Print Email Facebook Twitter Accelerating volcanic ash data assimilation using a mask-state algorithm based on an ensemble Kalman filter: A case study with the LOTOS-EUROS model (version 1.10) Title Accelerating volcanic ash data assimilation using a mask-state algorithm based on an ensemble Kalman filter: A case study with the LOTOS-EUROS model (version 1.10) Author Fu, G. Xiang Lin, H. Heemink, A. Lu, S. Segers, A. van Velzen, N. Lu, T. Xu, S. Publication year 2017 Abstract In this study, we investigate a strategy to accelerate the data assimilation (DA) algorithm. Based on evaluations of the computational time, the analysis step of the assimilation turns out to be the most expensive part. After a study of the characteristics of the ensemble ash state, we propose a mask-state algorithm which records the sparsity information of the full ensemble state matrix and transforms the full matrix into a relatively small one. This will reduce the computational cost in the analysis step. Experimental results show the mask-state algorithm significantly speeds up the analysis step. Subsequently, the total amount of computing time for volcanic ash DA is reduced to an acceptable level. The mask-state algorithm is generic and thus can be embedded in any ensemble-based DA framework. Moreover, ensemble-based DA with the mask-state algorithm is promising and flexible, because it implements exactly the standard DA without any approximation and it realizes the satisfying performance without any change in the full model. © 2017 The Author(s). Subject 2015 Urban Mobility & EnvironmentCAS - Climate, Air and SustainabilityELSS - Earth, Life and Social SciencesEnvironment & SustainabilityEnvironmentUrbanisationalgorithmdata assimilationexperimental studyinformation systemKalman filternumerical modelstandard (reference)volcanic ash To reference this document use: http://resolver.tudelft.nl/uuid:4e9b0106-7e4f-400c-a1d1-f7d7b9ae05ea DOI https://doi.org/10.5194/gmd-10-1751-2017 TNO identifier 762772 Publisher Copernicus GmbH ISSN 1991-959X Source Geoscientific Model Development, 10 (4), 1751-1766 Document type article Files To receive the publication files, please send an e-mail request to TNO Library.