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Tellus A: Dynamic Meteorology and Oceanography Volume 52, 2000 - Issue 2
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Original Articles

Towards a true 4-dimensional data assimilation algorithm: application of a cycling representer algorithm to a simple transport problem

Liang XuNaval Research L aboratory, 7 Grace Hopper Ave., Monterey, CA93943-5502, USA;;Science Applications International Corporation,Correspondence[email protected]
&
Roger DaleyNaval Research L aboratory, 7 Grace Hopper Ave., Monterey, CA93943-5502, USA;;University Corporation for Atmospheric Research
Pages 109-128 | Received 03 Dec 1998, Accepted 01 Jul 1999, Published online: 15 Dec 2016

Citations (18)

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Byoung-Joo Jung, Sangil Kim & Youngsoon Jo. (2014) Representer-based variational data assimilation in a spectral element shallow water model on the cubed-sphere grid. Tellus A: Dynamic Meteorology and Oceanography 66:1.
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Wei Kang & Liang Xu. (2012) Optimal placement of mobile sensors for data assimilations. Tellus A: Dynamic Meteorology and Oceanography 64:1.
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Jun Qin, Ronggao Liu, Shunlin Liang, Hao Zhang & Bo Hu. (2007) A new method based on remote sensing observations and data assimilation for estimation of evapotranspiration over field crops. New Zealand Journal of Agricultural Research 50:5, pages 997-1004.
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Thomas Rosmond & Liang Xu. (2006) Development of NAVDAS-AR: non-linear formulation and outer loop tests. Tellus A: Dynamic Meteorology and Oceanography 58:1, pages 45-58.
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Liang Xu, Tom Rosmond & Roger Daley. (2005) Development of NAVDAS-AR: formulation and initial tests of the linear problem. Tellus A: Dynamic Meteorology and Oceanography 57:4, pages 546-559.
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Liang Xu & Roger Daley. (2002) Data assimilation with a barotropically unstable shallow water system using representer algorithms. Tellus A: Dynamic Meteorology and Oceanography 54:2, pages 125-137.
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Articles from other publishers (12)

Apoorv Srivastava, Wei Kang & Daniel M. Tartakovsky. (2023) Feature-informed data assimilation. Journal of Computational Physics 494, pages 112499.
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. 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 785 795 .
. 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 753 763 .
Srdjan Dobricic. (2013) An Application of Sequential Variational Method without Tangent Linear and Adjoint Model Integrations. Monthly Weather Review 141:1, pages 307-323.
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Colin Y. Shen, Thomas E. Evans & Steven Finette. (2010) Polynomial Chaos Quantification of the Growth of Uncertainty Investigated with a Lorenz Model. Journal of Atmospheric and Oceanic Technology 27:6, pages 1059-1071.
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Marco A Iglesias & Clint Dawson. (2009) An iterative representer-based scheme for data inversion in reservoir modeling. Inverse Problems 25:3, pages 035006.
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Srdjan Dobricic. (2009) A Sequential Variational Algorithm for Data Assimilation in Oceanography and Meteorology. Monthly Weather Review 137:1, pages 269-287.
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Hans E. Ngodock, Scott R. Smith & Gregg A. Jacobs. 2009. Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications. Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications 321 340 .
H. E. Ngodock, S. R. Smith & G. A. Jacobs. (2007) Cycling the Representer Algorithm for Variational Data Assimilation with the Lorenz Attractor. Monthly Weather Review 135:2, pages 373-386.
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S. K. Park. (2004) Inverse three-dimensional variational data assimilation for an advection-diffusion problem: Impact of diffusion and hybrid application. Geophysical Research Letters 31:4.
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