Articles | Volume 10, issue 9
Geosci. Model Dev., 10, 3189–3206, 2017
https://doi.org/10.5194/gmd-10-3189-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 10, 3189–3206, 2017
https://doi.org/10.5194/gmd-10-3189-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper 31 Aug 2017
Model description paper | 31 Aug 2017
eddy4R 0.2.0: a DevOps model for community-extensible processing and analysis of eddy-covariance data based on R, Git, Docker, and HDF5
Stefan Metzger et al.
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Cited
22 citations as recorded by crossref.
- Basic and extensible post-processing of eddy covariance flux data with REddyProc T. Wutzler et al. 10.5194/bg-15-5015-2018
- The AmeriFlux network: A coalition of the willing K. Novick et al. 10.1016/j.agrformet.2017.10.009
- An Ecosystem-Scale Flux Measurement Strategy to Assess Natural Climate Solutions K. Hemes et al. 10.1021/acs.est.0c06421
- Surface-atmosphere exchange in a box: Making the control volume a suitable representation for in-situ observations S. Metzger 10.1016/j.agrformet.2017.08.037
- Remote sensing northern lake methane ebullition M. Engram et al. 10.1038/s41558-020-0762-8
- An Open‐Source Python Library for Varying Model Parameters and Automating Concurrent Simulations of the National Water Model A. Raney et al. 10.1111/1752-1688.12973
- Bigleaf—An R package for the calculation of physical and physiological ecosystem properties from eddy covariance data J. Knauer et al. 10.1371/journal.pone.0201114
- The Terrestrial Carbon Sink T. Keenan & C. Williams 10.1146/annurev-environ-102017-030204
- Generating Spatially Robust Carbon Budgets From Flux Tower Observations A. Griebel et al. 10.1029/2019GL085942
- Surface–atmosphere fluxes of volatile organic compounds in Beijing W. Acton et al. 10.5194/acp-20-15101-2020
- InnFLUX – an open-source code for conventional and disjunct eddy covariance analysis of trace gas measurements: an urban test case M. Striednig et al. 10.5194/amt-13-1447-2020
- Measurements of traffic-dominated pollutant emissions in a Chinese megacity F. Squires et al. 10.5194/acp-20-8737-2020
- Toward understanding the contribution of waterbodies to the methane emissions of a permafrost landscape on a regional scale—A case study from the Mackenzie Delta, Canada K. Kohnert et al. 10.1111/gcb.14289
- Ozone deposition to a coastal sea: comparison of eddy covariance observations with reactive air–sea exchange models D. Loades et al. 10.5194/amt-13-6915-2020
- From NEON Field Sites to Data Portal: A Community Resource for Surface–Atmosphere Research Comes Online S. Metzger et al. 10.1175/BAMS-D-17-0307.1
- A robust data cleaning procedure for eddy covariance flux measurements D. Vitale et al. 10.5194/bg-17-1367-2020
- Calibration Strategies for Detecting Macroscale Patterns in NEON Atmospheric Carbon Isotope Observations R. Fiorella et al. 10.1029/2020JG005862
- Surface-atmosphere exchange in a box: Space-time resolved storage and net vertical fluxes from tower-based eddy covariance K. Xu et al. 10.1016/j.agrformet.2017.10.011
- The eddy-covariance storage term in air: Consistent community resources improve flux measurement reliability K. Xu et al. 10.1016/j.agrformet.2019.107734
- Geospatial coherence of surface-atmosphere fluxes in the upper Great Lakes region J. Poe et al. 10.1016/j.agrformet.2020.108188
- Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions A. Serafimovich et al. 10.5194/acp-18-10007-2018
- Can Data Mining Help Eddy Covariance See the Landscape? A Large-Eddy Simulation Study K. Xu et al. 10.1007/s10546-020-00513-0
22 citations as recorded by crossref.
- Basic and extensible post-processing of eddy covariance flux data with REddyProc T. Wutzler et al. 10.5194/bg-15-5015-2018
- The AmeriFlux network: A coalition of the willing K. Novick et al. 10.1016/j.agrformet.2017.10.009
- An Ecosystem-Scale Flux Measurement Strategy to Assess Natural Climate Solutions K. Hemes et al. 10.1021/acs.est.0c06421
- Surface-atmosphere exchange in a box: Making the control volume a suitable representation for in-situ observations S. Metzger 10.1016/j.agrformet.2017.08.037
- Remote sensing northern lake methane ebullition M. Engram et al. 10.1038/s41558-020-0762-8
- An Open‐Source Python Library for Varying Model Parameters and Automating Concurrent Simulations of the National Water Model A. Raney et al. 10.1111/1752-1688.12973
- Bigleaf—An R package for the calculation of physical and physiological ecosystem properties from eddy covariance data J. Knauer et al. 10.1371/journal.pone.0201114
- The Terrestrial Carbon Sink T. Keenan & C. Williams 10.1146/annurev-environ-102017-030204
- Generating Spatially Robust Carbon Budgets From Flux Tower Observations A. Griebel et al. 10.1029/2019GL085942
- Surface–atmosphere fluxes of volatile organic compounds in Beijing W. Acton et al. 10.5194/acp-20-15101-2020
- InnFLUX – an open-source code for conventional and disjunct eddy covariance analysis of trace gas measurements: an urban test case M. Striednig et al. 10.5194/amt-13-1447-2020
- Measurements of traffic-dominated pollutant emissions in a Chinese megacity F. Squires et al. 10.5194/acp-20-8737-2020
- Toward understanding the contribution of waterbodies to the methane emissions of a permafrost landscape on a regional scale—A case study from the Mackenzie Delta, Canada K. Kohnert et al. 10.1111/gcb.14289
- Ozone deposition to a coastal sea: comparison of eddy covariance observations with reactive air–sea exchange models D. Loades et al. 10.5194/amt-13-6915-2020
- From NEON Field Sites to Data Portal: A Community Resource for Surface–Atmosphere Research Comes Online S. Metzger et al. 10.1175/BAMS-D-17-0307.1
- A robust data cleaning procedure for eddy covariance flux measurements D. Vitale et al. 10.5194/bg-17-1367-2020
- Calibration Strategies for Detecting Macroscale Patterns in NEON Atmospheric Carbon Isotope Observations R. Fiorella et al. 10.1029/2020JG005862
- Surface-atmosphere exchange in a box: Space-time resolved storage and net vertical fluxes from tower-based eddy covariance K. Xu et al. 10.1016/j.agrformet.2017.10.011
- The eddy-covariance storage term in air: Consistent community resources improve flux measurement reliability K. Xu et al. 10.1016/j.agrformet.2019.107734
- Geospatial coherence of surface-atmosphere fluxes in the upper Great Lakes region J. Poe et al. 10.1016/j.agrformet.2020.108188
- Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions A. Serafimovich et al. 10.5194/acp-18-10007-2018
- Can Data Mining Help Eddy Covariance See the Landscape? A Large-Eddy Simulation Study K. Xu et al. 10.1007/s10546-020-00513-0
Discussed (final revised paper)
Latest update: 17 Jan 2022
Short summary
We apply the
development and systems operationssoftware development model to create the eddy4R–Docker open-source, flexible, and modular eddy-covariance data processing environment. Test applications to aircraft and tower data, as well as a software cross validation demonstrate its efficiency and consistency. Key improvements in accessibility, extensibility, and reproducibility build the foundation for deploying complex scientific algorithms in an effective and scalable manner.
We apply the
development and systems operationssoftware development model to create the...
