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Original Articles

Development of NAVDAS-AR: formulation and initial tests of the linear problem

, &
Pages 546-559 | Received 20 Jul 2004, Accepted 10 Dec 2004, 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 (5)

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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Yonghan Choi, Gyu-Ho Lim, Dong-Kyou Lee & Xiang-Yu Huang. (2014) An adjoint sensitivity-based data assimilation method and its comparison with existing variational methods. Tellus A: Dynamic Meteorology and Oceanography 66:1.
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Yonghan Choi, Gyu-Ho Lim & Dong-Kyou Lee. (2013) Radar radial wind data assimilation using the time-incremental 4D-Var method implemented to the WRFDA system. Tellus A: Dynamic Meteorology and Oceanography 65:1.
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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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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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Hui Christophersen, Benjamin Ruston & Nancy L. Baker. (2023) Assimilation of GNSS Zenith Total Delay in NAVGEM. Journal of Geophysical Research: Atmospheres 128:3.
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Douglas R. AllenKarl W. HoppelGerald E. NedoluhaStephen D. EckermannCory A. Barton. (2022) Ensemble-Based Gravity Wave Parameter Retrieval for Numerical Weather Prediction. Journal of the Atmospheric Sciences 79:3, pages 621-648.
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Brett T. Hoover & Chris S. Velden. (2020) Adjoint-Derived Impact of Assimilated Observations on Tropical Cyclone Intensity Forecasts of Hurricane Joaquin (2015) and Hurricane Matthew (2016). Journal of Atmospheric and Oceanic Technology 37:8, pages 1333-1352.
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Russell L. Elsberry, Eric A. Hendricks, Christopher S. Velden, Michael M. Bell, Melinda Peng, Eleanor Casas & Qingyun Zhao. (2018) Demonstration with Special TCI-15 Datasets of Potential Impacts of New-Generation Satellite Atmospheric Motion Vectors on Navy Regional and Global Models. Weather and Forecasting 33:6, pages 1617-1637.
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Sergey Frolov, Douglas R. AllenCraig H. Bishop, Rolf Langland, Karl W. HoppelDavid D. Kuhl. (2018) First Application of the Local Ensemble Tangent Linear Model (LETLM) to a Realistic Model of the Global Atmosphere. Monthly Weather Review 146:7, pages 2247-2270.
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Douglas R. Allen, Karl W. Hoppel & David D. Kuhl. (2018) Extraction of wind and temperature information from hybrid 4D-Var assimilation of stratospheric ozone using NAVGEM. Atmospheric Chemistry and Physics 18:4, pages 2999-3026.
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David D. Flagg, James D. Doyle, Teddy R. Holt, Daniel P. Tyndall, Clark M. Amerault, Daniel Geiszler, Tracy Haack, Jonathan R. Moskaitis, Jason Nachamkin & Daniel P. Eleuterio. (2018) On the Impact of Unmanned Aerial System Observations on Numerical Weather Prediction in the Coastal Zone. Monthly Weather Review 146:2, pages 599-622.
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Hyo-Jong Song, Seoleun Shin, Ji-Hyun Ha & Sujeong Lim. (2017) The Advantages of Hybrid 4DEnVar in the Context of the Forecast Sensitivity to Initial Conditions. Journal of Geophysical Research: Atmospheres 122:22, pages 12,226-12,244.
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William F. Campbell, Elizabeth A. Satterfield, Benjamin Ruston & Nancy L. Baker. (2017) Accounting for Correlated Observation Error in a Dual-Formulation 4D Variational Data Assimilation System. Monthly Weather Review 145:3, pages 1019-1032.
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Brett T. HOOVER & Rolf H. LANGLAND. (2017) Forecast and Observation-Impact Experiments in the Navy Global Environmental Model with Assimilation of ECWMF Analysis Data in the Global Domain. Journal of the Meteorological Society of Japan. Ser. II 95:6, pages 369-389.
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Douglas R. AllenCraig H. Bishop, Sergey Frolov, Karl W. HoppelDavid D. KuhlGerald E. Nedoluha. (2017) Hybrid 4DVAR with a Local Ensemble Tangent Linear Model: Application to the Shallow-Water Model. Monthly Weather Review 145:1, pages 97-116.
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Douglas R. Allen, Karl W. Hoppel & David D. Kuhl. (2016) Hybrid ensemble 4DVar assimilation of stratospheric ozone using a global shallow water model. Atmospheric Chemistry and Physics 16:13, pages 8193-8204.
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Max Yaremchuk, Paul Martin, Andrey Koch & Christopher Beattie. (2016) Comparison of the adjoint and adjoint-free 4dVar assimilation of the hydrographic and velocity observations in the Adriatic Sea. Ocean Modelling 97, pages 129-140.
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Craig H. Bishop, Bo Huang & Xuguang Wang. (2015) A Nonvariational Consistent Hybrid Ensemble Filter. Monthly Weather Review 143:12, pages 5073-5090.
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David D. KuhlThomas E. Rosmond, Craig H. Bishop, Justin McLay & Nancy L. Baker. (2013) Comparison of Hybrid Ensemble/4DVar and 4DVar within the NAVDAS-AR Data Assimilation Framework. Monthly Weather Review 141:8, pages 2740-2758.
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Meng Zhang & Fuqing Zhang. (2012) E4DVar: Coupling an Ensemble Kalman Filter with Four-Dimensional Variational Data Assimilation in a Limited-Area Weather Prediction Model. Monthly Weather Review 140:2, pages 587-600.
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Craig H. Bishop & Daniel Hodyss. (2011) Adaptive Ensemble Covariance Localization in Ensemble 4D-VAR State Estimation. Monthly Weather Review 139:4, pages 1241-1255.
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