86 citations as recorded by crossref.

1. Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0 N. Raoult et al. 10.5194/gmd-9-2833-2016
2. Constraining a terrestrial biosphere model with remotely sensed atmospheric carbon dioxide T. Kaminski et al. 10.1016/j.rse.2017.08.017
3. Toward Robust Parameterizations in Ecosystem‐Level Photosynthesis Models S. Bao et al. 10.1029/2022MS003464
4. Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm J. Kallingal et al. 10.5194/gmd-17-2299-2024
5. Age‐dependent forest carbon sink: Estimation via inverse modeling T. Zhou et al. 10.1002/2015JG002943
6. Parameterization and sensitivity analysis of a process‐based terrestrial ecosystem model using adjoint method Q. Zhu & Q. Zhuang 10.1002/2013MS000241
7. Contrasting responses of grassland water and carbon exchanges to climate change between Tibetan Plateau and Inner Mongolia D. Liu et al. 10.1016/j.agrformet.2017.11.034
8. Evaluation and uncertainty analysis of regional-scale CLM4.5 net carbon flux estimates H. Post et al. 10.5194/bg-15-187-2018
9. Spatial biases reduce the ability of Earth system models to simulate soil heterotrophic respiration fluxes B. Guenet et al. 10.5194/bg-21-657-2024
10. Ecosystem biogeochemistry model parameterization: Do more flux data result in a better model in predicting carbon flux? Q. Zhu & Q. Zhuang 10.1890/ES15-00259.1
11. Evaluating the potential of large-scale simulations to predict carbon fluxes of terrestrial ecosystems over a European Eddy Covariance network M. Balzarolo et al. 10.5194/bg-11-2661-2014
12. Exploring a hybrid ensemble–variational data assimilation technique (4DEnVar) with a simple ecosystem carbon model N. Douglas et al. 10.1016/j.envsoft.2025.106361
13. Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts C. Szczypta et al. 10.5194/gmd-7-931-2014
14. 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
15. The comparison between single-point method and footprint-integrated validation method of the remote-sensing retrieval of evapotranspiration: a case study at Daman site Y. Zhou et al. 10.1080/01431161.2024.2412803
16. Terrestrial CO2 exchange diagnosis using a peatland-optimized vegetation photosynthesis and respiration model (VPRM) for the Hudson Bay Lowlands O. Balogun et al. 10.1016/j.scitotenv.2023.162591
17. Improving North American terrestrial CO2 flux diagnosis using spatial structure in land surface model residuals T. Hilton et al. 10.5194/bg-10-4607-2013
18. Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model C. Safta et al. 10.5194/gmd-8-1899-2015
19. 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
20. A new approach to optimal discretization of plant functional types in a process‐based ecosystem model with forest management: a case study for temperate conifers M. Peaucelle et al. 10.1111/geb.12557
21. The potential benefit of using forest biomass data in addition to carbon and water flux measurements to constrain ecosystem model parameters: Case studies at two temperate forest sites T. Thum et al. 10.1016/j.agrformet.2016.12.004
22. Observation and integrated Earth-system science: A roadmap for 2016–2025 A. Simmons et al. 10.1016/j.asr.2016.03.008
23. Ideas and perspectives: Beyond model evaluation – combining experiments and models to advance terrestrial ecosystem science S. Caldararu et al. 10.5194/bg-20-3637-2023
24. Bayesian integration of flux tower data into a process-based simulator for quantifying uncertainty in simulated output R. Raj et al. 10.5194/gmd-11-83-2018
25. Strong constraint on modelled global carbon uptake using solar-induced chlorophyll fluorescence data N. MacBean et al. 10.1038/s41598-018-20024-w
26. Assimilation of NEON Observations Into a Process‐Based Carbon Cycle Model Reveals Divergent Mechanisms of Carbon Dynamics in Temperate Deciduous Forests C. Jung & O. Hararuk 10.1029/2021JG006474
27. Assessing nitrogen controls on carbon, water and energy exchanges in major plant functional types across North America using a carbon and nitrogen coupled ecosystem model S. Huang et al. 10.1016/j.ecolmodel.2015.11.020
28. Quantifying the model structural error in carbon cycle data assimilation systems S. Kuppel et al. 10.5194/gmd-6-45-2013
