Articles | Volume 10, issue 2
https://doi.org/10.5194/bg-10-789-2013
© Author(s) 2013. 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-10-789-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Simultaneous assimilation of satellite and eddy covariance data for improving terrestrial water and carbon simulations at a semi-arid woodland site in Botswana
T. Kato
Department of Earth Sciences, University of Bristol, Bristol, UK
Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
Laboratoire des Sciences du Climat et de l' Environnement, UMR 8212, CEA-CNRS-UVSQ, CEA-orme des Merisiers, 91191 Gif-sur-Yvette, France
W. Knorr
Department of Earth Sciences, University of Bristol, Bristol, UK
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 223 62 Lund, Sweden
M. Scholze
Department of Earth Sciences, University of Bristol, Bristol, UK
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 223 62 Lund, Sweden
KlimaCampus, University of Hamburg, Hamburg, Germany
E. Veenendaal
Nature Conservation and Plant Ecology Group, Department of Environmental Sciences,Wageningen University, Wageningen, The Netherlands
T. Kaminski
FastOpt, Hamburg, Germany
J. Kattge
Max-Planck-Institute for Biogeochemistry, Jena, Germany
N. Gobron
European Commission, Joint Research Center, Ispra, Italy
Viewed
Total article views: 4,627 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013, article published on 22 Mar 2012)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
2,485 | 1,964 | 178 | 4,627 | 182 | 117 |
- HTML: 2,485
- PDF: 1,964
- XML: 178
- Total: 4,627
- BibTeX: 182
- EndNote: 117
Total article views: 3,794 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 05 Feb 2013)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
2,053 | 1,593 | 148 | 3,794 | 158 | 110 |
- HTML: 2,053
- PDF: 1,593
- XML: 148
- Total: 3,794
- BibTeX: 158
- EndNote: 110
Total article views: 833 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013, article published on 22 Mar 2012)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
432 | 371 | 30 | 833 | 24 | 7 |
- HTML: 432
- PDF: 371
- XML: 30
- Total: 833
- BibTeX: 24
- EndNote: 7
Cited
36 citations as recorded by crossref.
- Advancement and Applications of Forest Remote Sensing in Korea: Past, Present, and Future Perspectives K. Kim et al. 10.7780/kjrs.2024.40.5.2.8
- Quantifying the constraint of biospheric process parameters by CO<sub>2</sub> concentration and flux measurement networks through a carbon cycle data assimilation system E. Koffi et al. 10.5194/acp-13-10555-2013
- Using SMOS soil moisture data combining CO2 flask samples to constrain carbon fluxes during 2010–2015 within a Carbon Cycle Data Assimilation System (CCDAS) M. Wu et al. 10.1016/j.rse.2020.111719
- Simultaneous Assimilation of Remotely Sensed Soil Moisture and FAPAR for Improving Terrestrial Carbon Fluxes at Multiple Sites Using CCDAS M. Wu et al. 10.3390/rs11010027
- On the Response of European Vegetation Phenology to Hydroclimatic Anomalies G. Ceccherini et al. 10.3390/rs6043143
- Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0) H. Zhu et al. 10.5194/gmd-17-6337-2024
- Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France A. Barbu et al. 10.5194/hess-18-173-2014
- Modeling Carbon Stocks in a Secondary Tropical Dry Forest in the Yucatan Peninsula, Mexico Z. Dai et al. 10.1007/s11270-014-1925-x
- A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions S. Lienert & F. Joos 10.5194/bg-15-2909-2018
- Quantifying the carbon uptake by vegetation for Europe on a 1 km<sup>2</sup> resolution using a remote sensing driven vegetation model K. Wißkirchen et al. 10.5194/gmd-6-1623-2013
- Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts C. Szczypta et al. 10.5194/gmd-7-931-2014
- Sensitivity of the annual net ecosystem exchange to the cospectral model used for high frequency loss corrections at a grazed grassland site O. Mamadou et al. 10.1016/j.agrformet.2016.06.008
- Estimating global gross primary productivity using chlorophyll fluorescence and a data assimilation system with the BETHY-SCOPE model A. Norton et al. 10.5194/bg-16-3069-2019
- Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model C. Bacour et al. 10.5194/bg-20-1089-2023
- Machine Learning Accelerates Parameter Optimization and Uncertainty Assessment of a Land Surface Model Y. Sawada 10.1029/2020JD032688
- <i>FluxPro</i> as a realtime monitoring and surveilling system for eddy covariance flux measurement W. KIM et al. 10.2480/agrmet.D-14-00034
- Estimation of Community Land Model parameters for an improved assessment of net carbon fluxes at European sites H. Post et al. 10.1002/2015JG003297
- A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle P. Peylin et al. 10.5194/gmd-9-3321-2016
- Terrestrial ecosystem model studies and their contributions to AsiaFlux A. ITO & K. ICHII 10.2480/agrmet.D-20-00024
- Modelling random uncertainty of eddy covariance flux measurements D. Vitale et al. 10.1007/s00477-019-01664-4
- Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2) V. Bastrikov et al. 10.5194/gmd-11-4739-2018
- Improved process representation of leaf phenology significantly shifts climate sensitivity of ecosystem carbon balance A. Norton et al. 10.5194/bg-20-2455-2023
- Regional-scale data assimilation with the Spatially Explicit Individual-based Dynamic Global Vegetation Model (SEIB-DGVM) over Siberia H. Arakida et al. 10.1186/s40645-021-00443-6
- Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems M. Scholze et al. 10.5194/bg-14-3401-2017
- Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables M. Dantas de Paula et al. 10.1080/17538947.2019.1597187
- Non-Gaussian data assimilation of satellite-based leaf area index observations with an individual-based dynamic global vegetation model H. Arakida et al. 10.5194/npg-24-553-2017
- Consistent assimilation of multiple data streams in a carbon cycle data assimilation system N. MacBean et al. 10.5194/gmd-9-3569-2016
- Improving the quantification of terrestrial ecosystem carbon dynamics over the United States using an adjoint method Q. Zhu & Q. Zhuang 10.1890/ES13-00058.1
- Constraining a terrestrial biosphere model with remotely sensed atmospheric carbon dioxide T. Kaminski et al. 10.1016/j.rse.2017.08.017
- Assessing MODIS carbon and water fluxes in grasslands and shrublands in semiarid regions using eddy covariance tower data Y. Li et al. 10.1080/01431161.2020.1811915
- Joint assimilation of eddy covariance flux measurements and FAPAR products over temperate forests within a process‐oriented biosphere model C. Bacour et al. 10.1002/2015JG002966
- Simultaneous assimilation of SMOS soil moisture and atmospheric CO2 in-situ observations to constrain the global terrestrial carbon cycle M. Scholze et al. 10.1016/j.rse.2016.02.058
- Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years J. Xiao et al. 10.1016/j.rse.2019.111383
- Constraining a land-surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System V1.0 G. Schürmann et al. 10.5194/gmd-9-2999-2016
- Simulating carbon and water fluxes using a coupled process-based terrestrial biosphere model and joint assimilation of leaf area index and surface soil moisture S. Li et al. 10.5194/hess-26-6311-2022
- Quantifying the model structural error in carbon cycle data assimilation systems S. Kuppel et al. 10.5194/gmd-6-45-2013
35 citations as recorded by crossref.
