Empirical determination of the covariance of forecast errors: An empirical justification and reformulation of hybrid covariance models
暂无分享,去创建一个
[1] M. Buehner,et al. Atmospheric Data Assimilation with an Ensemble Kalman Filter: Results with Real Observations , 2005 .
[2] Shunji Kotsuki,et al. Weight structure of the Local Ensemble Transform Kalman Filter: A case with an intermediate atmospheric general circulation model , 2020, Quarterly Journal of the Royal Meteorological Society.
[3] P. Courtier,et al. A strategy for operational implementation of 4D‐Var, using an incremental approach , 1994 .
[4] E. Kalnay,et al. Balance and Ensemble Kalman Filter Localization Techniques , 2011 .
[5] J. Wishart. THE GENERALISED PRODUCT MOMENT DISTRIBUTION IN SAMPLES FROM A NORMAL MULTIVARIATE POPULATION , 1928 .
[6] Anthony Hollingsworth,et al. The statistical structure of short-range forecast errors as determined from radiosonde data , 1986 .
[7] T. Auligne,et al. Optimized Localization and Hybridization to Filter Ensemble-Based Covariances , 2015 .
[8] Craig H. Bishop,et al. Adaptive sampling with the ensemble transform Kalman filter , 2001 .
[9] P. Bickel,et al. Obstacles to High-Dimensional Particle Filtering , 2008 .
[10] T. Hamill,et al. A Hybrid Ensemble Kalman Filter-3D Variational Analysis Scheme , 2000 .
[11] Xuguang Wang,et al. GSI-Based Four-Dimensional Ensemble–Variational (4DEnsVar) Data Assimilation: Formulation and Single-Resolution Experiments with Real Data for NCEP Global Forecast System , 2014 .
[12] Massimo Bonavita,et al. The ensemble Kalman filter in an operational regional NWP system: preliminary results with real observations , 2008 .
[13] Jonathan Flowerdew. Towards a theory of optimal localisation , 2015 .
[14] G. Evensen. Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statistics , 1994 .
[15] A. Lorenc,et al. Operational implementation of a hybrid ensemble/4D‐Var global data assimilation system at the Met Office , 2013 .
[16] Craig H. Bishop,et al. Hidden Error Variance Theory. Part I: Exposition and Analytic Model , 2013 .
[17] F. Molteni. Atmospheric simulations using a GCM with simplified physical parametrizations. I: model climatology and variability in multi-decadal experiments , 2003 .
[18] P. Houtekamer,et al. A Sequential Ensemble Kalman Filter for Atmospheric Data Assimilation , 2001 .
[19] Roland Potthast,et al. Particle filters for applications in geosciences , 2018, 1807.10434.
[20] P. Leeuwen,et al. Nonlinear data assimilation in geosciences: an extremely efficient particle filter , 2010 .
[21] Colin J. Cotter,et al. Probabilistic Forecasting and Bayesian Data Assimilation , 2015 .
[22] A. Hollingsworth,et al. The statistical structure of short-range forecast errors as determined from radiosonde data Part II: The covariance of height and wind errors , 1986 .
[23] J. Whitaker,et al. Ensemble Data Assimilation without Perturbed Observations , 2002 .
[24] P. Houtekamer,et al. Data Assimilation Using an Ensemble Kalman Filter Technique , 1998 .
[25] Jeffrey L. Anderson. An Ensemble Adjustment Kalman Filter for Data Assimilation , 2001 .
[26] T. Miyoshi. The Gaussian Approach to Adaptive Covariance Inflation and Its Implementation with the Local Ensemble Transform Kalman Filter , 2011 .
[27] Craig H. Bishop,et al. Comparison of Hybrid Ensemble/4DVar and 4DVar within the NAVDAS-AR Data Assimilation Framework , 2013 .