Gallery: Climatic impact of global-scale deforestation

Climatic impact of global-scale deforestation: radiative versus non-radiative processes

All models investigated in this study simulated a negative sensitivity for both the land and the ocean carbon cycle to future climate. However, there was still a large uncertainty on the magnitude of these sensitivities. Eight models attributed most of the changes to the land, while three attributed it to the ocean. Also, a majority of the models located the reduction of land carbon uptake in the Tropics. However, the attribution of the land sensitivity to changes in net primary productivity versus changes in respiration is still subject to debate; no consensus emerged among the models.


Europe-wide reduction in primary productivity caused by the heat and drought in 2003

This study estimates a 30 per cent reduction in gross primary productivity over Europe, which resulted in a strong anomalous net source of carbon dioxide to the atmosphere and reversed the effect of four years of net ecosystem carbon sequestration. The results suggest that productivity reduction in eastern and western Europe can be explained by rainfall deficit and extreme summer heat, respectively. The study reports that ecosystem respiration decreased together with gross primary productivity, rather than accelerating with the temperature rise.

Reference: P. Ciais, M. Reichstein, N. Viovy, A. Granier, J. Ogeé, V. Allard, M. Aubinet, N. Buchmann, C. Bernhofer, A. Carrara, F. Chevallier, N. De Noblet, A. D. Friend, P. Friedlingstein, T. Grünwald, B. Heinesch, P. Keronen, A. Knohl, G. Krinner, D. Loustau, G. Manca, G. Matteucci, F. Miglietta, J. M. Ourcival, D. Papale, K. Pilegaard, S. Rambal, G. Seufert, J. F. Soussana, M. J. Sanz, E. D. Schulze, T. Vesala and R. Valentini, 2005. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature, 437:529-533.



      • Bernus, Anthony, and Catherine Ottlé Modeling subgrid lake energy balance in ORCHIDEE terrestrial scheme using the FLake lake model Geoscientific Model Development , 2022, 15, 10
      • Guion, Antoine, Solène Turquety, Jan Polcher, Romain Pennel, Sophie Bastin, and Thomas Arsouze Droughts and heatwaves in the Western Mediterranean: impact on vegetation and wildfires using the coupled WRF-ORCHIDEE regional model (RegIPSL) Climate Dynamics, 2022, 58, 9
      • MacBean, N., C. Bacour, N. Raoult, V. Bastrikov, E. N. Koffi, S. Kuppel, F. Maignan et al. 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 Global Biogeochemical Cycles, 2022, 36



      • Raoult, Nina, Catherine Ottlé, Philippe Peylin, Vladislav Bastrikov, and Pascal Maugis Evaluating and optimizing surface soil moisture drydowns in the ORCHIDEE land surface model at in situ locations Journal of Hydrometeorology, 2021, 22, 4
      • Sun, Yan, Daniel S. Goll, Jinfeng Chang, Philippe Ciais, Betrand Guenet, Julian Helfenstein, Yuanyuan Huang et al. Global evaluation of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1. 2 (r5986) Geoscientific Model Development, 2021, 14, 4
      • Jeong, Jina, Jonathan Barichivich, Philippe Peylin, Vanessa Haverd, Matthew Joseph McGrath, Nicolas Vuichard, Michael Neil Evans, Flurin Babst, and Sebastiaan Luyssaert Using the International Tree-Ring Data Bank (ITRDB) records as century-long benchmarks for global land-surface models Geoscientific Model Development, 2021, 14, 9
      • Petrescu, Ana Maria Roxana, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet et al. The consolidated European synthesis of CO 2 emissions and removals for the European Union and United Kingdom: 1990–2018 Earth System Science Data, 2021, 13, 5
      • Mizuochi, H., Ducharne, A., Cheruy, F., Ghattas, J., Al-Yaari, A., Wigneron, J.-P., Bastrikov, V., Peylin, P., Maignan, F., and Vuichard, N. Multivariable evaluation of land surface processes in forced and coupled modes reveals new error sources to the simulated water cycle in the IPSL (Institute Pierre Simon Laplace) climate model Hydrol. Earth Syst. Sci., 2021, 25, 2199–2221
      • Zhang, Y., Ciais, P., Boucher, O., Maignan, F., Bastos, A., Goll, D., Lurton, T., Viovy, N., Bellouin, N. & Li, L. Disentangling the impacts of anthropogenic aerosols on terrestrial carbon cycle during 1850-2014 Earth’s Future, 2021.
      • Zhang, Y., Boucher, O., Ciais, P., Li, L., & Bellouin, N. How to reconstruct aerosol-induced diffuse radiation scenario for simulating GPP in land surface models? An evaluation of reconstruction methods with ORCHIDEE_DFv1.0_DFforc Geoscientific Model Development, 2021, 14, 2029–2039
      • Chen, X., Ciais, P., Maignan, F., Zhang, Y., Bastos, A., Bacour, C., Gentine, P., Goll, D., Fan, L., Kim, H., Li, L., Liu, L., Liu, Y., Peng, S., Tang, H., Viovy, N., Wigneron, J.P., Wu, J., Yuan, W. & Zhang, H. Vapor Pressure Deficit and Sunlight Explain Seasonality of Leaf Phenology and Photosynthesis Across Amazonian Evergreen Broadleaved Forest Global Biogeochemical Cycles, 2021, 35
      • Maignan, F., Abadie, C., Remaud, M., Kooiijmans, L. M. J., Kohonen, K.-M., Commane, R., Wehr, R., Campbell, J. E., Belviso, S., Montzka, S. A., Raoult, N., Seibt, U., Shiga, Y. P., Vuichard, N., Whelan, M. E. & Peylin, P. Carbonyl Sulfide: Comparing a Mechanistic Representation of the Vegetation Uptake in a Land Surface Model and the Leaf Relative Uptake Biogeosciences, 2021, 18, 2917–2955
      • Qiu, C., Ciais, P., Zhu, D., Guenet, B., Peng, S., Petrescu, A.M.R., Lauerwald, R., Makowski, D., Gallego-Sala, A. V., Charman, D.J. & Brewer, S.C. Large historical carbon emissions from cultivated northern peatlands Science Advances, 2021, 7


