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A Reduced-Order Kalman Filter for Data Assimilation in Physical Oceanography

D. Rozier, F. Birol, E. Cosme, P. Brasseur, J. M. Brankart, J. Verron
2007 SIAM Review  
The main part of this paper focuses on the Kalman filter as a data assimilation method, and especially on how this mathematical technique, usually associated with a prohibitively high computing cost for  ...  A central task of physical oceanography is the prediction of ocean circulation at various time scales.  ...  We would like to thank Eric Blayo from the Laboratory of Modelling and Calculus in Grenoble (LMC, IMAG) for his useful feedback on this paper, and Julie Dugdale for her thorough English proofreading.  ... 
doi:10.1137/050635717 fatcat:zrnhdhxbcrgr3hy3fi22mwdpq4

Geostatistics and Sequential Data Assimilation [chapter]

Hans Wackernagel, Laurent Bertino
2005 Quantitative Geology and Geostatistics  
The reduced rank square root filter and the ensemble Kalman filter are presented from this perspective.  ...  Contributions of geostatistics are discussed showing that sequential data assimilation is a promising area for the application of geostatistical techniques. 893  ...  Kalman filter We present the Kalman filter in its so-called reduced rank square-root (RRSQRT) version (Verlaan and Heemink, 1997) using notation that is close to the one used in geostatistics.  ... 
doi:10.1007/978-1-4020-3610-1_92 fatcat:khovhwqnrvhd5lwmfbfdhe7yvi

Sequential Data Assimilation Techniques in Oceanography

Laurent Bertino, Geir Evensen, Hans Wackernagel
2007 International Statistical Review  
We review recent developments of sequential data assimilation techniques used in oceanography to integrate spatio-temporal observations into numerical models describing physical and ecological dynamics  ...  Current methods derived from the Kalman filter are presented from the least complex to the most general and perspectives for nonlinear estimation by sequential importance resampling filters are discussed  ...  Acknowledgments The present work was performed in relation with the EC funded MAST III project Pioneer and has been partly supported by a grant of computer time from the Norwegian Supercomputing Committee  ... 
doi:10.1111/j.1751-5823.2003.tb00194.x fatcat:cgbqc6hoefekvkes7imw55ncmm

Data Assimilation and Predictability Studies for the Coupled Ocean-Atmosphere System

Michael Ghil, Carlos Mechoso
1992 Oceanography  
Our approach is to develop methods for data assimilation from sequential estimation and control theory and for predictability studies from dynamical systems and statistical turbulence theory: these methods  ...  AS OCEANIC DATA SETS increase dramatically in quality and quantity in the near future, and both oceanic and atmospheric models improve apace, the predictability of the coupled ocean-atmosphere system will  ...  Acknowledgements It is a pleasure to thank the other participants in this project: Y. Chao, Y. Feliks, M. Fisher, Z. OCEANOGRAPHY-Vol. 5. No. 1.1992  ... 
doi:10.5670/oceanog.1992.27 fatcat:fmavrcm2i5hnjmtijopn6u7z24

Comparison of the Kalman smoothing technique with other ocean diagnostic methods

V. A. Moiseenko, O. A. Saenko
1994 Physical Oceanography  
The use of the Kalman smoothing technique is suggested to handle an ocean diagnosis problem.  ...  It is shown that the variety of existing diagnostic techniques may be generalized, for which purpose the smoothing problem from the theory of optimal evaluation may be used.  ...  assimilation [4] ; (iv) a variety of modified schemes of data assimilation using Kalman filtering [5, 6] ; and (v) variational techniques of data assimilation [7] .  ... 
doi:10.1007/bf02197514 fatcat:gkjx5k34zray3deu6fb3v4gkui

A methodology to test the pertinence of remote-sensing data assimilation into vegetation models for water and energy exchange at the land surface

Jennifer Pellenq, Gilles Boulet
2004 Agronomie  
This paper presents a methodology to test the performance of assimilation of satellite data into models for the functioning of the continental surface.  ...  The OSSE approach may present a first step in designing a decision support system, and also in predicting the usefulness of new types of satellite data. surface functioning / data assimilation / remote  ...  Acknowledgements: The authors thank Dara Entekhabi, MIT, and Steve Margulis, UCLA, for providing guidance and codes for the Ensemble Kalman Filter and the OSSE implementation.  ... 
doi:10.1051/agro:2004017 fatcat:y2joqyjqf5bi7b4odp2scqefym

Development of a physics-based reduced state Kalman filter for the ionosphere

L. Scherliess, R. W. Schunk, J. J. Sojka, D. C. Thompson
2004 Radio Science  
The main data assimilation in GAIM will be performed by a Kalman filter.  ...  In this paper we present a practical method for the implementation of a Kalman filter using a new physics-based ionosphere/plasmasphere model (IPM).  ...  , data assimilation models have become a dominant tool for specifications and forecasts in meteorology and oceanography.  ... 
doi:10.1029/2002rs002797 fatcat:dj6yke42uzb2fa3opbi5xpnkgm

Mapping tropical Pacific sea level: Data assimilation via a reduced state space Kalman filter

