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Recurrence analysis of Eddy covariance fluxes

Title data

Flach, Milan ; Lange, Holger ; Foken, Thomas ; Hauhs, Michael:
Recurrence analysis of Eddy covariance fluxes.
In: Webber Jr., Charles L. ; Ioana, Cornel ; Marwan, Norbert (ed.): Recurrence Plots and Their Quantifications : Expanding Horizons ; Proceedings of the 6th International Symposium on Recurrence Plots, Grenoble, France, 17-19 June 2015. - Cham : Springer , 2016 . - pp. 301-319 . - (Springer Proceedings in Physics ; 180 )
ISBN 978-3-319-29921-1
DOI: https://doi.org/10.1007/978-3-319-29922-8_16

Abstract in another language

The eddy covariance (EC) method is one key method to quantify fluxes in biogeochemical cycles in general, and carbon and energy transport across the vegetation-atmosphere boundary layer in particular. EC data from the worldwide net of flux towers (Fluxnet) have also been used to validate biogeochemical models. The high resolution data are usually obtained at 20 Hz sampling rate but are affected by missing values and other restrictions. In this contribution, we investigate the nonlinear dynamics of EC fluxes using Recurrence Analysis (RA). High resolution data from the site DE-Bay (Waldstein-Weidenbrunnen) and fluxes calculated at half-hourly resolution from eight locations (part of the La Thuile dataset) provide a set of very long time series to analyze. After careful quality assessment and Fluxnet standard gapfilling pretreatment, we calculate properties and indicators of the recurrent structure based both on Recurrence Plots as well as Recurrence Networks. Time series of RA measures obtained from windows moving along the time axis are presented. Their interpretation is guided by three different questions: (1) Is RA able to discern periods where the (atmospheric) conditions are particularly suitable to obtain reliable EC fluxes? (2) Is RA capable to detect dynamical transitions (different behavior) beyond those obvious from visual inspection? (3) Does RA contribute to an understanding of the nonlinear synchronization between EC fluxes and atmospheric parameters, which is crucial for both improving carbon flux models as well for reliable interpolation of gaps? (4) Is RA able to recommend an optimal time resolution for measuring EC data and for analyzing EC fluxes? (5) Is it possible to detect non-trivial periodicities with a global RA? We will demonstrate that the answers to all five questions is affirmative, and that RA provides insights into EC dynamics not easily obtained otherwise.

Further data

Item Type: Article in a book
Refereed: No
Additional notes: BAYCEER133234
Institutions of the University: Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Chair Ecological Modelling
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Chair Ecological Modelling > Chair Ecological Modelling - Univ.-Prof. Dr. Michael Hauhs
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Professorship Micrometeorology
Research Institutions
Research Institutions > Research Centres
Research Institutions > Research Centres > Bayreuth Center of Ecology and Environmental Research- BayCEER
Faculties
Faculties > Faculty of Biology, Chemistry and Earth Sciences
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences
Result of work at the UBT: Yes
DDC Subjects: 500 Science
Date Deposited: 10 Aug 2016 09:43
Last Modified: 04 Mar 2019 11:22
URI: https://eref.uni-bayreuth.de/id/eprint/33877