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Local finite-time Lyapunov exponent, local sampling and probabilistic source and destination regions

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dc.contributor.authorBozorgMagham, Amir E.en
dc.contributor.authorRoss, Shane D.en
dc.contributor.authorSchmale, David G. IIIen
dc.contributor.departmentSchool of Plant and Environmental Sciencesen
dc.date.accessioned2019-06-11T15:30:00Zen
dc.date.available2019-06-11T15:30:00Zen
dc.date.issued2015en
dc.description.abstractThe finite-time Lyapunov exponent (FTLE) is a powerful Lagrangian concept widely used for describing large-scale flow patterns and transport phenomena. However, field experiments usually have modest scales. Therefore, it is necessary to bridge the gap between the concept of FTLE and field experiments. In this paper, two independent observations are discussed: (i) approximation of the local FTLE time series at a fixed location as a function of known distances between the destination (or source) points of released (or collected) particles and local velocity, and (ii) estimation of the distances between the destination (or source) points of the released (or collected) particles when consecutive release (or sampling) events are performed at a fixed location. These two observations lay the groundwork for an ansatz methodology that can practically assist in field experiments where consecutive samples are collected at a fixed location, and it is desirable to attribute source locations to the collected particles, and also in planning of optimal local sampling of passive particles for maximal diversity monitoring of atmospheric assemblages of microorganisms. In addition to deterministic flows, the more realistic case of unresolved turbulence and low-resolution flow data that yield probabilistic source (or destination) regions are studied. It is shown that, similar to deterministic flows, Lagrangian coherent structures (LCS) and local FTLE can describe the separation of probabilistic source (or destination) regions corresponding to consecutively collected (or released) particles.en
dc.description.sponsorshipThis material is based upon work supported by the National Science Foundation under grant numbers CMMI- 1100263 (Dynamical Mechanisms Influencing the Population Structure of Airborne Pathogens: Theory and Observations) and CMMI-1150456 (Integrating Geometric, Probabilistic, and Topological Methods for Phase Space Transport in Dynamical Systems). Part of this research was performed during a visit by S. D. Ross to the Instituto de Ciencias Matemáticas, Madrid, Spain. He thanks ICMAT for its hospitality and support from MINECO ICMAT Severo Ochoa project SEV-2011-0087.en
dc.format.extent15 pagesen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.5194/npgd-2-903-2015en
dc.identifier.urihttp://hdl.handle.net/10919/89924en
dc.identifier.volume22en
dc.language.isoenen
dc.publisherEuropean Geosciences Unionen
dc.rightsCreative Commons Attribution 3.0 United Statesen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/en
dc.titleLocal finite-time Lyapunov exponent, local sampling and probabilistic source and destination regionsen
dc.title.serialNonlinear Processes in Geophysicsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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