      • Tafasca, Salma, Agnès Ducharne, and Christian Valentin Weak sensitivity of the terrestrial water budget to global soil texture maps in the ORCHIDEE land surface model Hydrology and Earth System Sciences, 2020, 24, 7
      • Macbean, Natasha, Russell L. Scott, Joel A. Biederman, Catherine Ottlé, Nicolas Vuichard, Agnès Ducharne, Thomas Kolb, Sabina Dore, Marcy Litvak, and David JP Moore Testing water fluxes and storage from two hydrology configurations within the ORCHIDEE land surface model across US semi-arid sites Hydrology and Earth System Sciences, 2020, 24, 11
      • Zhang, Yuan, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti et al. Modeling the impacts of diffuse light fraction on photosynthesis in ORCHIDEE (v5453) land surface model Geoscientific Model Development, 2020, 13, 11
      • Schrapffer, Anthony, Anna Sörensson, Jan Polcher, and Lluís Fita Benefits of representing floodplains in a Land Surface Model: Pantanal simulated with ORCHIDEE CMIP6 version Climate Dynamics, 2020, 55
      • Yin, Z., X. H. Wang, C. Ottlé, F. Zhou, M. Guimberteau, J. Polcher, S. S. Peng et al. Improvement of the irrigation scheme in the ORCHIDEE land surface model and impacts of irrigation on regional water budgets over China Journal of advances in modeling earth systems, 2020, 12, 4
      • Raoult, N., Ottlé, C., Peylin, P., Bastrikov, V., and Maugis, P. Evaluating and Optimising Surface Soil Moisture drydowns in the ORCHIDEE land-surface model Journal of Hydrometeorology, 2020, 22, 4
      • Boucher O, Servonnat J, and al. Presentation and evaluation of the IPSL-CM6A-LR climate model Journal of Advances in Modeling Earth Systems, 2020, 12
      • Bowring, S. P. K., Lauerwald, R., Guenet, B., Zhu, D., Guimberteau, M., Regnier, P., Tootchi, A., Ducharne, A., and Ciais, P. ORCHIDEE MICT-LEAK (r5459), a global model for the production, transport, and transformation of dissolved organic carbon from Arctic permafrost regions – Part 2: Model evaluation over the Lena River basin Geosci. Model Dev., 2020, 13, 507–520
      • Vuichard, N., Messina, P., Luyssaert, S., Guenet, B., Zaehle, S., Ghattas, J., Bastrikov, V. and Peylin, P. Accounting for carbon and nitrogen interactions in the global terrestrial ecosystem model ORCHIDEE (trunk version, rev 4999): multi-scale evaluation of gross primary production Geosci. Model Dev., 2020, 12, 11
      • Ciais, P., Yao, Y., Gasser, T., Baccini, A., Wang, Y., Lauerwald, R., Peng, S., Bastos, A., Li, W., Raymond, P. A., Canadell, J. G., Peters, G. P., Andres, R. J., Chang, J., Yue, C., Dolman, A. J., Haverd, V., Hartmann, J., Laruelle, G., Konings, A. G., King, A. W., Liu, Y., Luyssaert, S., Maignan, F., Patra, P. K., Peregon, A., Regnier, P., Pongratz, J., Poulter, B., Shvidenko, A., Valentini, R., Wang, R., Broquet, G., Yin, Y., Zscheischler, J., Guenet, B., Goll, D. S., Ballantyne, A.-P., Yang, H., Qiu, C. & Zhu, D. Empirical estimates of regional carbon budgets imply reduced global soil heterotrophic respiration National Science Review, 2020