29. 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. 10.1029/2019JG005040
30. The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling C. Phillips et al. 10.1007/s11104-016-3084-x
31. Greenhouse gas observation network design for Africa A. Nickless et al. 10.1080/16000889.2020.1824486
32. Parameter uncertainty dominates C-cycle forecast errors over most of Brazil for the 21st century T. Smallman et al. 10.5194/esd-12-1191-2021
33. Assimilation of river discharge in a land surface model to improve estimates of the continental water cycles F. Wang et al. 10.5194/hess-22-3863-2018
34. Potential of MODIS data to track the variability in ecosystem water-use efficiency of temperate deciduous forests X. Tang et al. 10.1016/j.ecoleng.2016.02.022
35. A novel approach for ecosystem respiration simulation in drylands J. Ai et al. 10.3389/fevo.2023.1186272
36. Fundamentals of data assimilation applied to biogeochemistry P. Rayner et al. 10.5194/acp-19-13911-2019
37. 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
38. Assimilation of repeated woody biomass observations constrains decadal ecosystem carbon cycle uncertainty in aggrading forests T. Smallman et al. 10.1002/2016JG003520
39. Quantifying the constraint of biospheric process parameters by CO2 concentration and flux measurement networks through a carbon cycle data assimilation system E. Koffi et al. 10.5194/acp-13-10555-2013
40. Separation of the Effects of Land and Climate Model Errors on Simulated Contemporary Land Carbon Cycle Trends in the MPI Earth System Model version 1* D. Dalmonech et al. 10.1175/JCLI-D-13-00593.1
41. Models ignoring spatial heterogeneities of forest age will significantly overestimate the climate effects on litterfall in China X. Liu et al. 10.1016/j.scitotenv.2019.01.162
42. Nonsteady state carbon sequestration in forest ecosystems of China estimated by data assimilation T. Zhou et al. 10.1002/jgrg.20114
43. Ecosystem model optimization using in situ flux observations: benefit of Monte Carlo versus variational schemes and analyses of the year-to-year model performances D. Santaren et al. 10.5194/bg-11-7137-2014
44. 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
45. Simulated effects of canopy structural complexity on forest productivity M. Toda et al. 10.1016/j.foreco.2023.120978
46. 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
47. Precipitation amount, seasonality and frequency regulate carbon cycling of a semi-arid grassland ecosystem in Inner Mongolia, China: A modeling analysis S. Peng et al. 10.1016/j.agrformet.2013.02.002
48. From Ecosystem Observation to Environmental Decision-Making: Model-Data Fusion as an Operational Tool T. Smallman et al. 10.3389/ffgc.2021.818661
49. Modeling phenological controls on carbon dynamics in dryland sagebrush ecosystems K. Renwick et al. 10.1016/j.agrformet.2019.04.003
50. Exploring the potential of history matching for land surface model calibration N. Raoult et al. 10.5194/gmd-17-5779-2024
51. Improving the global MODIS GPP model by optimizing parameters with FLUXNET data X. Huang et al. 10.1016/j.agrformet.2020.108314
52. Carbonyl sulfide: comparing a mechanistic representation of the vegetation uptake in a land surface model and the leaf relative uptake approach F. Maignan et al. 10.5194/bg-18-2917-2021
53. A boreal forest model benchmarking dataset for North America: a case study with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) B. Qu et al. 10.1088/1748-9326/ace376
54. Uncertainty analysis of eddy covariance CO2 flux measurements for different EC tower distances using an extended two-tower approach H. Post et al. 10.5194/bg-12-1205-2015
55. Variation of parameters in a Flux-Based Ecosystem Model across 12 sites of terrestrial ecosystems in the conterminous USA Q. Li et al. 10.1016/j.ecolmodel.2016.05.016
56. Optimizing Carbon Cycle Parameters Drastically Improves Terrestrial Biosphere Model Underestimates of Dryland Mean Net CO2 Flux and its Inter‐Annual Variability K. Mahmud et al. 10.1029/2021JG006400
57. The role of data assimilation in predictive ecology S. Niu et al. 10.1890/ES13-00273.1
