The following software and packages are generally designed for data acquisition and processing raw (high frequency) flux data. While sharing the common feature of flux calculation, they vary in terms of the extended features provided (e.g., QA/QC, footprint analysis)
- Obtain through direct contact with the authors (Kolle, O. and Rebmann, C.)
- Allows acquisition, visualization, and processing of eddy covariance data
- Tech report: https://repository.publisso.de/resource/frl:4414276-1/data
- OS: Windows
- It computes fluxes of water vapor (evapotranspiration), carbon dioxide, methane, other trace gases, and energy with the eddy covariance method, including footprint models and other features.
- OS: Windows, Mac, and Linux. (While executables are only for Win and Mac, both the engine and the GUI can be compiled from source code (openly available) and used under any Linux distribution)
- It computes fluxes of water vapor (evapotranspiration), carbon dioxide, methane, other trace gases, and energy with the eddy covariance method, including extended quality assurance tools and other features.
- OS: Windows, Linux
- The software is a MATLAB-based program with a graphical user interface. It processes data obtained from various sonic anemometer and gas analyzer combinations and from various measurement sites. The software can process CO2, H2O, temperature, O3, CH4, N2O, and particle high-frequency data.
- OS: Windows, Mac, Linux.
- EdiRe is a fast, flexible, and user-friendly software tool for micrometeorologists with a focus on eddy covariance and micrometeorological measurement analyses. EdiRe is adaptable to most eddy covariance raw data formats and can incorporate microclimate data. In addition, the graphical user interface simplifies the development of processing routines and allows rapid redesign of routines to enhance the question/answer cycle of data analysis.
- OS: Windows.
- The first eddy-covariance flux processor building on the open-source, reproducible, and community-extensible DevOps software development model. Amongst others, it produces NEON’s first EC data, and provides an environment for advanced end-to-end analytics and modeling for EC flux and rich contextual data (e.g., Metzger et al., 2013; Vaughan et al., 2016; Xu et al, 2017).
- R software-based – OS: Windows, Mac, and Linux.
- Encompasses eddy-covariance calculation scheme, a fork of the well-known EC-PACK and quality control and assessment (QC/QA) scheme developed in the German TERENO project.
- Process eddy covariance and disjunct eddy covariance flux data written in Matlab. It can be easily configured to process high-frequency, low-frequency, and disjunct data.
- It can be applied to a wide range of analytical setups for NMVOC and other trace gas measurements and is tailored towards the application of noisy data, where lag time corrections become challenging. Several corrections and quality control routines are implemented to obtain reliable results.
- Reference: https://amt.copernicus.org/articles/13/1447/2020/
- To download test data: click HERE [https://www.atm-phys-chem.at/wp-content/innfluxdata/innfluxdata_corrected.zip] (zip file is 5Gb large – so the download can take some time)
- An R graphical user interface for processing eddy covariance raw data and releasing 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, 2021). ‘RFlux’ provides tools for metadata management as well as for the implementation of the robust data cleaning procedure described by Vitale et al. (2020, https://doi.org/10.5194/bg-17-1367-2020).
- Python 3 module for partitioning water vapor and carbon dioxide fluxes.
- Implements the Scanlon and Sahu (2008) procedure for partitioning eddy covariance measurements of water vapor and carbon dioxide fluxes into stomatal (transpiration, photosynthesis) and nonstomatal (evaporation, respiration) components.
- Includes capabilities for applying basic QA/QC to high-frequency eddy covariance data, for correcting high-frequency data for external fluctuations associated with air temperature and vapor density, and for estimating leaf-level water use efficiency.
- The module was recently described in Agricultural and Forest Meteorology (https://doi.org/10.1016/j.agrformet.2018.02.019).
- Python package designed to work efficiently with micrometeorological datasets. It aims to improve productivity (by allowing us to focus more on micrometeorology) while still being flexible enough to program project-specific things.
- The functionalities include QA/QC, double rotation, detrending, correction of sensor drift, spectra/cross-spectra, WPL correction, and common constants generally used in atmospheric sciences.
The list was initially compiled by Ladislav Šigut and Housen Chu and has been updated with inputs from the communities. We thank all the original software/package developers for sharing and maintaining such great services. For details of each software/package, please refer to the developing team through the external links. Please contact the website manager (email@example.com) if you would like to propose any addition or update to the list.