      • Vuichard, Nicolas, Palmira Messina, Sebastiaan Luyssaert, Bertrand Guenet, Sönke Zaehle, Josefine Ghattas, Vladislav Bastrikov, and Philippe Peylin Accounting for carbon and nitrogen interactions in the global terrestrial ecosystem model ORCHIDEE (trunk version, rev 4999): multi-scale evaluation of gross primary production Geoscientific Model Development, 2019, 12, 11
      • Druel, Arsène, Philippe Ciais, Gerhard Krinner, and Philippe Peylin Modeling the vegetation dynamics of northern shrubs and mosses in the ORCHIDEE land surface model Journal of Advances in Modeling Earth Systems, 2019, 11, 7
      • Qiu, Chunjing, Dan Zhu, Philippe Ciais, Bertrand Guenet, Shushi Peng, Gerhard Krinner, Ardalan Tootchi, Agnès Ducharne, and Adam Hastie Modelling northern peatland area and carbon dynamics since the Holocene with the ORCHIDEE-PEAT land surface model (SVN r5488) Geoscientific Model Development, 2019, 12, 7
      • Bowring, Simon PK, Ronny Lauerwald, Bertrand Guenet, Dan Zhu, Matthieu Guimberteau, Ardalan Tootchi, Agnès Ducharne, and Philippe Ciais ORCHIDEE MICT-LEAK (r5459), a global model for the production, transport, and transformation of dissolved organic carbon from Arctic permafrost regions–Part 1: Rationale, model description, and simulation protocol Geoscientific Model Development, 2019, 12,8
      • Camino‐Serrano, Marta, Marwa Tifafi, Jérôme Balesdent, Christine Hatté, Josep Peñuelas, Sophie Cornu, and Bertrand Guenet Including stable carbon isotopes to evaluate the dynamics of soil carbon in the land‐surface model ORCHIDEE Journal of advances in modeling earth systems, 2019, 11, 11
      • Tootchi, A., Jost, A., and Ducharne, A. Multi-source global wetland maps combining surface water imagery and groundwater constraints Earth Syst. Sci. Data, 2019 11, 189–220
      • Zhu, D., Ciais, P., Krinner, G., Maignan, F., Jornet-Puig, A. & Hugelius, G. Controls of soil organic matter on permafrost thermal and carbon dynamics Nature Communications, 2019, 10, 1
      • Peaucelle, M., Ciais, P., Maignan, F., Nicolas, M., Cecchini, S. & Viovy, N. Calibrating a new coniferous phenology model in the global model ORCHIDEE: impacts on leaf area index dynamic and carbon fluxes Agricultural and Forest Meteorology, 2019, 266, 97-108,
      • Bacour, C., Maignan, F., MacBean, N., Porcar-Castell, A., Flexas, J., Frankenberg, C., Peylin, P., Chevallier F., Vuichard, N. & Bastrikov, V. Improving estimates of Gross Primary Productivity by assimilating solar-induced fluorescence satellite retrievals in a terrestrial biosphere model using a process-based SIF model Journal of Geophysical Research – Biogeosciences, 2019
      • Peaucelle M, Bacour C, Ciais P, et al. Covariations between plant functional traits emerge from constraining parameterization of a terrestrial biosphere model Global Ecol Biogeogr., 2019, 00, 1–15



      • Camino-Serrano, M.; Guenet, B.; Luyssaert, S.; Ciais, P.; Bastrikov, V.; De Vos, B.; Gielen, B.; Gleixner, G.; Jornet-Puig, A.; Kaiser, K.; Kothawala, D.; Lauerwald, R.; Penuelas, J.; Schrumpf, M.; Vicca, S.; Vuichard, N.; Walmsley, D. & Janssens, I. A. ORCHIDEE-SOM: modeling soil organic carbon (SOC) and dissolved organic carbon (DOC) dynamics along vertical soil profiles in Europe Geosci. Model Dev., 2018, 11, 937
      • Guimberteau, M.; Zhu, D.; Maignan, F.; Huang, Y.; Chao, Y.; Dantec-Nédélec, S.; Ottlé, C.; Jornet-Puig, A.; Bastos, A.; Laurent, P.; Goll, D.; Bowring, S.; Chang, J.; Guenet, B.; Tifafi, M.; Peng, S.; Krinner, G.; Ducharne, A.; Wang, F.; Wang, T.; Wang, X.; Wang, Y.; Yin, Z.; Lauerwald, R.; Joetzjer, E.; Qiu, C.; Kim, H. & Ciais, P. ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation Geosci. Model Dev., 2018, 11, 121-163
      • Qiu, C.; Zhu, D.; Ciais, P.; Guenet, B.; Krinner, G.; Peng, S.; Aurela, M.; Bernhofer, C.; Brümmer, C.; Bret-Harte, S.; Chu, H.; Chen, J.; Desai, A. R.; Dušek, J.; Euskirchen, E. S.; Fortuniak, K.; Flanagan, L. B.; Friborg, T.; Grygoruk, M.; Gogo, S.; Grünwald, T.; Hansen, B. U.; Holl, D.; Humphreys, E.; Hurkuck, M.; Kiely, G.; Klatt, J.; Kutzbach, L.; Largeron, C.; Laggoun-Défarge, F.; Lund, M.; Lafleur, P. M.; Li, X.; Mammarella, I.; Merbold, L.; Nilsson, M. B.; Olejnik, J.; Ottosson-Löfvenius, M.; Oechel, W.; Parmentier, F.-J. W.; Peichl, M.; Pirk, N.; Peltola, O.; Pawlak, W.; Rasse, D.; Rinne, J.; Shaver, G.; Schmid, H. P.; Sottocornola, M.; Steinbrecher, R.; Sachs, T.; Urbaniak, M.; Zona, D. & Ziemblinska, K. ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO 2, water, and energy fluxes on daily to annual scales Geosci. Model Dev., 2018, 11, 497-519
      • Raoult, Nina, Bertrand Delorme, Catherine Ottlé, Philippe Peylin, Vladislav Bastrikov, Pascal Maugis, and Jan PolcherConfronting soil moisture dynamics from the ORCHIDEE land surface model with the ESA-CCI product: Perspectives for data assimilationRemote Sensing, 2018, 10, 11
      • Bastrikov, Vladislav, Natasha MacBean, Cédric Bacour, Diego Santaren, Sylvain Kuppel, and Philippe Peylin 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) Geosci. Model Dev., 2018, 11, 12
      • Nguyen-Quang, Trung, Jan Polcher, Agnès Ducharne, Thomas Arsouze, Xudong Zhou, Ana Schneider, and Lluís Fita ORCHIDEE-ROUTING: revising the river routing scheme using a high-resolution hydrological databaseGeosci. Model Dev., 2018, 11, 12



