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Data assimilation for stratified convection
Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Nordic Institute for Theoretical Physics (Nordita).
2013 (English)In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 433, no 3, 2278-2285 p.Article in journal (Refereed) Published
Abstract [en]

We show how the 3DVAR data assimilation methodology can be used in the astrophysical context of a two-dimensional convection flow. We study the way in which this variational approach finds best estimates of the current state of the flow from a weighted average of model states and observations. We use numerical simulations to generate synthetic observations of a vertical two-dimensional slice of the outer part of the solar convection zone for varying noise levels, and implement 3DVAR when the covariance matrices are diagonal and proportional to the identity matrix. Our simulation results demonstrate the capability of 3DVAR to produce error estimates of system states that can be more than two orders of magnitude below the original noise level present in the observations. This work illustrates the importance of applying data to obtain accurate model estimates given a set of observations. It also exemplifies how data assimilation techniques can be applied to simulations of stratified convection.

Place, publisher, year, edition, pages
2013. Vol. 433, no 3, 2278-2285 p.
Keyword [en]
chaos, convection, MHD, methods: numerical, methods: statistical, Sun: general
National Category
Astronomy, Astrophysics and Cosmology
Identifiers
URN: urn:nbn:se:su:diva-93308DOI: 10.1093/mnras/stt891ISI: 000322403800043OAI: oai:DiVA.org:su-93308DiVA: diva2:646102
Funder
EU, European Research Council, 227952
Note

AuthorCount:3;

Available from: 2013-09-06 Created: 2013-09-06 Last updated: 2017-12-06Bibliographically approved

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Brandenburg, Axel
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