Data and codes used in Peltola et al. "Towards an enhanced metric for detecting vertical flow decoupling in eddy covariance flux observations"

These codes and data can be used to reproduce the results presented in Peltola et al. (2025): "Towards an enhanced metric for detecting vertical flow decoupling in eddy covariance flux observations" submitted to Agricultural and Forest Meteorology.

Codes

Installation

The codes have been run under Windows OS with Python 3.11.6. Install the required Python packages by running 

pip install -r requirements.txt

Usage

Reproducing figures
You can reproduce the figures shown in the manuscript by downloading the data from this Zenodo repository and then by running

python plot_figures.py

Note that the data needs to be located in subfolder `data/`.
Processing data
The data files included in this Zenodo repository can be recreated by downloading data from NEON data portal and ICOS carbon portal, see DOI for each dataset in the manuscript, in addition to NEON PAI data from GBOV website (https://gbov.land.copernicus.eu/dataaccessRM/) and then by running

python process_data.py

Note that `.env` file is needed, there the location of each dataset on the computer should be described.
Example Omega calculation
For calculating Omega decoupling parameter for a few example cases, you can run

python example_omega_calculation.py

Github

The codes can also be found in Github: https://github.com/OPeltola/EC_Omega_filtering

Data

The data from each site are given in site-specific *.csv files. See the metadata in README.txt. Yearly friction velocity thresholds are given in ONEflux subdirectory and the file naming and structure follow ONEflux practises.

NEON data are released under Creative Commons CC0 1.0 “No Rights Reserved” (https://creativecommons.org/publicdomain/zero/1.0/).
ICOS data is licensed under a Creative Commons Attribution 4.0 international licence (https://creativecommons.org/licenses/by/4.0/).