- Advancement and Applications of Forest Remote Sensing in Korea: Past, Present, and Future Perspectives K. Kim et al. 10.7780/kjrs.2024.40.5.2.8
- Quantifying the constraint of biospheric process parameters by CO<sub>2</sub> concentration and flux measurement networks through a carbon cycle data assimilation system E. Koffi et al. 10.5194/acp-13-10555-2013
- Using SMOS soil moisture data combining CO2 flask samples to constrain carbon fluxes during 2010–2015 within a Carbon Cycle Data Assimilation System (CCDAS) M. Wu et al. 10.1016/j.rse.2020.111719
- Simultaneous Assimilation of Remotely Sensed Soil Moisture and FAPAR for Improving Terrestrial Carbon Fluxes at Multiple Sites Using CCDAS M. Wu et al. 10.3390/rs11010027
- On the Response of European Vegetation Phenology to Hydroclimatic Anomalies G. Ceccherini et al. 10.3390/rs6043143
- Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0) H. Zhu et al. 10.5194/gmd-17-6337-2024
- Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France A. Barbu et al. 10.5194/hess-18-173-2014
- Modeling Carbon Stocks in a Secondary Tropical Dry Forest in the Yucatan Peninsula, Mexico Z. Dai et al. 10.1007/s11270-014-1925-x
- A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions S. Lienert & F. Joos 10.5194/bg-15-2909-2018
- Quantifying the carbon uptake by vegetation for Europe on a 1 km<sup>2</sup> resolution using a remote sensing driven vegetation model K. Wißkirchen et al. 10.5194/gmd-6-1623-2013
- Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts C. Szczypta et al. 10.5194/gmd-7-931-2014
- Sensitivity of the annual net ecosystem exchange to the cospectral model used for high frequency loss corrections at a grazed grassland site O. Mamadou et al. 10.1016/j.agrformet.2016.06.008
- Estimating global gross primary productivity using chlorophyll fluorescence and a data assimilation system with the BETHY-SCOPE model A. Norton et al. 10.5194/bg-16-3069-2019
- Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model C. Bacour et al. 10.5194/bg-20-1089-2023
- Machine Learning Accelerates Parameter Optimization and Uncertainty Assessment of a Land Surface Model Y. Sawada 10.1029/2020JD032688
- <i>FluxPro</i> as a realtime monitoring and surveilling system for eddy covariance flux measurement W. KIM et al. 10.2480/agrmet.D-14-00034
- Estimation of Community Land Model parameters for an improved assessment of net carbon fluxes at European sites H. Post et al. 10.1002/2015JG003297
- A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle P. Peylin et al. 10.5194/gmd-9-3321-2016
- Terrestrial ecosystem model studies and their contributions to AsiaFlux A. ITO & K. ICHII 10.2480/agrmet.D-20-00024
- Modelling random uncertainty of eddy covariance flux measurements D. Vitale et al. 10.1007/s00477-019-01664-4
- Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2) V. Bastrikov et al. 10.5194/gmd-11-4739-2018
- Improved process representation of leaf phenology significantly shifts climate sensitivity of ecosystem carbon balance A. Norton et al. 10.5194/bg-20-2455-2023
- Regional-scale data assimilation with the Spatially Explicit Individual-based Dynamic Global Vegetation Model (SEIB-DGVM) over Siberia H. Arakida et al. 10.1186/s40645-021-00443-6
- Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems M. Scholze et al. 10.5194/bg-14-3401-2017
- Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables M. Dantas de Paula et al. 10.1080/17538947.2019.1597187
- Non-Gaussian data assimilation of satellite-based leaf area index observations with an individual-based dynamic global vegetation model H. Arakida et al. 10.5194/npg-24-553-2017
- Consistent assimilation of multiple data streams in a carbon cycle data assimilation system N. MacBean et al. 10.5194/gmd-9-3569-2016
- Improving the quantification of terrestrial ecosystem carbon dynamics over the United States using an adjoint method Q. Zhu & Q. Zhuang 10.1890/ES13-00058.1
- Constraining a terrestrial biosphere model with remotely sensed atmospheric carbon dioxide T. Kaminski et al. 10.1016/j.rse.2017.08.017
- Assessing MODIS carbon and water fluxes in grasslands and shrublands in semiarid regions using eddy covariance tower data Y. Li et al. 10.1080/01431161.2020.1811915
- Joint assimilation of eddy covariance flux measurements and FAPAR products over temperate forests within a process‐oriented biosphere model C. Bacour et al. 10.1002/2015JG002966
- Simultaneous assimilation of SMOS soil moisture and atmospheric CO2 in-situ observations to constrain the global terrestrial carbon cycle M. Scholze et al. 10.1016/j.rse.2016.02.058
- Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years J. Xiao et al. 10.1016/j.rse.2019.111383
- Constraining a land-surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System V1.0 G. Schürmann et al. 10.5194/gmd-9-2999-2016
- Simulating carbon and water fluxes using a coupled process-based terrestrial biosphere model and joint assimilation of leaf area index and surface soil moisture S. Li et al. 10.5194/hess-26-6311-2022
1 citations as recorded by crossref.
Saved (final revised paper)
Latest update: 21 Nov 2024
Altmetrics
Final-revised paper
Preprint