dc.contributorPark, Seon Ki
dc.contributorXu, Liang
dc.creatorPolavarapu, Saroja
dc.creatorPulido, Manuel Arturo
dc.date.accessioned2020-02-21T17:47:48Z
dc.date.accessioned2022-10-15T14:07:29Z
dc.date.available2020-02-21T17:47:48Z
dc.date.available2022-10-15T14:07:29Z
dc.date.created2020-02-21T17:47:48Z
dc.date.issued2016
dc.identifierPolavarapu, Saroja; Pulido, Manuel Arturo; Stratospheric and mesospheric data assimilation: the role of middle atmospheric dynamics; Springer; III; 2016; 429-454
dc.identifier978-3-319-43414-8
dc.identifierhttp://hdl.handle.net/11336/98278
dc.identifierCONICET Digital
dc.identifierCONICET
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4394988
dc.description.abstractThe middle atmosphere refers to the stratosphere and mesosphere and features dynamics and circulationsthat are fundamentally different from those of the troposphere. The large-scale meridional circulations inthe middle atmosphere operate on seasonal and longer time scales and are largely forced by the breakingof upward propagating waves. The winter stratosphere is dominated by large-scale waves and a polarvortex which confines constituents and which is sometimes punctuated by stratospheric sudden warmings.In contrast, the summer stratosphere is quiescent. Meanwhile, the meridional circulation in themesosphere is mainly driven by the breaking of a broad spectrum of gravity waves that have propagatedupward from the troposphere. These facets of middle atmosphere dynamics have implications for, andpose unique challenges to, data assimilation systems whose models encompass this region of theatmosphere. In this work, we provide an overview of middle atmosphere data assimilation in the contextof the dynamics of this region. The purpose is to demonstrate how the dynamics can be used to explainthe behavior of data assimilation systems in the middle atmosphere, and also to identify challenges inassimilating measurements from this region of the atmosphere. There are two overarching themes.Firstly, we consider the vertical propagation of information through waves, resolved and parameterized,and background error covariances. Secondly, we delve into the dynamical sources of model errors andtechniques for their estimation.
dc.languageeng
dc.publisherSpringer
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/978-3-319-43415-5_19
dc.rightshttps://creativecommons.org/licenses/by-nd/2.5/ar/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceData assimilation for atmospheric, oceanic and hydrologic applications
dc.subjectDATA ASSIMILATION
dc.subjectSTRATOSPHERIC ASSIMILATION
dc.subjectREMOTE SENSING
dc.subjectDYNAMICS
dc.titleStratospheric and mesospheric data assimilation: the role of middle atmospheric dynamics
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typeinfo:eu-repo/semantics/bookPart
dc.typeinfo:ar-repo/semantics/parte de libro


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