Post-process eddy covariance data with ease using R packages openeddy, REddyProc and bigleaf (onsite only)
Convener:
Ladislav Šigut
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Co-conveners:
Khue Vu Hoang Ngoc,
Georg Jocher,
Jürgen Knauer,
Natalia Kowalska
Wed, 30 Apr, 14:00–15:45 (CEST) Room 0.55
Wed, 14:00
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/
REddyProc materials from EGU19 Short Course: https://github.com/bgctw/EGU19EddyCourse