RFlux-package: Eddy Covariance Flux Data Processing

In domvit81/RFlux: Eddy Covariance Flux Data Processing

Description

An R graphical user interface for processing eddy covariance raw data and release high quality fluxes of the main GHGs exchanged by ecosystems and agricultural fields. Fluxes are estimated through a call to the open source EddyPro software (registered trademark, LI-COR, Biosciences, 2019). 'RFlux' provides tools for the metadata management as well as for the implementation of the robust data cleaning procedure described by Vitale et al (2019) <doi:10.5194/bg-2019-270>.

Details

RFlux package ingests eddy covariance rawdata sampled by either open- or closed-path system and implement the processing pipeline adopted by the ICOS-ETC (Integrated Carbon Observation System European Research Infrastructure - Ecosystem Thematic Center, http://www.icos-etc.eu/icos/). All metadata information have to be reported in the filename_ecmd.csv table. Such information are then processed by the get_md function.

The processing of rawdata aims at

i

estimating fluxes and other micrometeorolgical parameters.

ii

performing data quality control.

Flux estimation involves the following options/methods:

• Planar fit for tilt correction (Wilczak et al, 2001).

• Maximum cross-covariance method for time lag determination (see Rebmann et al, 2012).

• Block average (see Moncrieff et al, 2004).

• WPL correction, only for open path systems (Webb et al, 1980).

• In-situ spectral corrections (Fratini et al, 2012).

The open source EddyPro software (registered trademark, LI-COR Biosciences, 2019) is used to this aim employing also the estimation of micrometeorological parameters useful in subsequent analyses. It is required the EddyPro software is installed on your system (for download see www.licor.com/EddyPro).

Quality control involves the data cleaning procedure described in Vitale et al (2019). Its implementation involves a three-step procedure

Step 1:

Estimation of the test statistics via the qcStat function.

Step 2:

Generating the workset via the ecworkset function.

Step 3:

Application of data cleaning procedure (including despiking) via the cleanFlux function.

Acknowledgements. Rflux has been developed in the context of the ICOS Ecosystem Thematic Centre. DV thanks the ENVRIPLUS H2020 European project (Grant Agreement 654182) for the support. DP thanks the ENVRIFAIR H2020 European project (Grant Agreement 824068) for the support.

Author(s)

Domenico Vitale [aut, cre], Dario Papale [com, ctb]

Maintainer: Domenico Vitale <[e-mail]>

References

Fratini, G., Mauder, M. (2014). Towards a consistent eddy-covariance processing: an intercomparison of EddyPro and TK3. Atmospheric Measurement Techniques, 7(7), 2273-2281, doi: https://doi.org/10.5194/amt-7-2273-2014.

Fratini, G., Ibrom, A., Arriga, N., Burba, G., Papale, D. (2012). Relative humidity effects on water vapour fluxes measured with closed-path eddy-covariance systems with short sampling lines. Agricultural and forest meteorology, 165, pp 53-63, doi: https://doi.org/10.1016/j.agrformet.2012.05.018.

LI-COR Biosciences: EddyPro 7.0.4: Help and User's Guide, LI-COR Biosciences, Lincoln, Nebraska USA, www.licor.com/EddyPro, 2019.

Moncrieff, J., Clement, R., Finnigan, J., Meyers, T. (2004). Averaging, detrending, and filtering of eddy covariance time series. In Handbook of micrometeorology, pp. 7-31, Springer, Dordrecht, doi: https://doi.org/10.1007/1-4020-2265-4_2.

Rebmann, C., Kolle, O., Heinesch, B., Queck, R., Ibrom, A., Aubinet, M. (2012). Data acquisition and flux calculations. In Eddy covariance, pp. 59-83, Springer, Dordrecht.

Vitale, D. Fratini, G. Bilancia, M. Nicolini, G. Sabbatini, S. Papale, D. (2019). A robust data cleaning procedure for eddy covariance flux measurements, Biogeosciences Discussions, pp 1-36, doi: https://doi.org/10.5194/bg-2019-270.

Webb, E.K., Pearman, G.I., Leuning, R. (1980). Correction of flux measurements for density effects due to heat and water vapour transfer. Quarterly Journal of the Royal Meteorological Society, 106(447), pp 85-100, doi: https://doi.org/10.1002/qj.49710644707.

Wilczak, J.M., Oncley, S.P., Stage, S.A. (2001). Sonic anemometer tilt correction algorithms. Boundary-Layer Meteorology, 99(1), pp 127-150, doi: https://doi.org/10.1023/A:1018966204465.

domvit81/RFlux documentation built on Nov. 20, 2019, 8:02 a.m.