58. Variational assimilation of land surface temperature within the ORCHIDEE Land Surface Model Version 1.2.6 H. Benavides Pinjosovsky et al. 10.5194/gmd-10-85-2017
59. Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals N. Raoult et al. 10.5194/tc-17-2705-2023
60. Using Free Air CO2 Enrichment data to constrain land surface model projections of the terrestrial carbon cycle N. Raoult et al. 10.5194/bg-21-1017-2024
61. Plant gross primary production, plant respiration and carbonyl sulfide emissions over the globe inferred by atmospheric inverse modelling M. Remaud et al. 10.5194/acp-22-2525-2022
62. 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
63. Performance of the ecosystem demography model (EDv2.2) in simulating gross primary production capacity and activity in a dryland study area H. Dashti et al. 10.1016/j.agrformet.2020.108270
64. Evaluation of root water uptake in the ISBA-A-gs land surface model using agricultural yield statistics over France N. Canal et al. 10.5194/hess-18-4979-2014
65. Description and validation of an intermediate complexity model for ecosystem photosynthesis and evapotranspiration: ACM-GPP-ETv1 T. Smallman & M. Williams 10.5194/gmd-12-2227-2019
66. Model–data fusion across ecosystems: from multisite optimizations to global simulations S. Kuppel et al. 10.5194/gmd-7-2581-2014
67. Identifying environmental controls on vegetation greenness phenology through model–data integration M. Forkel et al. 10.5194/bg-11-7025-2014
68. 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
69. Assimilating Sentinel-2 data in a modified vegetation photosynthesis and respiration model (VPRM) to improve the simulation of croplands CO2 fluxes in Europe H. Bazzi et al. 10.1016/j.jag.2024.103666
70. Assimilating ESA CCI land surface temperature into the ORCHIDEE land surface model: insights from a multi-site study across Europe L. Olivera-Guerra et al. 10.5194/hess-29-261-2025
71. Local-scale evaluation of the simulated interactions between energy, water and vegetation in ISBA, ORCHIDEE and a diagnostic model J. De Pue et al. 10.5194/bg-19-4361-2022
72. Photosynthetic phenological variation may promote coexistence among co-dominant tree species in a Madrean sky island mixed conifer forest D. Potts et al. 10.1093/treephys/tpx076
73. Covariations between plant functional traits emerge from constraining parameterization of a terrestrial biosphere model M. Peaucelle et al. 10.1111/geb.12937
74. Using satellite data to improve the leaf phenology of a global terrestrial biosphere model N. MacBean et al. 10.5194/bg-12-7185-2015
75. Simulating canopy carbonyl sulfide uptake of two forest stands through an improved ecosystem model and parameter optimization using an ensemble Kalman filter B. Chen et al. 10.1016/j.ecolmodel.2022.110212
76. Bayesian inversions of a dynamic vegetation model at four European grassland sites J. Minet et al. 10.5194/bg-12-2809-2015
77. 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
78. Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH J. Mäkelä et al. 10.5194/gmd-12-4075-2019
79. 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. 10.1029/2021GB007177
80. Unravelling the Effects of Tree-Size and Canopy Structural Complexity on Forest Productivity M. Toda et al. 10.2139/ssrn.4148599
81. Estimation of Community Land Model parameters for an improved assessment of net carbon fluxes at European sites H. Post et al. 10.1002/2015JG003297
82. Testing variational estimation of process parameters and initial conditions of an earth system model S. Blessing et al. 10.3402/tellusa.v66.22606
83. Impacts of reduced model complexity and driver resolution on cropland ecosystem photosynthesis estimates A. Revill et al. 10.1016/j.fcr.2015.12.006
84. Calibration and validation of a semi-empirical flux ecosystem model for coniferous forests in the Boreal region F. Minunno et al. 10.1016/j.ecolmodel.2016.09.020
85. Quantifying carbon budget, crop yields and their responses to environmental variability using the ecosys model for U.S. Midwestern agroecosystems W. Zhou et al. 10.1016/j.agrformet.2021.108521
86. 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