      • Barella-Ortiz, A.; Polcher, J.; de Rosnay, P.; Piles, M. & Gelati, E. Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula Hydrol. Earth Syst. Sci. Dis., Copernicus GmbH, 2017, 21, 357-375
      • Dantec-Nédélec, S.; Ottlé, C.; Wang, T.; Guglielmo, F.; Maignan, F.; Delbart, N.; Valdayskikh, V.; Radchenko, T.; Nekrasova, O.; Zakharov, V. and Jouzel J. Testing the capability of ORCHIDEE land surface model to simulate arctic ecosystems: Sensitivity analysis and site-level model calibration J. Adv. Model. Earth Syst., 2017, 9, 1212-1230
      • Druel, A.; Peylin, P.; Krinner, G.; Ciais, P.; Viovy, N.; Peregon, A.; Bastrikov, V.; Kosykh, N. & Mironycheva-Tokareva, N. Towards a more detailed representation of high-latitude vegetation in the global land surface model ORCHIDEE (ORC-HL-VEGv1.0) Geosci. Model Dev., 2017, 10, 4693-4722
      • Getirana A, Boone A, Peugeot C, and the ALMIP2 working group (2017). Streamflows over a West African basin from the ALMIP-2 model ensemble. J. Hydrometeorology, 18, 1831-1845, doi:10.1175/JHM-D-16-0233.1
      • Goll, D. S.; Vuichard, N.; Maignan, F.; Jornet-Puig, A.; Sardans, J.; Violette, A.; Peng, S.; Sun, Y.; Kvakic, M.; Guimberteau, M.; Guenet, B.; Zaehle, S.; Penuelas, J.; Janssens, I. A. & Ciais, P. A representation of the phosphorus cycle for ORCHIDEE (revision 4520) Geosci. Model Dev., Copernicus, 2017, 10, 3745-3770
      • Grippa, Kergoat, Boone, Peugeot, Demarty, Cappelaere, Gal, Hiernaux, Mougin, Ducharne, Dutra, Anderson, Hain, and the ALMIP2 working group (2017). Modelling surface runoff and water fluxes over contrasted soils in pastoral Sahel: evaluation of the ALMIP2 land surface models over the Gourma region in Mali. J. Hydrometeorology, 18, 1847- 1866, doi:10.1175/JHM-D-16-0170.1
      • Guimberteau M., Ciais P., Ducharne A., Boisier J. P., Aguiar A. P., Biemans H., De Deurwaerder H., Galbraith D., Kruijt B., Langerwisch F., Poveda G., Rammig A., Rodriguez D. A., Tejada G., Thonicke K., Von Randow C., Von Randow R. C. S., Zhang K. and Verbeeck H. (2017): Impacts of future deforestation and climate change on the hydrology of the Amazon basin: a multi-model analysis with a new set of land-cover change scenarios, Hydrol. Earth Syst. Sci., 21, 1455-1475, doi:10.5194/hess-21-1455-2017
      • Largeron, C.; Krinner, G.; Ciais, P. & Brutel-Vuilmet, C. Implementing northern peatlands in a global land surface model: description and evaluation in the ORCHIDEE high latitude version model (ORC-HL-PEAT) Geosci. Model Dev. Discuss., 2017, 1-26Lauerwald R., Regnier P., Camino-Serrano M., Guenet B., Guimberteau M., Ducharne A., Polcher J., and Ciais P. (2017): ORCHILEAK (revision 3875): a new model branch to simulate carbon transfers along the terrestrial-aquatic continuum of the Amazon basin, Geosci. Model Dev., 10.5194/gmd-10-3821-2017
      • Wang F, Ducharne A, Cheruy F, Lo MH, Grandpeix JL (2017). Impact of a shallow groundwater table on the global water cycle in the IPSL land-atmosphere coupled model, Climate Dynamics, doi:10.1007/s00382-017-3820-9
      • Zhao F., Veldkamp T., Frieler K., Schewe, J., Ostberg S., Willner S., Schauberger B., Gosling S., Müller Schmied H., Portmann F., Leng G., Huang M., Liu X., Tang Q., Hanasaki N., Biemans H., Gerten D., Satoh Y., Pokhrel Y., Stacke T., Ciais P., Ducharne A., Guimberteau M., Wada Y., Kim H. and Yamazaki D. The critical role of the routing scheme in simulating peak river discharge in global hydrological models, Environ. Res. Lett., 12 (2017) 075003, doi: 10.1088/1748-9326/aa7250



