A parallel implementation of the ensemble Kalman filter based on modified Cholesky decomposition-Reference-Cited by-同舟云学术

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A parallel implementation of the ensemble Kalman filter based on modified Cholesky decomposition

Published:2019-09 Issue: Volume:36 Page:100654
ISSN:1877-7503
Container-title:Journal of Computational Science
language:en
Short-container-title:Journal of Computational Science

Author:

Nino-Ruiz Elias D.,Sandu Adrian,Deng Xinwei

Funder

NSF

AFOSR

Computational Science Laboratory at Virginia Tech

Publisher

Elsevier BV

Subject

Modelling and Simulation,General Computer Science,Theoretical Computer Science

Reference19 articles.

1. Software for ensemble-based data assimilation systems – implementation strategies and scalability;Nerger;Comput. Geosci.,2013

2. A time-parallel approach to strong-constraint four-dimensional variational data assimilation;Rao;J. Comput. Phys.,2016

3. Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities;Liu;Hydrol. Earth Syst. Sci.,2012

4. Theoretical and practical issues of ensemble data assimilation in weather and climate;Zupanski,2009

5. Ensemble smoother with multiple data assimilation;Emerick;Comput. Geosci.,2013

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2. A Novel Localized Fast Multipole Method for Computations With Spatially Correlated Observation Error Statistics in Data Assimilation;Journal of Advances in Modeling Earth Systems;2024-06

3. State-of-charge estimation of Lithium-ion batteries using an adaptive dual unscented Kalman filter based on a reduced-order model;Journal of Energy Storage;2023-12

4. Adaptive Workload-Balanced Scheduling Strategy for Global Ocean Data Assimilation on Massive GPUs;Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis;2023-11-11

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