Mark A. Cane, Alexey Kaplan, Robert N. Miller, Benyang Tang, Eric C. Hackert, Anthony J. Busalacchi
1996 Journal of Geophysical Research  
The usual objection to applying the Kalman filter (KF) to problems in meteorology or oceanography is computational 22,599 22,600 CANE ET AL.: SEA LEVEL VIA A REDUCED STATE SPACE KALMAN FILTER expense.  ...  Here we report on an assimilation of monthly data for the period 1975-1992 from 34 tropical Pacific tide gauges into such a model using a Kalman filter.  ...  We have demonstrated the reduced state space Kalman filter as a feasible data assimilation procedure in a real oceanographic problem.  ... 
doi:10.1029/96jc01684 fatcat:l3sh3s3usve77cl6x2umta47uy

Data assimilation in large time-varying multidimensional fields

A. Asif, J.M.F. Moura
1999 IEEE Transactions on Image Processing  
In the physical sciences, e.g., meteorology and oceanography, combining measurements with the dynamics of the underlying models is usually referred to as data assimilation.  ...  Assimilating data with algorithms like the Kalman-Bucy filter (KBf) is challenging due to their computational cost which for two-dimensional (2-D) fields is of O(I 6 ) where I is the linear dimension of  ...  SUMMARY The paper considered data assimilation in problems in the physical sciences, in particular, in physical oceanography.  ... 
doi:10.1109/83.799887 pmid:18267434 fatcat:ooxrdskfefcf7pkqz4yumynmiu

A singular evolutive extended Kalman filter to assimilate real in situ data in a 1-D marine ecosystem model

I. Hoteit, G. Triantafyllou, G. Petihakis, J. I. Allen
2003 Annales Geophysicae  
A singular evolutive extended Kalman (SEEK) filter is used to assimilate real in situ data in a water column marine ecosystem model.  ...  The purpose of this contribution is to track the possibility of using data assimilation techniques for state estimation in marine ecosystem models.  ...  Eleftheriou for her help in editing this text, and K. Georgiou for software assistance. Topical Editor N. Pinardi thanks V. Echevin and another referee for their help in evaluating this paper.  ... 
doi:10.5194/angeo-21-389-2003 fatcat:6bndynnqzvcetarigtfougr5za

Data assimilation for geophysical fluids

Didier Auroux
2017 Annales de la Faculté des Sciences de Toulouse  
Conclusion We have presented in this paper several data assimilation methods: variational methods (4D-VAR and 4D-PSAS), sequential methods (extended Kalman filter, ensemble Kalman filter), with their reduced-order  ...  Sequential methods: Kalman filtering In this section, we will study data assimilation methods based on the statistical estimation theory, in which the Kalman filtering theory is the primary framework.  ... 
doi:10.5802/afst.1552 fatcat:gfprb2nwwrcwnc5tlrezhpylp4

Importance of data assimilation technique in defining the model drivers for the space weather specification of the high-latitude ionosphere

L. Zhu, R. Schunk, L. Scherliess, V. Eccles
2012 Radio Science  
With a set of physical models and an ensemble Kalman filter, the model can define the drivers that are most truthful to the real space environment by ingesting data from multiple observations.  ...  Presently, most of the space weather models use limited observations and/or indices to define a set of empirical drivers for physical models forward in time.  ...  We thank the reviewers for their constructive comments and suggestions. This work was supported by the Office of Naval Research under contract N000140910292.  ... 
doi:10.1029/2011rs004936 fatcat:tieukx2qpbbodatvpfvhpjeuya

Improved Disaster Management Using Data Assimilation [chapter]

Paul R.
2013 Approaches to Disaster Management - Examining the Implications of Hazards, Emergencies and Disasters  
Data Assimilation http://dx.  ...  Improved Disaster Management Using Data Assimilation Improved Disaster Management Using Data Assimilation Improved Disaster Management Using  ...  Data assimilation has also been successfully used in oceanography [6] for improving ocean dynamics prediction.  ... 
doi:10.5772/55840 fatcat:3lnxhwptojbypfjvrihha2r2ya

Ocean State Estimation for Climate Research

Tong Lee, Toshiyuki Awaji, Magdalena Balmaseda, Eric Greiner, Detlef Stammer
2009 Oceanography  
There have been an increasingly large number of applications of these products for a wide range of research topics in physical oceanography as well as other disciplines.  ...  A hierarchy of estimation methods is being used to routinely synthesize various observations with global ocean models. Many of the estimation products are available through public data servers.  ...  System APPLICATIONS Ocean state estimation products and tools have been applied to studies over a wide range of topics in physical oceanography, for instance, the nature of sea level variability (e.g  ... 
doi:10.5670/oceanog.2009.74 fatcat:n35revc6wne4lohkirhkpmfply

Identifying the radiation belt source region by data assimilation

J. Koller, Y. Chen, G. D. Reeves, R. H. W. Friedel, T. E. Cayton, J. A. Vrugt
2007 Journal of Geophysical Research  
1] We describe how assimilation of radiation belt data with a simple radial diffusion code can be used to identify and adjust for unknown physics in the model.  ...  Although the model does not contain explicit source or loss terms, the Kalman filter algorithm can implicitly add very localized sources or losses in order to reduce the discrepancy between model and observations  ...  Ensemble Kalman Filter [15] The term ''data assimilation'' is short for ''modelbased assimilation of observations''; that is, data assimilation is the combination of a given physical model with observations  ... 
doi:10.1029/2006ja012196 fatcat:ub2tbq7dhncwtn2ialetbcpfje
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