Eddy covariance measurements are instrumental for our understanding of carbon and water cycles. It allows us to examine local conditions at the given site or provide a global picture of the interaction of the terrestrial ecosystems with the overlaying atmosphere through data integration in modeling frameworks. The application of the method is multifaceted, and the data processing consists of multiple steps (i.e. raw data processing, quality control, gap-filling, flux partitioning, aggregation) that are dependent and result in a processing chain. Setting up this processing chain can be daunting, especially for new teams not connected to station networks.
In this workshop, we will provide a brief introductory presentation concerning the eddy covariance post-processing chain (30 mins), show useful resources and software (15 mins), and mainly focus on the independent hands-on training using available commented tutorials or complete processing workflow. The attendees will have a chance to learn how to use openeddy to 1) read and write data with units; 2) remap variable names; 3) merge data and fill gaps in timestamp; 4) plot eddy covariance data; 5) flag and remove spurious measurements and 6) aggregate gap-filled data and evaluate uncertainty. They will also have a chance to learn how to use REddyProc standard post-processing routines for 1) the estimation of the u*-threshold; 2) gap-filling, 3) flux-partitioning, and 4) the derivation of ecosystem properties using the bigleaf R package. The workshop could also be a good opportunity to meet the software developers, ask questions and interact with other colleagues.
Participants should come with a laptop with installed recent versions of R, RStudio, and the openeddy, REddyProc and bigleaf R packages. To work with openeddy tutorials and workflow files, you will also need to download additional data sets (see below).
openeddy package installation: https://github.com/lsigut/openeddy#installation
openeddy tutorials installation: https://github.com/lsigut/openeddy_tutorials#installation
eddy covariance workflow instructions: https://github.com/lsigut/EC_workflow#usage
REddyProc vignettes: https://github.com/bgctw/REddyProc/tree/master/vignettes
bigleaf vignette: https://github.com/cran/bigleaf/blob/master/vignettes/
In this workshop, we will provide a brief introductory presentation concerning the eddy covariance post-processing chain (30 mins), show useful resources and software (15 mins), and mainly focus on the independent hands-on training using available commented tutorials or complete processing workflow. The attendees will have a chance to learn how to use openeddy to 1) read and write data with units; 2) remap variable names; 3) merge data and fill gaps in timestamp; 4) plot eddy covariance data; 5) flag and remove spurious measurements and 6) aggregate gap-filled data and evaluate uncertainty. They will also have a chance to learn how to use REddyProc standard post-processing routines for 1) the estimation of the u*-threshold; 2) gap-filling, 3) flux-partitioning, and 4) the derivation of ecosystem properties using the bigleaf R package. The workshop could also be a good opportunity to meet the software developers, ask questions and interact with other colleagues.
Participants should come with a laptop with installed recent versions of R, RStudio, and the openeddy, REddyProc and bigleaf R packages. To work with openeddy tutorials and workflow files, you will also need to download additional data sets (see below).
openeddy package installation: https://github.com/lsigut/openeddy#installation
openeddy tutorials installation: https://github.com/lsigut/openeddy_tutorials#installation
eddy covariance workflow instructions: https://github.com/lsigut/EC_workflow#usage
REddyProc vignettes: https://github.com/bgctw/REddyProc/tree/master/vignettes
bigleaf vignette: https://github.com/cran/bigleaf/blob/master/vignettes/