Optimal localization for ensemble Kalman filter systemsPerianez, A., Reich, H. and Potthast, R. ORCID: https://orcid.org/0000-0001-6794-2500 (2014) Optimal localization for ensemble Kalman filter systems. Journal of the Meteorological Society of Japan. Ser. II, 92 (6). pp. 585-597. ISSN 0026-1165 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.2151/jmsj.2014-605 Abstract/SummaryIn ensemble Kalman filter methods, localization is applied for both avoiding the spurious correlations of distant observations and increasing the effective size of the ensemble space. The procedure is essential in order to provide quality assimilation in large systems; however a severe localization can cause imbalances that impact negatively on the accuracy of the analysis. We want to understand the fundamental properties of localized ensemble methods and to investigate an optimal localization expression which minimizes the analysis error. The novel analytical expression derived in this work depends on the observation error, the density of measurements, and the approximation error, i.e., the error that comes from working in the ensemble space. The mathematical results are tested with two numerical simulations using a toy model. We demonstrate that observations with different observation error or density need different localization length scales.
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