Articles | Volume 11, issue 12
https://doi.org/10.5194/gmd-11-4739-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-4739-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
30 Nov 2018
Development and technical paper |
| 30 Nov 2018
| 30 Nov 2018
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)
Vladislav Bastrikov
CORRESPONDING AUTHOR
Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212 CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France
Institute of Industrial Ecology UB RAS, 620219 Ekaterinburg, Russia
Natasha MacBean
Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212 CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France
now at: School of Natural Resources and the Environment, University of Arizona, 1064 E Lowell St., 85721,
Tucson, AZ, USA
Cédric Bacour
Noveltis, 153 rue du Lac, 31670 Labège, France
Diego Santaren
Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212 CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France
Sylvain Kuppel
Northern Rivers Institute, University of Aberdeen, Aberdeen, AB24 3UF, UK
Philippe Peylin
Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212 CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France
Viewed
Total article views: 2,824 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Jul 2018)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,823 | 939 | 62 | 2,824 | 364 | 70 | 75 |
- HTML: 1,823
- PDF: 939
- XML: 62
- Total: 2,824
- Supplement: 364
- BibTeX: 70
- EndNote: 75
Total article views: 2,251 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Nov 2018)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,450 | 747 | 54 | 2,251 | 198 | 59 | 65 |
- HTML: 1,450
- PDF: 747
- XML: 54
- Total: 2,251
- Supplement: 198
- BibTeX: 59
- EndNote: 65
Total article views: 573 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Jul 2018)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 373 | 192 | 8 | 573 | 166 | 11 | 10 |
- HTML: 373
- PDF: 192
- XML: 8
- Total: 573
- Supplement: 166
- BibTeX: 11
- EndNote: 10
Viewed (geographical distribution)
Total article views: 2,824 (including HTML, PDF, and XML)
Thereof 2,568 with geography defined
and 256 with unknown origin.
Total article views: 2,251 (including HTML, PDF, and XML)
Thereof 1,994 with geography defined
and 257 with unknown origin.
Total article views: 573 (including HTML, PDF, and XML)
Thereof 574 with geography defined
and -1 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
16 citations as recorded by crossref.
- 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
- 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
- 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
- Assessing methane emissions for northern peatlands in ORCHIDEE-PEAT revision 7020 E. Salmon et al. 10.5194/gmd-15-2813-2022
- 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
- ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application P. Bosman & M. Krol 10.5194/gmd-16-47-2023
- 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
- Global modelling of soil carbonyl sulfide exchanges C. Abadie et al. 10.5194/bg-19-2427-2022
- 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
- Carbon and Water Fluxes of the Boreal Evergreen Needleleaf Forest Biome Constrained by Assimilating Ecosystem Carbonyl Sulfide Flux Observations C. Abadie et al. 10.1029/2023JG007407
- Process refinement contributed more than parameter optimization to improve the CoLM's performance in simulating the carbon and water fluxes in a grassland Y. Li et al. 10.1016/j.agrformet.2020.108067
- Improving Simulations of Vegetation Dynamics over the Tibetan Plateau: Role of Atmospheric Forcing Data and Spatial Resolution Z. Kang et al. 10.1007/s00376-022-1426-6
- Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266) Y. Zhang et al. 10.5194/gmd-15-9111-2022
- 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
- Modeling China's terrestrial ecosystem gross primary productivity with BEPS model: Parameter sensitivity analysis and model calibration X. Xing et al. 10.1016/j.agrformet.2023.109789
- Towards a more detailed representation of high-latitude vegetation in the global land surface model ORCHIDEE (ORC-HL-VEGv1.0) A. Druel et al. 10.5194/gmd-10-4693-2017
15 citations as recorded by crossref.
- 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
- 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
- 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
- Assessing methane emissions for northern peatlands in ORCHIDEE-PEAT revision 7020 E. Salmon et al. 10.5194/gmd-15-2813-2022
- 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
- ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application P. Bosman & M. Krol 10.5194/gmd-16-47-2023
- 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
- Global modelling of soil carbonyl sulfide exchanges C. Abadie et al. 10.5194/bg-19-2427-2022
- 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
- Carbon and Water Fluxes of the Boreal Evergreen Needleleaf Forest Biome Constrained by Assimilating Ecosystem Carbonyl Sulfide Flux Observations C. Abadie et al. 10.1029/2023JG007407
- Process refinement contributed more than parameter optimization to improve the CoLM's performance in simulating the carbon and water fluxes in a grassland Y. Li et al. 10.1016/j.agrformet.2020.108067
- Improving Simulations of Vegetation Dynamics over the Tibetan Plateau: Role of Atmospheric Forcing Data and Spatial Resolution Z. Kang et al. 10.1007/s00376-022-1426-6
- Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266) Y. Zhang et al. 10.5194/gmd-15-9111-2022
- 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
- Modeling China's terrestrial ecosystem gross primary productivity with BEPS model: Parameter sensitivity analysis and model calibration X. Xing et al. 10.1016/j.agrformet.2023.109789
Latest update: 24 Apr 2024
Short summary
In this study, we compare different methods for optimising parameters of the ORCHIDEE land surface model (LSM) using in situ observations. We use two minimisation methods - local gradient-based and global random search - applied either at each individual site or a group of sites characterised by one plant functional type. We demonstrate the advantages and challenges of different techniques and provide some advice on using it for the LSM parameters optimisation.
In this study, we compare different methods for optimising parameters of the ORCHIDEE land...
