Articles | Volume 17, issue 6
https://doi.org/10.5194/bg-17-1367-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-17-1367-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A robust data cleaning procedure for eddy covariance flux measurements
Domenico Vitale
CORRESPONDING AUTHOR
Department for Innovation in Biological, Agro-Food and Forest Systems (DIBAF), University of Tuscia, via San Camillo de Lellis, 01100 Viterbo, Italy
Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), 01100 Viterbo, Italy
Gerardo Fratini
LI-COR Biosciences Inc., Lincoln, Nebraska 68504, USA
Massimo Bilancia
Ionian Department of Law, Economics and Environment, University of Bari Aldo Moro, Via Lago Maggiore angolo Via Ancona, 74121 Taranto, Italy
Giacomo Nicolini
Department for Innovation in Biological, Agro-Food and Forest Systems (DIBAF), University of Tuscia, via San Camillo de Lellis, 01100 Viterbo, Italy
Simone Sabbatini
Department for Innovation in Biological, Agro-Food and Forest Systems (DIBAF), University of Tuscia, via San Camillo de Lellis, 01100 Viterbo, Italy
Dario Papale
Department for Innovation in Biological, Agro-Food and Forest Systems (DIBAF), University of Tuscia, via San Camillo de Lellis, 01100 Viterbo, Italy
Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), 01100 Viterbo, Italy
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17 citations as recorded by crossref.
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- Utility of Copernicus-Based Inputs for Actual Evapotranspiration Modeling in Support of Sustainable Water Use in Agriculture R. Guzinski et al. 10.1109/JSTARS.2021.3122573
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- A gap filling method for daily evapotranspiration of global flux data sets based on deep learning L. Qian et al. 10.1016/j.jhydrol.2024.131787
- Technical note: Flagging inconsistencies in flux tower data M. Jung et al. 10.5194/bg-21-1827-2024
- Global transpiration data from sap flow measurements: the SAPFLUXNET database R. Poyatos et al. 10.5194/essd-13-2607-2021
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- System for automated Quality Control (SaQC) to enable traceable and reproducible data streams in environmental science L. Schmidt et al. 10.1016/j.envsoft.2023.105809
- Research on Oil Well Data Cleaning System Y. Feng & L. Zhao 10.2478/ijanmc-2022-0026
- El Niño-Southern Oscillation forcing on carbon and water cycling in a Bornean tropical rainforest N. Takamura et al. 10.1073/pnas.2301596120
- Quantitative Evaluation of Wavelet Analysis Method for Turbulent Flux Calculation of Non‐Stationary Series Y. Li et al. 10.1029/2022GL101591
17 citations as recorded by crossref.
- UAV-based in situ measurements of CO2 and CH4 fluxes over complex natural ecosystems A. Bolek et al. 10.5194/amt-17-5619-2024
- Biotic and Abiotic Control Over Diurnal CH4 Fluxes in a Temperate Transitional Poor Fen Ecosystem A. Lhosmot et al. 10.1007/s10021-022-00809-x
- A physical full-factorial scheme for gap-filling of eddy covariance measurements of daytime evapotranspiration Y. Jiang et al. 10.1016/j.agrformet.2022.109087
- Utility of Copernicus-Based Inputs for Actual Evapotranspiration Modeling in Support of Sustainable Water Use in Agriculture R. Guzinski et al. 10.1109/JSTARS.2021.3122573
- Classification and properties of non-idealized coastal wind profiles – an observational study C. Hallgren et al. 10.5194/wes-7-1183-2022
- AmeriFlux BASE data pipeline to support network growth and data sharing H. Chu et al. 10.1038/s41597-023-02531-2
- Drainage effects on carbon budgets of degraded peatlands in the north of the Netherlands T. Nijman et al. 10.1016/j.scitotenv.2024.172882
- A gap filling method for daily evapotranspiration of global flux data sets based on deep learning L. Qian et al. 10.1016/j.jhydrol.2024.131787
- Technical note: Flagging inconsistencies in flux tower data M. Jung et al. 10.5194/bg-21-1827-2024
- Global transpiration data from sap flow measurements: the SAPFLUXNET database R. Poyatos et al. 10.5194/essd-13-2607-2021
- A performance evaluation of despiking algorithms for eddy covariance data D. Vitale 10.1038/s41598-021-91002-y
- Modelling hourly evapotranspiration in urban environments with SCOPE using open remote sensing and meteorological data A. Duarte Rocha et al. 10.5194/hess-26-1111-2022
- Harmonized gap-filled datasets from 20 urban flux tower sites M. Lipson et al. 10.5194/essd-14-5157-2022
- System for automated Quality Control (SaQC) to enable traceable and reproducible data streams in environmental science L. Schmidt et al. 10.1016/j.envsoft.2023.105809
- Research on Oil Well Data Cleaning System Y. Feng & L. Zhao 10.2478/ijanmc-2022-0026
- El Niño-Southern Oscillation forcing on carbon and water cycling in a Bornean tropical rainforest N. Takamura et al. 10.1073/pnas.2301596120
- Quantitative Evaluation of Wavelet Analysis Method for Turbulent Flux Calculation of Non‐Stationary Series Y. Li et al. 10.1029/2022GL101591
Latest update: 21 Nov 2024
Short summary
This work describes a data cleaning procedure for the detection of eddy covariance fluxes affected by systematic errors. We believe that the proposed procedure can serve as a basis toward a unified quality control strategy suitable for the centralized data processing pipelines, where the use of completely data-driven and scalable procedures that guarantee high-quality standards and reproducibility of the released products constitutes an essential prerequisite.
This work describes a data cleaning procedure for the detection of eddy covariance fluxes...
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