77
Views
36
CrossRef citations to date
0
Altmetric
Original Articles

The application of Kalman smoother theory to the estimation of 4DVAR error statistics

&
Pages 221-237 | Received 16 Sep 1994, Accepted 10 Jul 1995, Published online: 15 Dec 2016

Keep up to date with the latest research on this topic with citation updates for this article.

Read on this site (6)

C. M. Thomas & K. Haines. (2017) Using lagged covariances in data assimilation. Tellus A: Dynamic Meteorology and Oceanography 69:1.
Read now
Heikki Järvinen. (2001) Temporal evolution of innovation and residual statistics in the ECMWF variational data assimilation systems. Tellus A: Dynamic Meteorology and Oceanography 53:3, pages 333-347.
Read now
Jian Zhu & Masafumi Kamachi. (2000) An adaptive variational method for data assimilation with imperfect models. Tellus A: Dynamic Meteorology and Oceanography 52:3, pages 265-279.
Read now
Claude Fischer, Alain Joly & François Lalaurette. (1998) Error growth and Kalman filtering within an idealized baroclinic flow. Tellus A: Dynamic Meteorology and Oceanography 50:5, pages 596-615.
Read now
Olaf Berke. (1998) On spatiotemporal prediction for on-line monitoring data. Communications in Statistics - Theory and Methods 27:9, pages 2343-2369.
Read now
Herschel L. Mitchell & Roger Daley. (1997) Discretization error and signal/error correlation in atmospheric data assimilation : (I). All scales resolved. Tellus A: Dynamic Meteorology and Oceanography 49:1, pages 32-53.
Read now

Articles from other publishers (30)

