25 research outputs found
Basic and extensible post-processing of eddy covariance flux data with REddyProc
With the eddy covariance (EC) technique, net fluxes of carbon dioxide
(CO2) and other trace gases as well as water and energy fluxes can be
measured at the ecosystem level. These flux measurements are a main source
for understanding biosphere–atmosphere interactions and feedbacks through
cross-site analysis, model–data integration, and upscaling. The raw fluxes
measured with the EC technique require extensive and laborious data
processing. While there are standard
tools1 available in an open-source environment for
processing high-frequency (10 or 20 Hz) data into half-hourly
quality-checked fluxes, there is a need for more usable and extensible tools
for the subsequent post-processing steps. We tackled this need by developing
the REddyProc package in the cross-platform language R that provides
standard CO2-focused post-processing routines for reading
(half-)hourly data from different formats, estimating the u*
threshold, as well as gap-filling, flux-partitioning, and visualizing the
results. In addition to basic processing, the functions are extensible
and allow easier integration in extended analysis than current tools. New
features include cross-year processing and a better treatment of
uncertainties. A comparison of REddyProc routines with other
state-of-the-art tools resulted in no significant differences in monthly and
annual fluxes across sites. Lower uncertainty estimates of both u* and
resulting gap-filled fluxes by 50 % with the presented tool were achieved
by an improved treatment of seasons during the bootstrap analysis. Higher
estimates of uncertainty in daytime partitioning (about twice as high)
resulted from a better accounting for the uncertainty in estimates of
temperature sensitivity of respiration. The provided routines can be easily
installed, configured, and used. Hence, the eddy covariance community will
benefit from the REddyProc package, allowing easier integration of
standard post-processing with extended analysis.
1http://fluxnet.fluxdata.org/2017/10/10/toolbox-a-rolling-list-of-softwarepackages-for-flux-related-data-processing/,
last access: 17 August 2018</p
ECOSTRESS: NASA's next generation mission to measure evapotranspiration from the International Space Station
The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station ECOSTRESS) was launched to the International Space Station on June 29, 2018. The primary science focus of ECOSTRESS is centered on evapotranspiration (ET), which is produced as level‐3 (L3) latent heat flux (LE) data products. These data are generated from the level‐2 land surface temperature and emissivity product (L2_LSTE), in conjunction with ancillary surface and atmospheric data. Here, we provide the first validation (Stage 1, preliminary) of the global ECOSTRESS clear‐sky ET product (L3_ET_PT‐JPL, version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against the site measurements (clear‐sky instantaneous/time of overpass: r2 = 0.88; overall bias = 8%; normalized RMSE = 6%). ET uncertainty was generally consistent across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), though temperate sites are over‐represented. The 70 m high spatial resolution of ECOSTRESS improved correlations by 85%, and RMSE by 62%, relative to 1 km pixels. This paper serves as a reference for the ECOSTRESS L3 ET accuracy and Stage 1 validation status for subsequent science that follows using these data
Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data
The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions
The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.
The FLUXNET2015 dataset provides ecosystem-scale data on CO2, 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
Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data
The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data
The FLUXNET2015 dataset provides ecosystem-scale data on CO2, 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.Peer reviewe
Eddy covariance raw data processing for CO2 and energy fluxes calculation at ICOS ecosystem stations
Eddy covariance raw data processing for CO2 and energy fluxes calculation at ICOS ecosystem stations
The eddy covariance is a powerful technique to
estimate the surface-atmosphere exchange of different scalars
at the ecosystem scale. The EC method is central to the ecosys tem component of the Integrated Carbon Observation System,
a monitoring network for greenhouse gases across the European
Continent. The data processing sequence applied to the collected
raw data is complex, and multiple robust options for the differ ent steps are often available. For Integrated Carbon Observation
System and similar networks, the standardisation of methods is
essential to avoid methodological biases and improve compara bility of the results. We introduce here the steps of the processing
chain applied to the eddy covariance data of Integrated Carbon
Observation System stations for the estimation of final CO2, water
and energy fluxes, including the calculation of their uncertain ties. The selected methods are discussed against valid alternative
options in terms of suitability and respective drawbacks and
advantages. The main challenge is to warrant standardised pro cessing for all stations in spite of the large differences in e.g.
ecosystem traits and site conditions. The main achievement of
the Integrated Carbon Observation System eddy covariance data
processing is making CO2 and energy flux results as comparable
and reliable as possible, given the current micrometeorological
understanding and the generally accepted state-of-the-art process ing metho
Uncovering the critical soil moisture thresholds of plant water stress for European ecosystems
Leaf-level coordination principles propagate to the ecosystem scale
Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories – the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis – are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections