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Inverse Problems in Science and Engineering Volume 21, 2013 - Issue 3: Includes a Special Section on Inverse Problems in Geosciences
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Special Section

Estimating and including observation-error correlations in data assimilation

Takemasa MiyoshiDepartment of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20742, USA
,
Eugenia KalnayDepartment of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20742, USA
&
Hong LiShanghai Typhoon Institute, Shanghai, China
Pages 387-398 | Received 16 Jun 2012, Accepted 19 Jun 2012, Published online: 31 Aug 2012

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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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Shigenori Otsuka, Taeka Awazu, Christian A. Welzbacher, Roland Potthast & Takemasa Miyoshi. 2023. Numerical Weather Prediction: East Asian Perspectives. Numerical Weather Prediction: East Asian Perspectives 283 294 .
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Marissa S. Kivi, Bethany Blakely, Michael Masters, Carl J. Bernacchi, Fernando E. Miguez & Hamze Dokoohaki. (2022) Development of a data-assimilation system to forecast agricultural systems: A case study of constraining soil water and soil nitrogen dynamics in the APSIM model. Science of The Total Environment 820, pages 153192.
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Yicun Zhen, Pierre Tandeo, Stéphanie Leroux, Sammy Metref, Thierry Penduff & Julien Le Sommer. (2020) An Adaptive Optimal Interpolation Based on Analog Forecasting: Application to SSH in the Gulf of Mexico. Journal of Atmospheric and Oceanic Technology 37:9, pages 1697-1711.
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Yue Ying. (2020) Assimilating Observations with Spatially Correlated Errors Using a Serial Ensemble Filter with a Multiscale Approach. Monthly Weather Review 148:8, pages 3397-3412.
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Rebecca Reid, Simon Good & Matthew J. Martin. (2020) Use of Uncertainty Inflation in OSTIA to Account for Correlated Errors in Satellite-Retrieved Sea Surface Temperature Data. Remote Sensing 12:7, pages 1083.
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Sammy Metref, Emmanuel Cosme, Florian Le Guillou, Julien Le Sommer, Jean-Michel Brankart & Jacques Verron. (2020) Wide-Swath Altimetric Satellite Data Assimilation With Correlated-Error Reduction. Frontiers in Marine Science 6.
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Takemasa Miyoshi, Shunji Kotsuki, Koji Terasaki, Shigenori Otsuka, Guo-Yuan Lien, Hisashi Yashiro, Hirofumi Tomita, Masaki Satoh & Eugenia Kalnay. 2020. Satellite Precipitation Measurement. Satellite Precipitation Measurement 983 991 .
Peter Jan van Leeuwen. (2019) Non-local Observations and Information Transfer in Data Assimilation. Frontiers in Applied Mathematics and Statistics 5.
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Yohei Sawada, Kozo Okamoto, Masaru Kunii & Takemasa Miyoshi. (2019) Assimilating Every‐10‐minute Himawari‐8 Infrared Radiances to Improve Convective Predictability. Journal of Geophysical Research: Atmospheres 124:5, pages 2546-2561.
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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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Patrick N. Raanes, Marc Bocquet & Alberto Carrassi. (2019) Adaptive covariance inflation in the ensemble Kalman filter by Gaussian scale mixtures. Quarterly Journal of the Royal Meteorological Society 145:718, pages 53-75.
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Ting Wang, Jianfang Fei, Xiaoping Cheng, Xiaogang Huang & Jian Zhong. (2018) Estimating the Correlated Observation-Error Characteristics of the Chinese FengYun Microwave Temperature Sounder and Microwave Humidity Sounder. Advances in Atmospheric Sciences 35:11, pages 1428-1441.
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Pierre Gauthier, Ping Du, Sylvain Heilliette & Louis Garand. (2018) Convergence Issues in the Estimation of Interchannel Correlated Observation Errors in Infrared Radiance Data. Monthly Weather Review 146:10, pages 3227-3239.
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Geir Evensen & Kjersti Solberg Eikrem. (2018) Conditioning reservoir models on rate data using ensemble smoothers. Computational Geosciences 22:5, pages 1251-1270.
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Alberto Carrassi, Marc Bocquet, Laurent Bertino & Geir Evensen. (2018) Data assimilation in the geosciences: An overview of methods, issues, and perspectives. WIREs Climate Change 9:5.
