Articles | Volume 9, issue 10
https://doi.org/10.5194/gmd-9-3569-2016
https://doi.org/10.5194/gmd-9-3569-2016
Methods for assessment of models
 | 
04 Oct 2016
Methods for assessment of models |  | 04 Oct 2016

Consistent assimilation of multiple data streams in a carbon cycle data assimilation system

Natasha MacBean, Philippe Peylin, Frédéric Chevallier, Marko Scholze, and Gregor Schürmann

Related authors

Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model
Cédric Bacour, Natasha MacBean, Frédéric Chevallier, Sébastien Léonard, Ernest N. Koffi, and Philippe Peylin
Biogeosciences, 20, 1089–1111, https://doi.org/10.5194/bg-20-1089-2023,https://doi.org/10.5194/bg-20-1089-2023, 2023
Short summary
Testing water fluxes and storage from two hydrology configurations within the ORCHIDEE land surface model across US semi-arid sites
Natasha MacBean, Russell L. Scott, Joel A. Biederman, Catherine Ottlé, Nicolas Vuichard, Agnès Ducharne, Thomas Kolb, Sabina Dore, Marcy Litvak, and David J. P. Moore
Hydrol. Earth Syst. Sci., 24, 5203–5230, https://doi.org/10.5194/hess-24-5203-2020,https://doi.org/10.5194/hess-24-5203-2020, 2020
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, Natasha MacBean, Cédric Bacour, Diego Santaren, Sylvain Kuppel, and Philippe Peylin
Geosci. Model Dev., 11, 4739–4754, https://doi.org/10.5194/gmd-11-4739-2018,https://doi.org/10.5194/gmd-11-4739-2018, 2018
Short summary
Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992–2015)
Wei Li, Natasha MacBean, Philippe Ciais, Pierre Defourny, Céline Lamarche, Sophie Bontemps, Richard A. Houghton, and Shushi Peng
Earth Syst. Sci. Data, 10, 219–234, https://doi.org/10.5194/essd-10-219-2018,https://doi.org/10.5194/essd-10-219-2018, 2018
Short summary
Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools, and turnover in temperate forests
Francesc Montané, Andrew M. Fox, Avelino F. Arellano, Natasha MacBean, M. Ross Alexander, Alex Dye, Daniel A. Bishop, Valerie Trouet, Flurin Babst, Amy E. Hessl, Neil Pederson, Peter D. Blanken, Gil Bohrer, Christopher M. Gough, Marcy E. Litvak, Kimberly A. Novick, Richard P. Phillips, Jeffrey D. Wood, and David J. P. Moore
Geosci. Model Dev., 10, 3499–3517, https://doi.org/10.5194/gmd-10-3499-2017,https://doi.org/10.5194/gmd-10-3499-2017, 2017
Short summary

Related subject area

Biogeosciences
ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model
Ye Liu, Huilin Huang, Sing-Chun Wang, Tao Zhang, Donghui Xu, and Yang Chen
Geosci. Model Dev., 18, 4103–4117, https://doi.org/10.5194/gmd-18-4103-2025,https://doi.org/10.5194/gmd-18-4103-2025, 2025
Short summary
Development and assessment of the physical–biogeochemical ocean regional model in the Northwest Pacific: NPRT v1.0 (ROMS v3.9–TOPAZ v2.0)
Daehyuk Kim, Hyun-Chae Jung, Jae-Hong Moon, and Na-Hyeon Lee
Geosci. Model Dev., 18, 3941–3964, https://doi.org/10.5194/gmd-18-3941-2025,https://doi.org/10.5194/gmd-18-3941-2025, 2025
Short summary
Estimation of above- and below-ground ecosystem parameters for DVM-DOS-TEM v0.7.0 using MADS v1.7.3
Elchin E. Jafarov, Hélène Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev., 18, 3857–3875, https://doi.org/10.5194/gmd-18-3857-2025,https://doi.org/10.5194/gmd-18-3857-2025, 2025
Short summary
Alquimia v1.0: a generic interface to biogeochemical codes – a tool for interoperable development, prototyping and benchmarking for multiphysics simulators
Sergi Molins, Benjamin J. Andre, Jeffrey N. Johnson, Glenn E. Hammond, Benjamin N. Sulman, Konstantin Lipnikov, Marcus S. Day, James J. Beisman, Daniil Svyatsky, Hang Deng, Peter C. Lichtner, Carl I. Steefel, and J. David Moulton
Geosci. Model Dev., 18, 3241–3263, https://doi.org/10.5194/gmd-18-3241-2025,https://doi.org/10.5194/gmd-18-3241-2025, 2025
Short summary
Soil nitrous oxide emissions from global land ecosystems and their drivers within the LPJ-GUESS model (v4.1)
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev., 18, 3131–3155, https://doi.org/10.5194/gmd-18-3131-2025,https://doi.org/10.5194/gmd-18-3131-2025, 2025
Short summary

Cited articles

Alton, P. B.: From site-level to global simulation: Reconciling carbon, water and energy fluxes over different spatial scales using a process-based ecophysiological land-surface model, Agr. Forest Meteorol., 176, 111–124, https://doi.org/10.1016/j.agrformet.2013.03.010, 2013.
Anav, A., Friedlingstein, P., Kidston, M., Bopp, L., Ciais, P., Cox, P., Jones, C., Jung, M., Myneni, R., and Zhu, Z.: Evaluating the land and ocean components of the global carbon cycle in the CMIP5 earth system models, J. Climate, 26, 6801–6843, https://doi.org/10.1175/JCLI-D-12-00417.1, 2013.
Bacour, C., Peylin, P., MacBean, N., Rayner, P. J., Delage, F., Chevallier, F., Weiss, M., Demarty, J., Santaren, D., Baret, F., Berveiller, D., Dufrêne, E., and Prunet, P.: Joint assimilation of eddy covariance flux measurements and FAPAR products over temperate forests within a process-oriented biosphere model, J. Geophys. Res.-Biogeo., 120, 1839–1857, https://doi.org/10.1002/2015JG002966, 2015.
Barrett, D. J., Hill, M. J., Hutley, L. B., Beringer, J., Xu, J. H., Cook, G. D., and Williams, R. J.: Prospects for improving savanna biophysical models by using multiple-constraints model-data assimilation methods, Aust. J. Botany, 53, 689–714, 2005.
Bloom, A. A. and Williams, M.: Constraining ecosystem carbon dynamics in a data-limited world: integrating ecological “common sense” in a model-data fusion framework, Biogeosciences, 12, 1299–1315, https://doi.org/10.5194/bg-12-1299-2015, 2015.
Download
Short summary
Model projections of the response of the terrestrial biosphere to anthropogenic emissions are uncertain, in part due to unknown fixed parameters in a model. Data assimilation can address this by using observations to optimise these parameter values. Using multiple types of data is beneficial for constraining different model processes, but it can also pose challenges in a DA context. This paper demonstrates and discusses the issues involved using toy models and examples from existing literature.
Share