Articles | Volume 11, issue 17
https://doi.org/10.5194/bg-11-4651-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-11-4651-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
03 Sep 2014
Research article |
| 03 Sep 2014
Evaluation of a plot-scale methane emission model using eddy covariance observations and footprint modelling
A. Budishchev
Earth and Climate Cluster, Faculty of Earth and Life Sciences, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
Y. Mi
Earth and Climate Cluster, Faculty of Earth and Life Sciences, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
J. van Huissteden
Earth and Climate Cluster, Faculty of Earth and Life Sciences, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
L. Belelli-Marchesini
Earth and Climate Cluster, Faculty of Earth and Life Sciences, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
G. Schaepman-Strub
Institute of Evolutionary Biology and Environmental Studies, University of Zürich, Winterhurerstraße 190, 8057, Zürich, Switzerland
F. J. W. Parmentier
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 223 62, Lund, Sweden
G. Fratini
LI-COR Biosciences GmbH, Siemenstraße 25a, 61352, Bad Homburg, Germany
A. Gallagher
Earth and Climate Cluster, Faculty of Earth and Life Sciences, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
T. C. Maximov
Biogeochemical Cycles of Permafrost Ecosystems Lab, Institute for Biological Problems of Cryolithozone SB RAS, 41 Lenin ave., 678891, Yakutsk, Russia
International scientific and educational center of biogeochemistry and climatology BEST (Biogeoscience Educational and Scientific Trainings), Kulakovskogo 46, 677000, Yakutsk, Russia
A. J. Dolman
Earth and Climate Cluster, Faculty of Earth and Life Sciences, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
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Cited
28 citations as recorded by crossref.
- Review and Synthesis: Peatland and Wetland Models Simulating CH4 Production, Oxidation and Transport Pathways A. Tilak et al. https://doi.org/10.1007/s13157-026-02089-w
- A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0) A. Bloom et al. https://doi.org/10.5194/gmd-10-2141-2017
- Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems S. Davidson et al. https://doi.org/10.3390/rs9121227
- Vegetation influence and environmental controls on greenhouse gas fluxes from a drained thermokarst lake in the western Canadian Arctic J. Skeeter et al. https://doi.org/10.5194/bg-17-4421-2020
- Spatial Representativeness of Eddy Covariance Measurements in a Coniferous Plantation Mixed with Cropland in Southeastern China W. Xiang et al. https://doi.org/10.3390/rs14195022
- Comparison of Closed Chamber and Eddy Covariance Methods to Improve the Understanding of Methane Fluxes from Rice Paddy Fields in Japan N. Chaichana et al. https://doi.org/10.3390/atmos9090356
- Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems Y. Wang et al. https://doi.org/10.3389/fenvs.2022.939238
- Estimating methane emissions using vegetation mapping in the taiga–tundra boundary of a north-eastern Siberian lowland T. Morozumi et al. https://doi.org/10.1080/16000889.2019.1581004
- Component greenhouse gas fluxes and radiative balance from two deltaic marshes in Louisiana: Pairing chamber techniques and eddy covariance K. Krauss et al. https://doi.org/10.1002/2015JG003224
- Global methane emissions from rice paddies are now increasingly quantifiable M. Mehla et al. https://doi.org/10.1038/s43247-026-03902-4
- Interpreting eddy covariance data from heterogeneous Siberian tundra: land-cover-specific methane fluxes and spatial representativeness J. Tuovinen et al. https://doi.org/10.5194/bg-16-255-2019
- Combining eddy-covariance and chamber measurements to determine the methane budget from a small, heterogeneous urban floodplain wetland park T. Morin et al. https://doi.org/10.1016/j.agrformet.2017.01.022
- HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands M. Raivonen et al. https://doi.org/10.5194/gmd-10-4665-2017
- Upscaling tower-observed turbulent exchange at fine spatio-temporal resolution using environmental response functions K. Xu et al. https://doi.org/10.1016/j.agrformet.2016.07.019
- The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling C. Phillips et al. https://doi.org/10.1007/s11104-016-3084-x
- Advances in the Eddy Covariance Approach to CH4 Monitoring Over Two and a Half Decades T. Morin https://doi.org/10.1029/2018JG004796
- A cross-site comparison of ecosystem- and plot-scale methane fluxes across multiple timescales T. Määttä et al. https://doi.org/10.5194/bg-23-4379-2026
- Effects of inhomogeneities within the flux footprint on the interpretation of seasonal, annual, and interannual ecosystem carbon exchange A. Griebel et al. https://doi.org/10.1016/j.agrformet.2016.02.002
- A New Process‐Based Soil Methane Scheme: Evaluation Over Arctic Field Sites With the ISBA Land Surface Model X. Morel et al. https://doi.org/10.1029/2018MS001329
- Forecasting short-term methane based on corrected numerical weather prediction outputs S. Zhao et al. https://doi.org/10.1016/j.jclepro.2024.142500
- Inference of spatial heterogeneity in surface fluxes from eddy covariance data: A case study from a subarctic mire ecosystem P. Levy et al. https://doi.org/10.1016/j.agrformet.2019.107783
- Field testing two flux footprint models T. Coates et al. https://doi.org/10.5194/amt-14-7147-2021
- East Siberian Arctic inland waters emit mostly contemporary carbon J. Dean et al. https://doi.org/10.1038/s41467-020-15511-6
- Resolving heterogeneous fluxes from tundra halves the growing season carbon budget S. Ludwig et al. https://doi.org/10.5194/bg-21-1301-2024
- Scaling and balancing methane fluxes in a heterogeneous tundra ecosystem of the Lena River Delta N. Rößger et al. https://doi.org/10.1016/j.agrformet.2018.06.026
- Importance of vegetation classes in modeling CH4 emissions from boreal and subarctic wetlands in Finland T. Li et al. https://doi.org/10.1016/j.scitotenv.2016.08.020
- Contrasting radiation and soil heat fluxes in Arctic shrub and wet sedge tundra I. Juszak et al. https://doi.org/10.5194/bg-13-4049-2016
- Higher recent peat C accumulation than that during the Holocene on the Zoige Plateau M. Wang et al. https://doi.org/10.1016/j.quascirev.2015.01.025
28 citations as recorded by crossref.