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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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Yue Ying & Fuqing Zhang. (2018) Potentials in Improving Predictability of Multiscale Tropical Weather Systems Evaluated through Ensemble Assimilation of Simulated Satellite-Based Observations. Journal of the Atmospheric Sciences 75:5, pages 1675-1698.
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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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Kai Wu, Hong Shu, Lei Nie & Zhenhang Jiao. (2018) Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation. Journal of Applied Remote Sensing 12:01, pages 1.
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Dean S. Oliver & Miguel Alfonzo. (2017) Calibration of imperfect models to biased observations. Computational Geosciences 22:1, pages 145-161.
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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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Daisuke Hotta, Eugenia Kalnay, Yoichiro Ota & Takemasa Miyoshi. (2017) EFSR: Ensemble Forecast Sensitivity to Observation Error Covariance. Monthly Weather Review 145:12, pages 5015-5031.
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J. A. Waller, S. L. Dance & N. K. Nichols. (2017) On diagnosing observation‐error statistics with local ensemble data assimilation. Quarterly Journal of the Royal Meteorological Society 143:708, pages 2677-2686.
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Kostas P. Tsiaras, Ibrahim Hoteit, Sofia Kalaroni, George Petihakis & George Triantafyllou. (2017) A hybrid ensemble-OI Kalman filter for efficient data assimilation into a 3-D biogeochemical model of the Mediterranean. Ocean Dynamics 67:6, pages 673-690.
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M. Cordoba, S. L. Dance, G. A. Kelly, N. K. Nichols & J. A. Waller. (2017) Diagnosing atmospheric motion vector observation errors for an operational high-resolution data assimilation system. Quarterly Journal of the Royal Meteorological Society 143:702, pages 333-341.
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Giovanni Abdelnur Ruggiero, Emmanuel Cosme, Jean-Michel Brankart, Julien Le Sommer & Clement Ubelmann. (2016) An Efficient Way to Account for Observation Error Correlations in the Assimilation of Data from the Future SWOT High-Resolution Altimeter Mission. Journal of Atmospheric and Oceanic Technology 33:12, pages 2755-2768.
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Joanne Waller, Susan Ballard, Sarah Dance, Graeme Kelly, Nancy Nichols & David Simonin. (2016) Diagnosing Horizontal and Inter-Channel Observation Error Correlations for SEVIRI Observations Using Observation-Minus-Background and Observation-Minus-Analysis Statistics. Remote Sensing 8:7, pages 581.
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Alicia R. Karspeck. (2016) An Ensemble Approach for the Estimation of Observational Error Illustrated for a Nominal 1° Global Ocean Model. Monthly Weather Review 144:5, pages 1713-1728.
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Masaru Kunii, Michiko Otsuka, Kazuki Shimoji & Hiromu Seko. (2016) Ensemble Data Assimilation and Forecast Experiments for the September 2015 Heavy Rainfall Event in Kanto and Tohoku Regions with Atmospheric Motion Vectors from Himawari-8. SOLA 12:0, pages 209-214.
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J. A. Waller, S. L. Dance & N. K. Nichols. (2015) Theoretical insight into diagnosing observation error correlations using observation‐minus‐background and observation‐minus‐analysis statistics. Quarterly Journal of the Royal Meteorological Society 142:694, pages 418-431.
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P. Tandeo, M. Pulido & F. Lott. (2015) Offline parameter estimation using EnKF and maximum likelihood error covariance estimates: Application to a subgrid-scale orography parametrization. Quarterly Journal of the Royal Meteorological Society 141:687, pages 383-395.
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G. Wu, X. Yi, L. Wang, X. Liang, S. Zhang, X. Zhang & X. Zheng. (2014) Improving the ensemble transform Kalman filter using a second-order Taylor approximation of the nonlinear observation operator. Nonlinear Processes in Geophysics 21:5, pages 955-970.
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Koji Terasaki & Takemasa Miyoshi. (2014) Data Assimilation with Error-Correlated and Non-Orthogonal Observations: Experiments with the Lorenz-96 Model. SOLA 10:0, pages 210-213.
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Ross N. Hoffman, Joseph V. Ardizzone, S. Mark Leidner, Deborah K. Smith & Robert Atlas. (2013) Error Estimates for Ocean Surface Winds: Applying Desroziers Diagnostics to the Cross-Calibrated, Multiplatform Analysis of Wind Speed. Journal of Atmospheric and Oceanic Technology 30:11, pages 2596-2603.
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