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Use of multi-point analysis and modelling to address cross-scale coupling in space plasmas: Lessons from Cluster

dc.contributor.authorDunlop, M.W.
dc.contributor.authorBingham, R.
dc.contributor.authorChapman, S.
dc.contributor.authorEscoubet, P.
dc.contributor.authorZhang, Q.-H.
dc.contributor.authorShen, C.
dc.contributor.authorShi, J.-K.
dc.contributor.authorTrines, R.
dc.contributor.authorWicks, R.
dc.contributor.authorPu, Z.-Y.
dc.contributor.authorDe Keyser, J.
dc.contributor.authorSchwartz, S.
dc.contributor.authorLiu, Z.-X.
dc.date2011
dc.date.accessioned2016-03-29T12:43:51Z
dc.date.available2016-03-29T12:43:51Z
dc.identifier.urihttps://orfeo.belnet.be/handle/internal/3071
dc.descriptionThe properties of plasmas (in space) are fundamentally governed by both 'cross-scale' coupling and comparative temporal behaviour operating over the micro-, meso-, and (MHD-) fluid regimes: for example, under conditions of turbulence, during magnetic reconnection and in shocks and other plasma boundaries. These themes map to a number of related and overlapping, phenomena, where known phenomena play different roles in each theme. Detailed understanding of fundamental plasma processes therefore requires analysis of both theoretical models (to distinguish the collisionless from the collisional regimes) and multi-scale measurements (suitable to address issues of stationarity). In particular, the investigation of phenomena requires analysis techniques which can distinguish and quantify temporal behaviour and the multi-scale spatial behaviour. The analysis of existing, multi-point data sets has led to a number of data co-ordination methods, such as the four spacecraft analysis tools developed for cluster, and we consider examples here. Advanced analysis concepts may be investigated with suitable considerations of measurement quality:adequate sampling of phenomena (for example, to extract the necessary information on the mechanisms operating) requires suitable spacecraft configurations and directly relates to the measurement quality achievable. A particular issue is how to resolve temporal behaviour across the spatial regimes, so that the data set is suitably coordinated. With the addition of theoretical modelling (in the context of particular phenomena) both the space and laboratory plasma regimes may be compared and we give an example of nonlinear wave coupling across spatial scales in this context.
dc.languageeng
dc.titleUse of multi-point analysis and modelling to address cross-scale coupling in space plasmas: Lessons from Cluster
dc.typeArticle
dc.subject.frascatiPhysical sciences
dc.audienceScientific
dc.subject.freeAdvanced analysis
dc.subject.freeAnalysis techniques
dc.subject.freeAnalysis tools
dc.subject.freeCollisionless
dc.subject.freeCross-scale coupling
dc.subject.freeData sets
dc.subject.freeFluid regime
dc.subject.freeLaboratory plasma
dc.subject.freeMagnetic reconnections
dc.subject.freeMeasurement quality
dc.subject.freeMultiscales
dc.subject.freeNonlinear waves
dc.subject.freeNumber of datum
dc.subject.freePlasma boundary
dc.subject.freePlasma process
dc.subject.freePoint data
dc.subject.freeReconnection
dc.subject.freeSpace plasmas
dc.subject.freeSpacecraft configurations
dc.subject.freeSpatial scale
dc.subject.freeStationarity
dc.subject.freeTemporal behaviour
dc.subject.freeTheoretical modelling
dc.subject.freeTheoretical models
dc.subject.freeWave mode coupling
dc.subject.freeCollisional plasmas
dc.subject.freeCollisionless plasmas
dc.subject.freeSpacecraft
dc.subject.freeTurbulence
dc.subject.freeMagnetohydrodynamics
dc.source.titlePlanetary and Space Science
dc.source.volume59
dc.source.issue7
dc.source.page630-638
Orfeo.peerreviewedYes
dc.identifier.doi10.1016/j.pss.2010.06.014
dc.identifier.scopus2-s2.0-79953702276


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