https://github.com/noctiluc3nt/reddy
R-Package: A toolbox for analyzing eddy-covariance measurements
https://github.com/noctiluc3nt/reddy
eddy-covariance fluxes land-atmosphere-interactions meteorology r-programming turbulence
Last synced: 4 months ago
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R-Package: A toolbox for analyzing eddy-covariance measurements
- Host: GitHub
- URL: https://github.com/noctiluc3nt/reddy
- Owner: noctiluc3nt
- License: gpl-3.0
- Created: 2023-07-02T20:09:58.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-10-17T08:30:05.000Z (4 months ago)
- Last Synced: 2025-10-17T11:10:05.992Z (4 months ago)
- Topics: eddy-covariance, fluxes, land-atmosphere-interactions, meteorology, r-programming, turbulence
- Language: R
- Homepage: https://noctiluc3nt.github.io/ec_analyze/
- Size: 2.64 MB
- Stars: 5
- Watchers: 1
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Reddy: A toolbox for analyzing eddy-covariance measurements
[](https://noctiluc3nt.github.io/ec_analyze/)
[](https://www.gnu.org/licenses/gpl-3.0)
[](https://github.com/noctiluc3nt/Reddy)
## Installation
The package Reddy can be installed directly from github:
```
devtools::install_git("https://github.com/noctiluc3nt/Reddy")
```
## Documentation, Examples and Usage
The [manual](https://github.com/noctiluc3nt/Reddy/tree/main/inst/manual/Reddy-manual.pdf) describes all functions and the [gitbook](https://noctiluc3nt.github.io/ec_analyze/) provides background information and examples how to execute the core functions of this package. The examples are also provided as [jupyter notebooks](https://github.com/noctiluc3nt/ec_analyze/tree/main/notebooks) (based on [example data](https://github.com/noctiluc3nt/ec_analyze/tree/main/data)).
## Functionality and Scripts
The Reddy package provides functions for the post-processing, analysis and evaluation of eddy-covariance measurements, which are described in the [manual](https://github.com/noctiluc3nt/Reddy/tree/main/inst/manual/Reddy-manual.pdf) and are divided into the following scripts:
- `anisotropy.R`: invariant analysis of the Reynolds stress tensor, calculation of turbulence anisotropy and visualization in a barycentric map
- `auxilliary.R`: collection of some useful generic functions for the evaluation (e.g., discrete binning, cross-correlation maximization)
- `constants.R`: constants used for calculations (internal)
- `diagnostics-meteorology.R`: calculation of "background-meteorology" quantities (e.g., clear-sky index, vapor pressure deficit, unit conversions of moisture variables)
- `diagnostics-turbulence.R`: calculation of some standard turbulence diagnostics (e.g., friction velocity, TKE, turbulence intensity, stability parameter)
- `ec-processing.R`: collection of functions for post-processing and quality control of eddy-covariance measurements
- `ec-processing-routine.R`: an example for a post-processing and quality control routine of eddy-covariance measurements utilizing the functions in `ec-processing.R` with storing the final averaged output data in an external file
- `flux-footprint.R`: calculation and visualization of 2D flux footprint (FFP, Kljun et al., 2015)
- `model-utils.R`: collection of function to post-process NWP model output (e.g. flux deaccumulation, conversion of sigma levels to physical height)
- `multiresolution-decomposition.R`: calculation and visualization of multiresolution decomposition (MRD, Vickers and Mahrt, 2003)
- `ogive.R`: calculation and visualization of ogives, i.e. cumulative distribution functions
- `parameterizations-of-turbulence.R`: collection of functions used to calculated bulk closures, flux-profile and flux-variance relations (e.g. Richardson number, eddy viscosity, eddy conductivity, scaling functions) used in turbulence parameterizations in numerical weather and climate models
- `quadrant-analysis.R`: calculation and visualization of quadrant analysis to study coherent structures and their organization
- `spectrum.R`: calculation and visualization of frequency (temporal) and wavenumber (spatial) spectra, possibility to bin them to compare them with theoretically expected slopes
- `structure-functions.R`: calculation of structure functions and autocorrelation
- `surface-energy-balance.R`: visualization of surface energy balance, residual flux and closure ratio
**Any issues or comments?** Create an issue [here](https://github.com/noctiluc3nt/Reddy/issues).
## Literature
- Foken, T. (2017). Micrometeorology, Springer, Berlin, Heidelberg. DOI: https://doi.org/10.1007/978-3-642-25440-6.
- Kljun, N., Calanca, P., Rotach, M. W., Schmid, H. P. (2015). A simple two-dimensional parameterisation for Flux Footprint
Prediction (FFP), Geoscientific Model Development, 8, 3695-3713. DOI: https://doi.org/10.5194/gmd-8-3695-2015
- Mack, L., Berntsen, T.K., Vercauteren, N., Pirk, N. (2024). Transfer Efficiency and Organization in Turbulent Transport over Alpine Tundra. Boundary-Layer Meteorology 190, 38. DOI: https://doi.org/10.1007/s10546-024-00879-5
- Vickers, D., Mahrt, L. (2003). The Cospectral Gap and Turbulent Flux Calculations. Journal of Atmospheric and Oceanic Technology, 20:660-672. DOI:
[https://doi.org/10.1175/1520-0426(2003)20<660:TCGATF>2.0.CO;2](https://doi.org/10.1175/1520-0426(2003)20<660:TCGATF>2.0.CO;2)