30 citations as recorded by crossref.

1. Quantifying and Reducing Uncertainty in Global Carbon Cycle Predictions: Lessons and Perspectives From 15 Years of Data Assimilation Studies With the ORCHIDEE Terrestrial Biosphere Model N. MacBean et al. https://doi.org/10.1029/2021GB007177
2. Towards the assimilation of atmospheric CO2 concentration data in a land surface model using adjoint-free variational methods S. Beylat et al. https://doi.org/10.5194/gmd-18-7501-2025
3. Contrasting responses of grassland water and carbon exchanges to climate change between Tibetan Plateau and Inner Mongolia D. Liu et al. https://doi.org/10.1016/j.agrformet.2017.11.034
4. Comment F. Chevallier & F. Bréon https://doi.org/10.1080/01621459.2017.1419138
5. Joint assimilation of eddy covariance flux measurements and FAPAR products over temperate forests within a process‐oriented biosphere model C. Bacour et al. https://doi.org/10.1002/2015JG002966
6. Constraining a land-surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System V1.0 G. Schürmann et al. https://doi.org/10.5194/gmd-9-2999-2016
7. Estimating global annual gross primary production based on satellite-derived phenology and maximal carbon uptake capacity X. Xu & D. Chen https://doi.org/10.1016/j.envres.2024.119063
8. Technical Note: Comparison of ensemble Kalman filter and variational approaches for CO2 data assimilation A. Chatterjee & A. Michalak https://doi.org/10.5194/acp-13-11643-2013
9. Fundamentals of data assimilation applied to biogeochemistry P. Rayner et al. https://doi.org/10.5194/acp-19-13911-2019
10. Estimating global gross primary productivity using chlorophyll fluorescence and a data assimilation system with the BETHY-SCOPE model A. Norton et al. https://doi.org/10.5194/bg-16-3069-2019
11. Model–data fusion across ecosystems: from multisite optimizations to global simulations S. Kuppel et al. https://doi.org/10.5194/gmd-7-2581-2014
12. Using storage selection functions to assess mixing patterns and water ages of soil water, evaporation and transpiration A. Smith et al. https://doi.org/10.1016/j.advwatres.2020.103586
13. Consistent assimilation of multiple data streams in a carbon cycle data assimilation system N. MacBean et al. https://doi.org/10.5194/gmd-9-3569-2016
14. Diagnostic methods for atmospheric inversions of long-lived greenhouse gases A. Michalak et al. https://doi.org/10.5194/acp-17-7405-2017
15. Estimating forest carbon fluxes using four different data-driven techniques based on long-term eddy covariance measurements: Model comparison and evaluation X. Dou & Y. Yang https://doi.org/10.1016/j.scitotenv.2018.01.202
16. Balancing multiple constraints in model‐data integration: Weights and the parameter block approach T. Wutzler & N. Carvalhais https://doi.org/10.1002/2014JG002650
17. Global Estimates of Marine Gross Primary Production Based on Machine Learning Upscaling of Field Observations Y. Huang et al. https://doi.org/10.1029/2020GB006718
18. Assimilating solar-induced chlorophyll fluorescence into the terrestrial biosphere model BETHY-SCOPE v1.0: model description and information content A. Norton et al. https://doi.org/10.5194/gmd-11-1517-2018
19. Spatiotemporal patterns of terrestrial gross primary production: A review A. Anav et al. https://doi.org/10.1002/2015RG000483
20. A new moving strategy for the sequential Monte Carlo approach in optimizing the hydrological model parameters G. Zhu et al. https://doi.org/10.1016/j.advwatres.2018.02.007
21. Improving Estimates of Gross Primary Productivity by Assimilating Solar‐Induced Fluorescence Satellite Retrievals in a Terrestrial Biosphere Model Using a Process‐Based SIF Model C. Bacour et al. https://doi.org/10.1029/2019JG005040
22. On the statistical optimality of CO2 atmospheric inversions assimilating CO2 column retrievals F. Chevallier https://doi.org/10.5194/acp-15-11133-2015
23. Towards a more detailed representation of high-latitude vegetation in the global land surface model ORCHIDEE (ORC-HL-VEGv1.0) A. Druel et al. https://doi.org/10.5194/gmd-10-4693-2017
24. 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. https://doi.org/10.5194/bg-20-1089-2023
25. Spatio‐Temporal Model Variance‐Covariance Approach to Assimilating Streamflow Observations Into a Distributed Landscape Water Balance Model S. Tian et al. https://doi.org/10.1029/2021WR031649
26. Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values A. Valade et al. https://doi.org/10.5194/gmd-7-1225-2014
27. A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle P. Peylin et al. https://doi.org/10.5194/gmd-9-3321-2016
28. Testing the capability of ORCHIDEE land surface model to simulate Arctic ecosystems: Sensitivity analysis and site‐level model calibration S. Dantec‐Nédélec et al. https://doi.org/10.1002/2016MS000860
29. Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system P. Ciais et al. https://doi.org/10.5194/bg-11-3547-2014
30. Estimation of Community Land Model parameters for an improved assessment of net carbon fluxes at European sites H. Post et al. https://doi.org/10.1002/2015JG003297