      • Chen, Y.; Ryder, J.; Bastrikov, V.; McGrath, M. J.; Naudts, K.; Otto, J.; Ottlé, C.; Peylin, P.; Polcher, J.; Valade, A.; Black, A.; Elbers, J. A.; Moors, E.; Foken, T.; van Gorsel, E.; Haverd, V.; Heinesch, B.; Tiedemann, F.; Knohl, A.; Launiainen, S.; Loustau, D.; Ogée, J.; Vessala, T. & Luyssaert, S.  Evaluating the performance of land surface model ORCHIDEE-CAN v1. 0 on water and energy flux estimation with a single-and multi-layer energy budget scheme Geosci. Model Dev., 2016, 9, 2951-2972
      • Guenet, B.; Moyano, F. E.; Peylin, P.; Ciais, P. & Janssens, I. A. Towards a representation of priming on soil carbon decomposition in the global land biosphere model ORCHIDEE (version 1.9. 5.2) Geosci. Model Dev., 2016, 9, 841-855
      • Johnson M.O., Galbraith D., Gloor E., De Deurwaerder H., Guimberteau M., Rammig A., Thonicke K., Verbeeck H., von Randow C., Brienen R.J.W., Feldpausch T.R., Lopez Gonzalez G., Monteagudo A., Phillips O.L., Quesada C.A., Christoffersen B., Ciais P., Gilvan S., Kruijt B., Meir P., Moorcroft P., Zhang K., Alvarez E.A., Alves de Oliveira A., Amaral I., Andrade A., Aragao L.E.O.C., Araujo-Murakami A., Arets E.J.M.M., Arroyo L., Aymard G.A., Baraloto C., Barroso J., Bonal D., Boot R., Camargo J., Chave J., Cogollo A., Cornejo Valverde F., da Costa L., di Fiore A., Higuchi N., Honorio E., Killeen T.J., Laurance S.G., Laurance W.F., Licona J., Lovejoy T., Malhi Y., Marimon B., Marimon Junior B., Mendoza C., Neill D.A., Pardo G., Peña-Claros M., Pitman N.C.A., Poorter L., Prieto A., Ramirez-Angulo H., Roopsind A., Rudas A., Salomao R.P., Silveira M., Stropp J., ter Steege H., Terborgh J., Thomas R., Toledo M., Torres-Lezama A., van der Heijden G.M.F., Vasquez R., Vieira I., Vilanova E., Vos V.A. and Baker T.R. (2016): Variation in stem mortality rates determines patterns of aboveground biomass in Amazonian forests: implications for dynamic global vegetation models, Glob. Change Biol., 22, 3996-4013, doi: 10.1111/gcb.13315
      • McGrath, M. J.; Ryder, J.; Pinty, B.; Otto, J.; Naudts, K.; Valade, A.; Chen, Y.; Weedon, J. & Luyssaert, S. A multi-level canopy radiative transfer scheme for ORCHIDEE (SVN r2566), based on a domain-averaged structure factor Geosci. Model Dev. Discuss., 2016
      • Polcher, J.; Piles, M.; Gelati, E.; Barella-Ortiz, A. & Tello, M. Comparing surface-soil moisture from the SMOS mission and the ORCHIDEE land-surface model over the Iberian Peninsula Remote Sens. Environ., Elsevier, 2016, 174, 69-81
      • Risi, C.; Ogee, J.; Bony, S.; Bariac, T.; Yaseef, N. R.; Wingate, L.; Welker, J.; Knohl, A.; Besson, C. K.; Leclerc, M.; Zhang, G.; Buchmann, N.; Santrucek, J.; Hronkova, M.; David, T.; Peylin, P. & Guglielmo, F.  The water isotopic version of the land-surface model ORCHIDEE: Implementation, evaluation, sensitivity to hydrological parameters Hydrol Current Res, 2016, 7, 2
      • Ryder, J.; Polcher, J.; Peylin, P.; Ottlé, C.; Chen, Y.; Gorsel, E. v.; Haverd, V.; McGrath, M.; Naudts, K.; Otto, J.; Valade, A. & Luyssaert, S. A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations Geosci. Model Dev., Copernicus GmbH, 2016, 9, 223-245
      • Wu, X.; Vuichard, N.; Ciais, P.; Viovy, N.; de Noblet-Ducoudré, N.; Wang, X.; Magliulo, V.; Wattenbach, M.; Vitale, L.; Tommasi, P. D.; Moors, E. J.; Jans, W.; Elbers, J.; Ceschia, E.; Tallec, T.; Bernhofer, C.; Grünwald, T.; Moureaux, C.; Manise, T.; Ligne, A.; Cellier, P.; Loubet, B.; Larmanou, E. & Ripoche, D. ORCHIDEE-CROP (v0), a new process based Agro-Land Surface Model: model description and evaluation over Europe Geosci. Model Dev., 2016, 9, 857-873



      • Naudts, K.; Ryder, J.; McGrath, M. J.; Otto, J.; Chen, Y.; Valade, A.; Bellasen, V.; Berhongaray, G.; Bönisch, G.; Campioli, M.; Ghattas, J.; Groote, T. D.; Haverd, V.; Kattge, J.; MacBean, N.; Maignan, F.; Merilä, P.; Penuelas, J.; Peylin, P.; Pinty, B.; Pretzsch, H.; Schulze, E. D.; Solyga, D.; Vuichard, N.; Yan, Y. & Luyssaert, S. A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes Geosci. Model Dev., 2015, 7, 8565-8647
      • Yang H., Piao S., Zeng Z., Ciais P., Yin Y., Friedlingstein P., Sitch S., Ahlström A., Guimberteau M., Huntingford C., Levis S., Levy P., Huang M., Li Y., Li X., Lomas M., Peylin P., Poulter B., Viovy N., Zaehle S., Zeng N., Zhao F. and Wang L. (2015): Multi-criteria evaluation of discharge simulation in Dynamic Global Vegetation Models, J. Geophys. Res.-Atmos., 120, 7488-7505, doi:10.1002/2015JD023129
      • Yue, C.; Ciais, P.; Cadule, P.; Thonicke, K. & Van Leeuwen, T. Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE–Part 2: Carbon emissions and the role of fires in the global carbon balance Geosci. Model Dev., 2015, 8, 1321-1338
      • Zhu, D.; Peng, S. S.; Ciais, P.; Viovy, N.; Druel, A.; Kageyama, M.; Krinner, G.; Peylin, P.; Ottlé, C.; Piao, S. L.; Poulter, B.; Schepaschenko, D. & Shvidenko, A. Improving the dynamics of northern vegetation in the ORCHIDEE ecosystem model Geosci. Model Dev., 2015, 8, 2263-2283



