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Tellus A: Dynamic Meteorology and Oceanography Volume 65, 2013 - Issue 1

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Data assimilation and predictability

Ensemble data assimilation with an adjusted forecast spread

Sabrina RainwaterDepartment of Mathematics, University of Maryland, College Park, Maryland, USACorrespondence[email protected]

Brian R. Hunt

Article: 19929 | Received 23 Oct 2012, Accepted 28 Feb 2013, Published online: 04 Apr 2013

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https://doi.org/10.3402/tellusa.v65i0.19929

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Articles from other publishers (4)

Jie Feng, Xuguang Wang & Jonathan Poterjoy. (2020) A Comparison of Two Local Moment-Matching Nonlinear Filters: Local Particle Filter (LPF) and Local Nonlinear Ensemble Transform Filter (LNETF). Monthly Weather Review 148:11, pages 4377-4395.
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Andrea Storto, Simona Masina, Simona Simoncelli, Doroteaciro Iovino, Andrea Cipollone, Marie Drevillon, Yann Drillet, Karina von Schuckman, Laurent Parent, Gilles Garric, Eric Greiner, Charles Desportes, Hao Zuo, Magdalena A. Balmaseda & K. Andrew Peterson. (2018) The added value of the multi-system spread information for ocean heat content and steric sea level investigations in the CMEMS GREP ensemble reanalysis product. Climate Dynamics 53:1-2, pages 287-312.
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Jianrong Lu & Ahmad Ghassemi. (2019) Estimating natural fracture orientations using geomechanics based stochastic analysis of microseismicity related to reservoir stimulation. Geothermics 79, pages 129-139.
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Julian Tödter & Bodo Ahrens. (2015) A Second-Order Exact Ensemble Square Root Filter for Nonlinear Data Assimilation. Monthly Weather Review 143:4, pages 1347-1367.
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