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Mathematical and Algorithmic Aspects of Data Assimilation in the Geosciences

dc.date.accessioned2019-10-24T15:23:02Z
dc.date.available2019-10-24T15:23:02Z
dc.date.issued2016
dc.identifier.urihttp://publications.mfo.de/handle/mfo/3551
dc.description.abstractThe field of “Data Assimilation” has been driven by applications from the geosciences where complex mathematical models are interfaced with observational data in order to improve model forecasts. Mathematically, data assimilation is closely related to filtering and smoothing on the one hand and inverse problems and statistical inference on the other. Key challenges of data assimilation arise from the high-dimensionality of the underlying models, combined with systematic spatio-temporal model errors, pure model uncertainty quantification and relatively sparse observation networks. Advances in the field of data assimilation will require combination of a broad range of mathematical techniques from differential equations, statistics, machine learning, probability, scientific computing and mathematical modeling, together with insights from practitioners in the field. The workshop brought together a collection of scientists representing this broad spectrum of research strands.
dc.titleMathematical and Algorithmic Aspects of Data Assimilation in the Geosciences
dc.rights.licenseDieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.de
dc.rights.licenseThis document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties.en
dc.identifier.doi10.14760/OWR-2016-47
local.series.idOWR-2016-47
local.subject.msc60
local.subject.msc37
local.sortindex991
local.date-range02 Oct - 08 Oct 2016
local.workshopcode1640
local.workshoptitleMathematical and Algorithmic Aspects of Data Assimilation in the Geosciences
local.organizersAndreas Griewank, Berlin; Sebastian Reich, Potsdam; Ian Roulstone, Guildford; Andrew Stuart, Coventry
local.report-nameWorkshop Report 2016,47
local.opc-photo-id1640
local.publishers-doi10.4171/OWR/2016/47
local.ems-referenceGriewank Andreas, Reich Sebastian, Roulstone Ian, Stuart Andrew: Mathematical and Algorithmic Aspects of Data Assimilation in the Geosciences. Oberwolfach Rep. 13 (2016), 2705-2748. doi: 10.4171/OWR/2016/47


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