      • Getirana A., Dutra E., Guimberteau M., Kam J., Li H.-Y., Decharme B., Zhang Z., Ducharne A., Boone A., Balsamo G., Rodell M., Toure A. M., Xue Y., Peters-Lidard C., Kumar S., Arsenault K., Drapeau G., Leung L. R., Ronchail J. and Sheffield J. (2014): Water Balance in the Amazon Basin from a Land Surface Model Ensemble, J. Hydrometeorol., 15, 2586-2614, doi:10.1175/JHM-D-14-0068.1
      • Guimberteau M., Ducharne A., Ciais P., Boisier J.P., Peng S., De Weirdt M. and Verbeeck H. (2014): Testing conceptual and physically based soil hydrology schemes against observations for the Amazon Basin, Geosci. Model Dev., 7, 1115-1136, doi:10.5194/gmd-7-1115-2014, 2014
      • Traore, A. K.; Ciais, P.; Vuichard, N.; Poulter, B.; Viovy, N.; Guimberteau, M.; Jung, M.; Myneni, R. & Fisher, J. B. Evaluation of the ORCHIDEE ecosystem model over Africa against 25 years of satellite-based water and carbon measurements J. Geophys. Res.-Biogeo., Wiley-Blackwell, 2014, 119, 1554-1575
      • Yue, C.; Ciais, P.; Cadule, P.; Thonicke, K.; Archibald, S.; Poulter, B.; Hao, W. M.; Hantson, S.; Mouillot, F.; Friedlingstein, P.; Maignan, F. & Viovy, N. Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE–Part 1: simulating historical global burned area and fire regimes Geosci. Model Dev., 2014, 7, 2747-2767



      • Barella-Ortiz, A.; Polcher, J.; Tuzet, A. & Laval, K. Potential evaporation estimation through an unstressed surface-energy balance and its sensitivity to climate change Hydrol. Earth Syst. Sc., 2013, 17, 4625-4639
      • Berg A., De Noblet-Ducoudré N., Sultan B., Lengaigne M. and Guimberteau M. (2013): Projections of climate change impacts on potential C4 crop productivity over tropical regions, Agric. For. Meteorol., 170 (2013) 89-102, doi:10.1016/j.agrformet.2011.12.003
      • Campoy A, Ducharne A, Cheruy F, Hourdin F, Polcher J, Dupont JC (2013). Response of land surface fluxes and precipitation to different soil bottom hydrological conditions in a general circulation model. JGR-Atmospheres, 118, 10,725–10,739, doi:10.1002/jgrd.50627.
      • Chang, J. F.; Viovy, N.; Vuichard, N.; Ciais, P.; Wang, T.; Cozic, A.; Lardy, R.; Graux, A.-I.; Klumpp, K.; Martin, R. & Soussana, J.-F. Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe Geosci. Model Dev., 2013, 6, 2165-2181
      • Cheruy F, Campoy A,  Dupont J-C, Ducharne A, Hourdin F, Haeffelin M, Chiriaco M, Idelkadi A (2013). Combined influence of atmospheric physics and soil hydrology on the simulated meteorology at the SIRTA atmospheric observatory. Climate Dynamics, 40, 2251-2269, doi:10.1007/s00382-012-1469-y.
      • Guenet, B.; Moyano, F.; Vuichard, N.; Kirk, G.; Bellamy, P.; Zaehle, S. & Ciais, P. Can we model observed soil carbon changes from a dense inventory? A case study over England and Wales using three versions of the ORCHIDEE ecosystem model (AR5, AR5-PRIM and O-CN) Geosci. Model Dev., 2013, 6, 2153-2163
      • Guimberteau M., Ronchail J., Espinoza J. C., Lengaigne M., Sultan B., Polcher J., Drapeau G., Guyot J.-L., Ducharne A. and Ciais P. (2013): Future changes in precipitation and impacts on extreme streamflow over Amazonian sub-basins, Environ. Res. Lett., 8 014035, doi:10.1088/1748-9326/8/1/014035
      • Seneviratne S, Wilhelm M, Stanelle T, van den Hurk B, Hagemann S, Berg A, Cheruy F, Higgins ME, Meier A, Brovkin V, Claussen M, Ducharne A, Dufresne JL, Findell K, Ghattas J, Lawrence DM, Malyshev S, Rumukainen M, Smith B (2013). Impact of soil moisture-climate feedbacks on CMIP5 projections: First results from the GLACE-CMIP5 experiment. GRL,40, 5212–5217, doi:10.1002/grl.50956.
      • Sterling S, Ducharne A, Polcher J (2013). The impact of global land-cover change on the terrestrial water cycle. Nature Climate Change, 3, 385-390, doi:10.1038/nclimate1690.
      • Wang, T.; Ottlé, C.; Boone, A.; Ciais, P.; Brun, E.; Morin, S.; Krinner, G.; Piao, S. & Peng, S. Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model J. Geophys. Res.-Atmos., 2013, 118, 6064-6079



