C. Bishop,et al. Resilience of Hybrid Ensemble/3DVAR Analysis Schemes to Model Error and Ensemble Covariance Error , 2004 .
[10] Istvan Szunyogh,et al. A Local Ensemble Kalman Filter for Atmospheric Data Assimilation , 2002 .
[11] Stéphane Laroche,et al. Implementation of a 3D variational data assimilation system at the Canadian Meteorological Centre. Part I: The global analysis , 1999 .
[12] R. Purser,et al. Three-Dimensional Variational Analysis with Spatially Inhomogeneous Covariances , 2002 .
[13] Craig H. Bishop,et al. Ensemble Transformation and Adaptive Observations , 1999 .
[14] R. Daley. Atmospheric Data Analysis , 1991 .
[15] J. Whitaker,et al. Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter , 2001 .
[16] T. Hamill,et al. A Comparison of Probabilistic Forecasts from Bred, Singular-Vector, and Perturbed Observation Ensembles , 2000 .
[17] Xuguang Wang,et al. A Comparison of Breeding and Ensemble Transform Kalman Filter Ensemble Forecast Schemes , 2003 .
[18] P. Courtier,et al. The ECMWF implementation of three‐dimensional variational assimilation (3D‐Var). I: Formulation , 1998 .
[19] R. Daley. The Analysis of Synoptic Scale Divergence by a Statistical Interpolation Procedure , 1985 .
[20] D. Dee. On-line Estimation of Error Covariance Parameters for Atmospheric Data Assimilation , 1995 .
[21] T. Hamill,et al. On the Theoretical Equivalence of Differently Proposed Ensemble 3DVAR Hybrid Analysis Schemes , 2007 .
[22] M. Buehner. Ensemble‐derived stationary and flow‐dependent background‐error covariances: Evaluation in a quasi‐operational NWP setting , 2005 .
[23] M. Buehner,et al. Atmospheric Data Assimilation with an Ensemble Kalman Filter: Results with Real Observations , 2005 .
[24] John Derber,et al. The National Meteorological Center's spectral-statistical interpolation analysis system , 1992 .
[25] S. Julier,et al. Which Is Better, an Ensemble of Positive–Negative Pairs or a Centered Spherical Simplex Ensemble? , 2004 .
[26] J. Whitaker,et al. Ensemble Data Assimilation without Perturbed Observations , 2002 .
[27] Andrew C. Lorenc,et al. The potential of the ensemble Kalman filter for NWP—a comparison with 4D‐Var , 2003 .
[28] P. Courtier,et al. A strategy for operational implementation of 4D‐Var, using an incremental approach , 1994 .
[29] Jeffrey D. Kepert,et al. On ensemble representation of the observation-error covariance in the Ensemble Kalman Filter , 2004 .
[30] Geir Evensen,et al. The Ensemble Kalman Filter: theoretical formulation and practical implementation , 2003 .
[31] E. Kalnay,et al. Ensemble Forecasting at NCEP and the Breeding Method , 1997 .
[32] A. Simmons,et al. The ECMWF operational implementation of four‐dimensional variational assimilation. I: Experimental results with simplified physics , 2007 .
[33] Haixia Liu. Retrieval of Moisture from GPS Slant-path Water Vapor Observations using 3DVAR with Isotropic and Anisotropic Recursive Filters , 2005 .
[34] P. Courtier,et al. Extended assimilation and forecast experiments with a four‐dimensional variational assimilation system , 1998 .
[35] Istvan Szunyogh,et al. Assessing a local ensemble Kalman filter: Perfect model experiments with the NCEP global model , 2004 .
[36] P. Houtekamer,et al. A Sequential Ensemble Kalman Filter for Atmospheric Data Assimilation , 2001 .
[37] Istvan Szunyogh,et al. Can an ensemble transform Kalman filter predict the reduction in forecast-error variance produced by targeted observations? , 2001 .
[38] S. Zhang,et al. Impact of spatially and temporally varying estimates of error covariance on assimilation in a simple atmospheric model , 2003 .
[39] S. Cohn,et al. Assessing the Effects of Data Selection with the DAO Physical-Space Statistical Analysis System* , 1998 .
[40] N. Roberts,et al. Numerical Aspects of the Application of Recursive Filters to Variational Statistical Analysis. Part II: Spatially Inhomogeneous and Anisotropic General Covariances , 2003 .
[41] Juanzhen Sun,et al. Impacts of Initial Estimate and Observation Availability on Convective-Scale Data Assimilation with an Ensemble Kalman Filter , 2004 .
[42] G. Evensen,et al. Analysis Scheme in the Ensemble Kalman Filter , 1998 .
[43] T. Palmer,et al. Singular Vectors, Metrics, and Adaptive Observations. , 1998 .
[44] J. Whitaker,et al. Ensemble Square Root Filters , 2003, Statistical Methods for Climate Scientists.
[45] C. Snyder,et al. Assimilation of Simulated Doppler Radar Observations with an Ensemble Kalman Filter , 2003 .
[46] A. Lorenc. A Global Three-Dimensional Multivariate Statistical Interpolation Scheme , 1981 .
[47] Craig H. Bishop,et al. Adaptive sampling with the ensemble transform Kalman filter , 2001 .
[48] Peter Lynch,et al. Initialization of the HIRLAM Model Using a Digital Filter , 1992 .
[49] T. Hamill,et al. A Hybrid Ensemble Kalman Filter-3D Variational Analysis Scheme , 2000 .
[50] J. Whitaker,et al. An Adjoint Sensitivity Study of Blocking in a Two-Layer Isentropic Model , 1993 .
[51] Thomas Schlatter,et al. Some Experiments with a Multivariate Statistical Objective Analysis Scheme , 1975 .
[52] S. Cohn,et al. Ooce Note Series on Global Modeling and Data Assimilation Construction of Correlation Functions in Two and Three Dimensions and Convolution Covariance Functions , 2022 .
[53] P. Houtekamer,et al. Data Assimilation Using an Ensemble Kalman Filter Technique , 1998 .
[54] Craig H. Bishop,et al. Adaptive sampling with the ensemble transform Kalman filter , 2001 .
[55] Thomas M. Hamill,et al. Predictability of Weather and Climate: Ensemble-based atmospheric data assimilation , 2006 .
[56] J. Whitaker,et al. Accounting for the Error due to Unresolved Scales in Ensemble Data Assimilation: A Comparison of Different Approaches , 2005 .
[57] Mingjing Tong,et al. Ensemble kalman filter assimilation of doppler radar data with a compressible nonhydrostatic model : OSS experiments , 2005 .
[58] Istvan Szunyogh,et al. Assessing a local ensemble Kalman filter: perfect model experiments with the National Centers for Environmental Prediction global model , 2005 .
[59] Jeffrey L. Anderson. An Ensemble Adjustment Kalman Filter for Data Assimilation , 2001 .