Articles | Volume 10, issue 9
Geosci. Model Dev., 10, 3189–3206, 2017
Geosci. Model Dev., 10, 3189–3206, 2017

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.

Related authors

Eddy Covariance Measurements Highlight Sources of Nitrogen Oxide Emissions Missing from Inventories for Central London
Will S. Drysdale, Adam R. Vaughan, Freya A. Squires, Sam J. Cliff, Stefan Metzger, David Durden, Natchaya Pingintha-Durden, Carole Helfter, Eiko Nemitz, C. Sue B. Grimmond, Janet Barlow, Sean Beevers, Gregor Stewart, David Dajnak, Ruth M. Purvis, and James D. Lee
Atmos. Chem. Phys. Discuss.,,, 2022
Preprint under review for ACP
Short summary
Novel approach to observing system simulation experiments improves information gain of surface–atmosphere field measurements
Stefan Metzger, David Durden, Sreenath Paleri, Matthias Sühring, Brian J. Butterworth, Christopher Florian, Matthias Mauder, David M. Plummer, Luise Wanner, Ke Xu, and Ankur R. Desai
Atmos. Meas. Tech., 14, 6929–6954,,, 2021
Short summary
Spatially and temporally resolved measurements of NOx fluxes by airborne eddy covariance over Greater London
Adam R. Vaughan, James D. Lee, Stefan Metzger, David Durden, Alastair C. Lewis, Marvin D. Shaw, Will S. Drysdale, Ruth M. Purvis, Brian Davison, and C. Nicholas Hewitt
Atmos. Chem. Phys., 21, 15283–15298,,, 2021
Short summary
Ozone deposition to a coastal sea: comparison of eddy covariance observations with reactive air–sea exchange models
David C. Loades, Mingxi Yang, Thomas G. Bell, Adam R. Vaughan, Ryan J. Pound, Stefan Metzger, James D. Lee, and Lucy J. Carpenter
Atmos. Meas. Tech., 13, 6915–6931,,, 2020
Short summary
Surface–atmosphere fluxes of volatile organic compounds in Beijing
W. Joe F. Acton, Zhonghui Huang, Brian Davison, Will S. Drysdale, Pingqing Fu, Michael Hollaway, Ben Langford, James Lee, Yanhui Liu, Stefan Metzger, Neil Mullinger, Eiko Nemitz, Claire E. Reeves, Freya A. Squires, Adam R. Vaughan, Xinming Wang, Zhaoyi Wang, Oliver Wild, Qiang Zhang, Yanli Zhang, and C. Nicholas Hewitt
Atmos. Chem. Phys., 20, 15101–15125,,, 2020
Short summary

Related subject area

Atmospheric sciences
Development of aerosol optical properties for improving the MESSy photolysis module in the GEM-MACH v2.4 air quality model and application for calculating photolysis rates in a biomass burning plume
Mahtab Majdzadeh, Craig A. Stroud, Christopher Sioris, Paul A. Makar, Ayodeji Akingunola, Chris McLinden, Xiaoyi Zhao, Michael D. Moran, Ihab Abboud, and Jack Chen
Geosci. Model Dev., 15, 219–249,,, 2022
Short summary
The sensitivity of simulated aerosol climatic impact to domain size using regional model (WRF-Chem v3.6)
Xiaodong Wang, Chun Zhao, Mingyue Xu, Qiuyan Du, Jianqiu Zheng, Yun Bi, Shengfu Lin, and Yali Luo
Geosci. Model Dev., 15, 199–218,,, 2022
Short summary
WOMBAT v1.0: a fully Bayesian global flux-inversion framework
Andrew Zammit-Mangion, Michael Bertolacci, Jenny Fisher, Ann Stavert, Matthew Rigby, Yi Cao, and Noel Cressie
Geosci. Model Dev., 15, 45–73,,, 2022
Short summary
Analysis of the MODIS above-cloud aerosol retrieval algorithm using MCARS
Galina Wind, Arlindo M. da Silva, Kerry G. Meyer, Steven Platnick, and Peter M. Norris
Geosci. Model Dev., 15, 1–14,,, 2022
Short summary
How well can inverse analyses of high-resolution satellite data resolve heterogeneous methane fluxes? Observing system simulation experiments with the GEOS-Chem adjoint model (v35)
Xueying Yu, Dylan B. Millet, and Daven K. Henze
Geosci. Model Dev., 14, 7775–7793,,, 2021
Short summary

Cited articles

Ammann, C., Brunner, A., Spirig, C., and Neftel, A.: Technical note: Water vapour concentration and flux measurements with PTR-MS, Atmos. Chem. Phys., 6, 4643–4651,, 2006.
Aubinet, M., Vesala, T., and Papale, D. (Eds.): Eddy covariance: A practical guide to measurement and data analysis, Springer, Dordrecht, Heidelberg, London, New York, 438 pp., 2012.
Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S., Anthoni, P., Bernhofer, C., Davis, K., Evans, R., Fuentes, J., Goldstein, A., Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, W., Oechel, W. U. K., Pilegaard, K., Schmid, H., Valentini, R., Verma, S., Vesala, T., Wilson, K., and Wofsy, S.: FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities, B. Am. Meteorol. Soc., 82, 2415–2434,<2415:FANTTS>2.3.CO;2, 2001.
Billesbach, D. P.: Estimating uncertainties in individual eddy covariance flux measurements: A comparison of methods and a proposed new method, Agr. Forest. Meteorol., 151, 394–405,, 2011.
Boettiger, C.: An introduction to Docker for reproducible research, with examples from the R environment, Operat. Syst. Rev., 49, 71–79,, 2015.
Short summary
We apply the development and systems operations software 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.