      • De Weirdt, M., H. Verbeeck, F. Maignan, P. Peylin, B. Poulter, D. Bonal, P. Ciais, and K. Steppe (2012), Seasonal leaf dynamics for tropical evergreen forests in a process-based global ecosystem model, Geoscientific Model Development, 5(5), 1091-1108 (link)
      • Gouttevin, I., Krinner, G., Ciais, P., Polcher, J., and Legout, C.: Multi-scale validation of a new soil freezing scheme for a land-surface model with physically-based hydrology, Cryosphere, 6, 407-430, DOI 10.5194/tc-6-407-2012 (link)
      • Gouttevin, I., Menegoz, M., Domine, F., Krinner, G., Koven, C., Ciais, P., Tarnocai, C., and Boike, J.: How the insulating properties of snow affect soil carbon distribution in the continental Pan-Arctic area, Journal of Geophysical Research-Biogeosciences, 117, Artn G02020, Doi 10.1029/2011jg001916 (link)
      • Guimberteau, M., Drapeau, G., Ronchail, J., Sultan, B., Polcher, J., Martinez, J. M., Prigent, C., Guyot, J. L., Cochonneau, G., Espinoza, J. C., Filizola, N., Fraizy, P., Lavado, W., De Oliveira, E., Pombosa, R., Noriega, L., and Vauchel, P.: Discharge simulation in the sub-basins of the Amazon using ORCHIDEE forced by new datasets, Hydrology and Earth System Sciences, 16, 911-935, DOI 10.5194/hess-16-911-2012 (link)
      • Kuppel, S., Peylin, P., Chevallier, F., Bacour, C., Maignan, F., and Richardson, A. D.: Constraining a global ecosystem model with multi-site eddy-covariance data, Biogeosciences, 9, 3757-3776, DOI 10.5194/bg-9-3757-2012 (link)
      • Lafont, S., Zhao, Y., Calvet, J. C., Peylin, P., Ciais, P., Maignan, F., and Weiss, M.: Modelling LAI, surface water and Carbon fluxes at high-resolution over France: Comparison of ISBA-A-gs and ORCHIDEE, Biogeosciences, 9, 439-456, DOI 10.5194/bg-9-439-2012 (link)
      • Luyssaert, S., Abril, G., Andres, R., Bastviken, D., Bellassen, V., Bergamaschi, P., Bousquet, P., Chevallier, F., Ciais, P., Corazza, M., Dechow, R., Erb, K.-H., Etiope, G., Fortems-Cheiney, a., Grassi, G., Hartmann, J., Jung, M., Lathière, J., Lohila, a., Mayorga, E., Moosdorf, N., Njakou, D. S., Otto, J., Papale, D., Peters, W., Peylin, P., Raymond, P., Rödenbeck, C., Saarnio, S., Schulze, E.-D., Szopa, S., Thompson, R., Verkerk, P. J., Vuichard, N., Wang, R., Wattenbach, M., and Zaehle, S.: The European land and inland water CO2, CO, CH4 and N2O balance between 2001 and 2005, Biogeosciences, 9, 3357-3380, 10.5194/bg-9-3357-2012 (link)
      • Ringeval, B., Decharme, B., Piao, S. L., Ciais, P., Papa, F., de Noblet-Ducoudre, N., Prigent, C., Friedlingstein, P., Gouttevin, I., Koven, C., and Ducharne, A.: Modelling sub-grid wetland in the ORCHIDEE global land surface model: Evaluation against river discharges and remotely sensed data, Geoscientific Model Development, 5, 941-962, DOI 10.5194/gmd-5-941-2012 (link)
      • Zhao, Y., Ciais, P., Peylin, P., Viovy, N., Longdoz, B., Bonnefond, J. M., Rambal, S., Klumpp, K., Olioso, A., Cellier, P., Maignan, F., Eglin, T., and Calvet, J. C.: How errors on meteorological variables impact simulated ecosystem fluxes: A case study for six French sites, Biogeosciences, 9, 2537-2564, DOI 10.5194/bg-9-2537-2012 (link)
      • Guimberteau M., Perrier A., Laval K. and Polcher J. (2012): A comprehensive approach to analyze discrepancies between land surface models and in-situ measurements: a case study over the US and Illinois with SECHIBA forced by NLDAS, Hydrol. Earth Syst. Sci., 16, 3973-3988, doi:10.5194/hess-16-3973-2012
      • Guimberteau M., Laval K., Perrier A. and Polcher J. (2012): Global effect of irrigation and its impact on the onset of the Indian summer monsoon, Clim. Dyn., 39:1329-1348, doi:10.1007/s00382-011-1252-5



      • Anav, A., Menut, L., Khvorostyanov, D., and Viovy, N.: Impact of tropospheric Ozone on the Euro-Mediterranean vegetation, Global Change Biology, 17, 2342-2359, DOI 10.1111/j.1365-2486.2010.02387.x (link)
      • Bellassen, V., le Maire, G., Guin, O., Dhote, J. F., Ciais, P., and Viovy, N.: Modelling forest management within a global vegetation model-part 2: Model validation from a tree to a continental scale, Ecological Modelling, 222, 57-75, DOI 10.1016/j.ecolmodel.2010.08.038 (link)
      • Bellassen, V., Viovy, N., Luyssaert, S., le Maire, G., Schelhaas, M. J., and Ciais, P.: Reconstruction and attribution of the Carbon sink of European forests between 1950 and 2000, Global Change Biology, 17, 3274-3292, doi: 10.1111/j.1365-2486.2011.02476.x (link)
      • Koven, C. D., Ringeval, B., Friedlingstein, P., Ciais, P., Cadule, P., Khvorostyanov, D., Krinner, G., and Tarnocai, C.: Permafrost Carbon-climate feedbacks accelerate global warming, Proceedings of the National Academy of Sciences of the United States of America, 108, 14769-14774, DOI 10.1073/pnas.1103910108 (link)
      • Maignan, F., Bréon, F.M., Chevallier, F., Viovy, N., Ciais, P., Trules, J. & Mancip, M. (2011). Evaluation of a Global Vegetation Model using time series of satellite vegetation indices. Geoscientific Model Development, 4, 1103–1114, doi:10.5194/gmd-4-1103-2011 (link)
      • Verbeeck, H., Peylin, P., Bacour, C., Bonal, D., Steppe, K., and Ciais, P.: Seasonal patterns of CO2 fluxes in Amazon forests: Fusion of eddy covariance data and the ORCHIDEE model, Journal of Geophysical Research-Biogeosciences, 116, Artn G02018, Doi 10.1029/2010jg001544 (link)
      • Woillez, M. N., Kageyama, M., Krinner, G., de Noblet-Ducoudre, N., Viovy, N., and Mancip, M.: Impact of CO2 and climate on the last glacial maximum vegetation: Results from the ORCHIDEE/IPSL models, Climate of the Past, 7, 557-577, DOI 10.5194/cp-7-557-2011 (link)


