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Graham Stonebridge, K. Andrea Scott & Mark Buehner. (2018) Impacts on sea ice analyses from the assumption of uncorrelated ice thickness observation errors: Experiments using a 1D toy model. Tellus A: Dynamic Meteorology and Oceanography 70:1, pages 1-13.
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Vincent Chabot, Maelle Nodet, Nicolas Papadakis & Arthur Vidard. (2015) Accounting for observation errors in image data assimilation. Tellus A: Dynamic Meteorology and Oceanography 67:1.
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Joanne A. Waller, Sarah L. Dance, Amos S. Lawless & Nancy K. Nichols. (2014) Estimating correlated observation error statistics using an ensemble transform Kalman filter. Tellus A: Dynamic Meteorology and Oceanography 66:1.
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Articles from other publishers (62)
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Eviatar Bach & Michael Ghil. (2023) A Multi‐Model Ensemble Kalman Filter for Data Assimilation and Forecasting. Journal of Advances in Modeling Earth Systems 15:1.
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Yanjun Gan, Yu Zhang, Yuqiong Liu, Cezar Kongoli & Christopher Grassotti. (2022) Assimilation of blended in situ-satellite snow water equivalent into the National Water Model for improving hydrologic simulation in two US river basins. Science of The Total Environment 838, pages 156567.
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Andreas Wagner, Benjamin Fersch, Peng Yuan, Thomas Rummler & Harald Kunstmann. (2022) Assimilation of GNSS and Synoptic Data in a Convection Permitting Limited Area Model: Improvement of Simulated Tropospheric Water Vapor Content. Frontiers in Earth Science 10.
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Tadashi Fujita, Hiromu Seko & Takuya Kawabata. (2022) Effects of Flow Dependency Introduced by Background Error in Frequent and Dense Assimilation of Radial Winds Using Observation Error Correlated in Time and Space. Monthly Weather Review 150:3, pages 481-503.
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Jemima M. Tabeart, Sarah L. Dance, Amos S. Lawless, Nancy K. Nichols & Joanne A. Waller. (2021) New bounds on the condition number of the Hessian of the preconditioned variational data assimilation problem. Numerical Linear Algebra with Applications 29:1.
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Mohammadreza Khanarmuei, Neda Mardani, Kabir Suara, Julius Sumihar, Scott W. McCue, Roy C. Sidle, Adrian McCallum & Richard J. Brown. (2021) Assimilation of GPS-tracked drifter data to improve the Eulerian velocity fields in an estuary. Estuarine, Coastal and Shelf Science 262, pages 107575.
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Sibo Cheng, Jean-Philippe Argaud, Bertrand Iooss, Angélique Ponçot & Didier Lucor. (2021) A Graph Clustering Approach to Localization for Adaptive Covariance Tuning in Data Assimilation Based on State-Observation Mapping. Mathematical Geosciences 53:8, pages 1751-1780.
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Guannan Hu & Sarah L. Dance. (2021) Efficient computation of matrix–vector products with full observation weighting matrices in data assimilation. Quarterly Journal of the Royal Meteorological Society 147:741, pages 4101-4121.
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Joanne A. Waller, Sarah L. Dance & Humphrey W. Lean. (2021) Evaluating errors due to unresolved scales in convection‐permitting numerical weather prediction. Quarterly Journal of the Royal Meteorological Society 147:738, pages 2657-2669.
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Sibo Cheng, Jean-Philippe Argaud, Bertrand Iooss, Didier Lucor & Angélique Ponçot. (2020) Error covariance tuning in variational data assimilation: application to an operating hydrological model. Stochastic Environmental Research and Risk Assessment 35:5, pages 1019-1038.
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Andrew K. Mirza, Sarah L. Dance, Gabriel G. Rooney, David Simonin, Edmund K. Stone & Joanne A. Waller. (2021) Comparing diagnosed observation uncertainties with independent estimates: A case study using aircraft‐based observations and a convection‐permitting data assimilation system. Atmospheric Science Letters 22:5.
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María Magdalena Lucini, Peter Jan van Leeuwen & Manuel Pulido. (2021) Model Error Estimation Using the Expectation Maximization Algorithm and a Particle Flow Filter. SIAM/ASA Journal on Uncertainty Quantification 9:2, pages 681-707.
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Shaodong Zang & Jichao Wang. (2019) Considering the impact of observation error correlation in ensemble square-root Kalman filter. Brazilian Journal of Oceanography 67.
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Jemima M. Tabeart, Sarah L. Dance, Stephen A. Haben, Amos S. Lawless, Nancy K. Nichols & Joanne A. Waller. (2018) The conditioning of least‐squares problems in variational data assimilation. Numerical Linear Algebra with Applications 25:5.
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Max Yaremchuk, Joseph M. D'Addezio, Gleb Panteleev & Gregg Jacobs. (2018) On the approximation of the inverse error covariances of high‐resolution satellite altimetry data. Quarterly Journal of the Royal Meteorological Society 144:715, pages 1995-2000.
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T. Janjić, N. Bormann, M. Bocquet, J. A Carton, S. E. Cohn, S. L. Dance, S. N. Losa, N. K. Nichols, R. Potthast, J. A. Waller & P. Weston. (2017) On the representation error in data assimilation. Quarterly Journal of the Royal Meteorological Society 144:713, pages 1257-1278.
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A. M. Fowler, S. L. Dance & J. A. Waller. (2017) On the interaction of observation and prior error correlations in data assimilation. Quarterly Journal of the Royal Meteorological Society 144:710, pages 48-62.
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Su Lee, Myoung-Hwan Ahn & Sung-Rae Chung. (2017) Atmospheric Profile Retrieval Algorithm for Next Generation Geostationary Satellite of Korea and Its Application to the Advanced Himawari Imager. Remote Sensing 9:12, pages 1294.
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S.W. Funke, P.E. Farrell & M.D. Piggott. (2017) Reconstructing wave profiles from inundation data. Computer Methods in Applied Mechanics and Engineering 322, pages 167-186.
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Ewan M. Pinnington, Eric Casella, Sarah L. Dance, Amos S. Lawless, James I.L. Morison, Nancy K. Nichols, Matthew Wilkinson & Tristan L. Quaife. (2016) Investigating the role of prior and observation error correlations in improving a model forecast of forest carbon balance using Four-dimensional Variational data assimilation. Agricultural and Forest Meteorology 228-229, pages 299-314.
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Sabrina Rainwater, Craig H. Bishop & William F. Campbell. (2015) The benefits of correlated observation errors for small scales. Quarterly Journal of the Royal Meteorological Society 141:693, pages 3439-3445.
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P. A. Browne, C. Charlton-Perez & S. L. Dance. (2014) RMetS Special Interest Group Meeting: high resolution data assimilation. Atmospheric Science Letters, pages n/a-n/a.
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J. A. Waller, S. L. Dance, A. S. Lawless, N. K. Nichols & J. R. Eyre. (2013) Representativity error for temperature and humidity using the Met Office high‐resolution model†. Quarterly Journal of the Royal Meteorological Society 140:681, pages 1189-1197.
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