Reddy: A toolbox for analyzing eddy-covariance measurements

Installation

The package Reddy can be installed directly from github:

    devtools::install_git("https://github.com/noctiluc3nt/Reddy")

Documentation, Examples and Usage

The manual describes all functions and the gitbook provides background information and examples how to execute the core functions of this package. The examples are also provided as jupyter notebooks (based on example 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 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)
• bulk_closures.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)
• constants.R: constants used for calculations (internal)
• diagnostics-meteorology.R: calculation of "background-meteorology" quantities (e.g., clear-sky index)
• 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
• 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)
• 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
• surface-energy-balance.R: visualization of surface energy balance, residual flux and closure ratio

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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