- Review and Synthesis: Peatland and Wetland Models Simulating CH4 Production, Oxidation and Transport Pathways A. Tilak et al. https://doi.org/10.1007/s13157-026-02089-w
- A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0) A. Bloom et al. https://doi.org/10.5194/gmd-10-2141-2017
- Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems S. Davidson et al. https://doi.org/10.3390/rs9121227
- Vegetation influence and environmental controls on greenhouse gas fluxes from a drained thermokarst lake in the western Canadian Arctic J. Skeeter et al. https://doi.org/10.5194/bg-17-4421-2020
- Spatial Representativeness of Eddy Covariance Measurements in a Coniferous Plantation Mixed with Cropland in Southeastern China W. Xiang et al. https://doi.org/10.3390/rs14195022
- Comparison of Closed Chamber and Eddy Covariance Methods to Improve the Understanding of Methane Fluxes from Rice Paddy Fields in Japan N. Chaichana et al. https://doi.org/10.3390/atmos9090356
- Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems Y. Wang et al. https://doi.org/10.3389/fenvs.2022.939238
- Estimating methane emissions using vegetation mapping in the taiga–tundra boundary of a north-eastern Siberian lowland T. Morozumi et al. https://doi.org/10.1080/16000889.2019.1581004
- Component greenhouse gas fluxes and radiative balance from two deltaic marshes in Louisiana: Pairing chamber techniques and eddy covariance K. Krauss et al. https://doi.org/10.1002/2015JG003224
- Global methane emissions from rice paddies are now increasingly quantifiable M. Mehla et al. https://doi.org/10.1038/s43247-026-03902-4
- Interpreting eddy covariance data from heterogeneous Siberian tundra: land-cover-specific methane fluxes and spatial representativeness J. Tuovinen et al. https://doi.org/10.5194/bg-16-255-2019
- Combining eddy-covariance and chamber measurements to determine the methane budget from a small, heterogeneous urban floodplain wetland park T. Morin et al. https://doi.org/10.1016/j.agrformet.2017.01.022
- HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands M. Raivonen et al. https://doi.org/10.5194/gmd-10-4665-2017
- Upscaling tower-observed turbulent exchange at fine spatio-temporal resolution using environmental response functions K. Xu et al. https://doi.org/10.1016/j.agrformet.2016.07.019
- The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling C. Phillips et al. https://doi.org/10.1007/s11104-016-3084-x
- Advances in the Eddy Covariance Approach to CH4 Monitoring Over Two and a Half Decades T. Morin https://doi.org/10.1029/2018JG004796
- A cross-site comparison of ecosystem- and plot-scale methane fluxes across multiple timescales T. Määttä et al. https://doi.org/10.5194/bg-23-4379-2026
- Effects of inhomogeneities within the flux footprint on the interpretation of seasonal, annual, and interannual ecosystem carbon exchange A. Griebel et al. https://doi.org/10.1016/j.agrformet.2016.02.002
- A New Process‐Based Soil Methane Scheme: Evaluation Over Arctic Field Sites With the ISBA Land Surface Model X. Morel et al. https://doi.org/10.1029/2018MS001329
- Forecasting short-term methane based on corrected numerical weather prediction outputs S. Zhao et al. https://doi.org/10.1016/j.jclepro.2024.142500
- Inference of spatial heterogeneity in surface fluxes from eddy covariance data: A case study from a subarctic mire ecosystem P. Levy et al. https://doi.org/10.1016/j.agrformet.2019.107783
- Field testing two flux footprint models T. Coates et al. https://doi.org/10.5194/amt-14-7147-2021
- East Siberian Arctic inland waters emit mostly contemporary carbon J. Dean et al. https://doi.org/10.1038/s41467-020-15511-6
- Resolving heterogeneous fluxes from tundra halves the growing season carbon budget S. Ludwig et al. https://doi.org/10.5194/bg-21-1301-2024
- Scaling and balancing methane fluxes in a heterogeneous tundra ecosystem of the Lena River Delta N. Rößger et al. https://doi.org/10.1016/j.agrformet.2018.06.026
- Importance of vegetation classes in modeling CH4 emissions from boreal and subarctic wetlands in Finland T. Li et al. https://doi.org/10.1016/j.scitotenv.2016.08.020
- Contrasting radiation and soil heat fluxes in Arctic shrub and wet sedge tundra I. Juszak et al. https://doi.org/10.5194/bg-13-4049-2016
- Higher recent peat C accumulation than that during the Holocene on the Zoige Plateau M. Wang et al. https://doi.org/10.1016/j.quascirev.2015.01.025
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