The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

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<p>Standardized processing of eddy covariance data is important for studies combining data from multiple sites, for validating remote sensing measurements as well as runs of ecosystem and climate models, and for applications relying on these flux data to create derived products like upscaled fluxes, among other examples. However, maintaining consistency within the software used for this processing while allowing for evolution of this code across research networks presents novel challenges in software development. The introduction of the ONEFlux (Open Network-Enabled Flux) eddy covariance data processing pipeline, originally developed within a collaboration of the AmeriFlux Management Project, the European Fluxes Database, and the ICOS Ecosystem Thematic Centre, supported the creation of consistently processed global eddy covariance data products. In particular, ONEFlux codes were used to generate the FLUXNET2015 dataset, which is widely adopted by thousands of eddy covariance data users in their work in research, ranging from soil microbiology to large scale drought effects, and also education, from basic plant biology all the way to global climate change. We are now more thoroughly instrumenting the code, and the code development process, to better address these challenges, efforts which we will describe in this presentation. In particular, we are seeking to improve software development practices to allow for more streamlined collaboration on expanding and contributing to the codebase. For instance, we are adopting planned release cycles for code updates, designing more detailed ways to incorporate and evaluate new modules, introducing data-centric testing and continuous integration, improving code performance, and adopting several other software engineering best practices more widely in the development workflows. The main goal of these changes is to lower the barriers for running ONEFlux by regional networks processing their data, while at the same time better supporting contributions from the community into the codebase. This will be critical to continue the current use of ONEFlux to generate updated versions of flux datasets by regional networks, the components of new global products.</p>

<p>The eddy covariance is a micrometeorological technique which allows for the estimation of the net fluxes of gases and energy between the atmosphere and an ecosystem. To estimate the net balance, the required input data are high frequency measurements (e.g. 10 or 20 Hz) of wind speed and gas concentration or amount of energy, plus lower frequency measurements (e.g. 1s to 30min ) of some meteorological variables and gas concentration vertical gradients below the measuring point. From these measurements, through a set of processing algorithms and corrections, continuous time series of fluxes are obtained which can be used to, e.g.,  estimate the net ecosystem exchange, as input/validation for modelling purposes, or for eco-physiological analyses. Although the fundamental processing steps and corrections are well established, there is still a discrete margin of subjectivity in the choice of specific operations and corrections which leads to different results even starting from the same set of measured data. The ICOS Ecosystem infrastructure consists of a network of eddy covariance stations equipped with high-level standardized instrumentation, whose data are processed centrally by means of a fully standardized and documented processing pipeline. This allows to obtain robust and consistent datasets, along with sets of metadata (e.g. instruments characteristics and location) and ancillary variables (e.g. meteorological and biometric) that help their interpretation and ensure their traceability and reproducibility. The description of the full processing pipeline is the aim of this contribution. All the data and metadata produced by the ICOS Ecosystem Thematic Centre (ETC) are freely available through the ICOS Carbon Portal as well as the processing codes are available in the ICOS ETC GitHub repository.</p>