. 2023. Data Assimilation for the Geosciences. Data Assimilation for the Geosciences 1073 1094 .
Steven J. Fletcher. 2023. Data Assimilation for the Geosciences. Data Assimilation for the Geosciences 797 813 .
Bo Dong, Keith Haines & Matthew Martin. (2021) Improved High Resolution Ocean Reanalyses Using a Simple Smoother Algorithm. Journal of Advances in Modeling Earth Systems 13:12.
Crossref
. 2017. Data Assimilation for the Geosciences. Data Assimilation for the Geosciences 923 939 .
Steven J. Fletcher. 2017. Data Assimilation for the Geosciences. Data Assimilation for the Geosciences 765 782 .
Zhijin Li, Xiaoping Cheng, William I. Gustafson Jr. & Andrew M. Vogelmann. (2016) Spectral characteristics of background error covariance and multiscale data assimilation. International Journal for Numerical Methods in Fluids 82:12, pages 1035-1048.
Crossref
Sergey Skachko, Richard Ménard, Quentin Errera, Yves Christophe & Simon Chabrillat. (2016) EnKF and 4D-Var data assimilation with chemical transport model BASCOE (version 05.06). Geoscientific Model Development 9:8, pages 2893-2908.
Crossref
S. Skachko, Q. Errera, R. Ménard, Y. Christophe & S. Chabrillat. (2014) Comparison of the ensemble Kalman filter and 4D-Var assimilation methods using a stratospheric tracer transport model. Geoscientific Model Development 7:4, pages 1451-1465.
Crossref
P. L. Houtekamer, Xingxiu Deng, Herschel L. Mitchell, Seung-Jong Baek & Normand Gagnon. (2014) Higher Resolution in an Operational Ensemble Kalman Filter. Monthly Weather Review 142:3, pages 1143-1162.
Crossref
S. Skachko, Q. Errera, R. Ménard, Y. Christophe & S. Chabrillat. (2014) Comparison of the ensemble Kalman filter and 4D-Var assimilation methods using a stratospheric tracer transport model. Geoscientific Model Development Discussions 7:1, pages 339-377.
Crossref
M. J. P. Cullen. (2013) Analysis of cycled 4D-Var with model error. Quarterly Journal of the Royal Meteorological Society 139:675, pages 1473-1480.
Crossref
Z. Li, Z. Zang, Q. B. Li, Y. Chao, D. Chen, Z. Ye, Y. Liu & K. N. Liou. (2013) A three-dimensional variational data assimilation system for multiple aerosol species with WRF/Chem and an application to PM<sub>2.5</sub> prediction. Atmospheric Chemistry and Physics 13:8, pages 4265-4278.
Crossref
S. Lakshmivarahan, J. M. Lewis & D. Phan. (2013) Data Assimilation as a Problem in Optimal Tracking: Application of Pontryagin’s Minimum Principle to Atmospheric Science. Journal of the Atmospheric Sciences 70:4, pages 1257-1277.
Crossref
Andrew S. Jones & Steven J. Fletcher. 2013. Solar Energy Forecasting and Resource Assessment. Solar Energy Forecasting and Resource Assessment 319 355 .
Z. Li, Z. Zang, Q. B. Li, Y. Chao, D. Chen, Z. Ye, Y. Liu & K.-N. Liou. (2012) A three-dimensional variational data assimilation system for multiple aerosol species with WRF/Chem and an application to PM<sub>2.5</sub> prediction. Atmospheric Chemistry and Physics Discussions 12:5, pages 13515-13552.
Crossref
Monika Krysta, Eric Blayo, Emmanuel Cosme & Jacques Verron. (2011) A Consistent Hybrid Variational-Smoothing Data Assimilation Method: Application to a Simple Shallow-Water Model of the Turbulent Midlatitude Ocean. Monthly Weather Review 139:11, pages 3333-3347.
Crossref
R. N. Bannister. (2008) A review of forecast error covariance statistics in atmospheric variational data assimilation. I: Characteristics and measurements of forecast error covariances. Quarterly Journal of the Royal Meteorological Society 134:637, pages 1951-1970.
Crossref
D. P. Dee. (2006) Bias and data assimilation. Quarterly Journal of the Royal Meteorological Society 131:613, pages 3323-3343.
Crossref
M. Fisher, M. Leutbecher & G. A. Kelly. (2006) On the equivalence between Kalman smoothing and weak‐constraint four‐dimensional variational data assimilation. Quarterly Journal of the Royal Meteorological Society 131:613, pages 3235-3246.
Crossref
Yoshi K. Sasaki. (2003) A Theory of Variational Assimilation with Kalman Filter–Type Constraints: Bias and Lagrange Multiplier. Monthly Weather Review 131:11, pages 2545-2554.
Crossref
Andrew C. Lorenc. (2006) Modelling of error covariances by 4D‐Var data assimilation. Quarterly Journal of the Royal Meteorological Society 129:595, pages 3167-3182.
Crossref
Yanqiu Zhu, Ricardo Todling, Jing Guo, Stephen E. Cohn, I. Michael Navon & Yan Yang. (2003) The GEOS-3 Retrospective Data Assimilation System: The 6-Hour Lag Case. Monthly Weather Review 131:9, pages 2129-2150.
Crossref
A. T. Weaver, J. Vialard & D. L. T. Anderson. (2003) Three- and Four-Dimensional Variational Assimilation with a General Circulation Model of the Tropical Pacific Ocean. Part I: Formulation, Internal Diagnostics, and Consistency Checks. Monthly Weather Review 131:7, pages 1360-1378.
Crossref
Angela Benedetti, Graeme L. Stephens & Tomislava Vukićević. (2006) Variational assimilation of radar reflectivities in a cirrus model. II: Optimal initialization and model bias estimation. Quarterly Journal of the Royal Meteorological Society 129:587, pages 301-319.
Crossref
Eugenia Kalnay. 2012. Atmospheric Modeling, Data Assimilation and Predictability. Atmospheric Modeling, Data Assimilation and Predictability.
Roger Daley. (1997) Atmospheric Data Assimilation (gtSpecial IssueltData Assimilation in Meteology and Oceanography: Theory and Practice). Journal of the Meteorological Society of Japan. Ser. II 75:1B, pages 319-329.
Crossref
Michael Ghil. (1997) Advances in Sequential Estimation for Atmospheric and Oceanic Flows (gtSpecial IssueltData Assimilation in Meteology and Oceanography: Theory and Practice). Journal of the Meteorological Society of Japan. Ser. II 75:1B, pages 289-304.
Crossref
Stephen E. Cohn. (1997) An Introduction to Estimation Theory (gtSpecial IssueltData Assimilation in Meteology and Oceanography: Theory and Practice). Journal of the Meteorological Society of Japan. Ser. II 75:1B, pages 257-288.
Crossref
Kayo Ide, Philippe Courtier, Michael Ghil & Andrew C. Lorenc. (1997) Unified Notation for Data Assimilation : Operational, Sequential and Variational (gtSpecial IssueltData Assimilation in Meteology and Oceanography: Theory and Practice). Journal of the Meteorological Society of Japan. Ser. II 75:1B, pages 181-189.
Crossref
R. Daley. (1996) Recovery of the one and two dimensional windfields from chemical constituent observations using the constituent transport equation and an extended Kalman filter. Meteorology and Atmospheric Physics 60:1-3, pages 119-136.
Crossref