      • Alkama, R., Kageyama, M., and Ramstein, G.: Relative contributions of climate change, stomatal closure, and leaf area index changes to 20th and 21st century runoff change: A modelling approach using the organizing Carbon and Hydrology in dynamic ecosystems (ORCHIDEE) land surface model, Journal of Geophysical Research-Atmospheres, 115, Artn D17112, Doi 10.1029/2009jd013408 (link)
      • Bellassen, V., Le Maire, G., Dhote, J. F., Ciais, P., and Viovy, N.: Modelling forest management within a global vegetation model part 1: Model structure and general behaviour, Ecological Modelling, 221, 2458-2474, DOI 10.1016/j.ecolmodel.2010.07.008 (link)
      • Cadule, P., Friedlingstein, P., Bopp, L., Sitch, S., Jones, C. D., Ciais, P., Piao, S. L., and Peylin, P.: Benchmarking coupled climate-carbon models against long-term atmospheric CO2 measurements, Global Biogeochemical Cycles, 24, Doi 10.1029/2009gb003556 (link)
      • Ciais, P., Wattenbach, M., Vuichard, N., Smith, P. C., Piao, S. L., Don, A., Luyssaert, S., Janssens, I. A., Bondeau, A., Dechow, R., Leip, A., Beer, C., van der Werf, G. R., Gervois, S., Van Oost, K., Tomelleri, E., Freibauer, A., Schulze, E. D., and Team, C.-I. S. t.: The European Carbon balance. Part 2: Croplands, Global Change Biology, 16, 1409-1428, 10.1111/j.1365-2486.2009.02055.x (link)
      • Delbart, N., Ciais, P., Chave, J., Viovy, N., Malhi, Y., and Le Toan, T.: Mortality as a key driver of the spatial distribution of above-ground biomass in Amazonian forest: Results from a Dynamic Vegetation Model, Biogeosciences, 7, 3027-3039, DOI 10.5194/bg-7-3027-2010 (link)
      • Luyssaert, S., Ciais, P., Piao, S. L., Schulze, E. D., Jung, M., Zaehle, S., Schelhaas, M. J., Reichstein, M., Churkina, G., Papale, D., Abril, G., Beer, C., Grace, J., Loustau, D., Matteucci, G., Magnani, F., Nabuurs, G. J., Verbeeck, H., Sulkava, M., van der Werf, G. R., Janssens, I. A., and Team, C.-I. S. t.: The European Carbon balance. Part 3: Forests, Global Change Biology, 16, 1429-1450, 10.1111/j.1365-2486.2009.02056.x (link)
      • Ringeval, B., de Noblet-Ducoudre, N., Ciais, P., Bousquet, P., Prigent, C., Papa, F., and Rossow, W. B.: An attempt to quantify the impact of changes in wetland extent on Methane emissions on the seasonal and interannual time scales, Global Biogeochemical Cycles, 24, Artn Gb2003, Doi 10.1029/2008gb003354 (link)
      • Risi, C., Bony, S., Vimeux, F., Frankenberg, C., Noone, D., and Worden, J.: Understanding the Sahelian water budget through the isotopic composition of water vapor and precipitation, Journal of Geophysical Research-Atmospheres, 115, Artn D24110, Doi 10.1029/2010jd014690 (link)
      • Smith, P. C., Ciais, P., Peylin, P., De Noblet-Ducoudre, N., Viovy, N., Meurdesoif, Y., and Bondeau, A.: European-wide simulations of croplands using an improved terrestrial biosphere model: 2. Interannual yields and anomalous CO2 fluxes in 2003, Journal of Geophysical Research-Biogeosciences, 115, Doi 10.1029/2009jg001041 (link)
      • Tan, K., Ciais, P., Piao, S. L., Wu, X. P., Tang, Y. H., Vuichard, N., Liang, S., and Fang, J. Y.: Application of the ORCHIDEE global vegetation model to evaluate biomass and soil Carbon stocks of Qinghai-Tibetan grasslands, Global Biogeochemical Cycles, 24, Artn Gb1013, Doi 10.1029/2009gb003530 (link)
      • Zaehle, S., and Friend, A. D.: Carbon and nitrogen cycle dynamics in the O-CN land surface model: 1. Model description, site-scale evaluation, and sensitivity to parameter estimates, Global Biogeochemical Cycles, 24, Artn Gb1005, Doi 10.1029/2009gb003521 (link)
      • Zaehle, S., Friend, A. D., Friedlingstein, P., Dentener, F., Peylin, P., and Schulz, M.: Carbon and Nitrogen cycle dynamics in the O-CN land surface model: 2. Role of the nitrogen cycle in the historical terrestrial Carbon balance, Global Biogeochemical Cycles, 24, Doi 10.1029/2009gb003522 (link)



      • Colleoni, F., Krinner, G., and Jakobsson, M.: Sensitivity of the Late Saalian (140 kyrs BP) and LGM (21 kyrs BP) Eurasian ice sheet surface mass balance to vegetation feedbacks, Geophysical Research Letters, 36, L08704, 10.1029/2009gl037200 (link)
      • Jost, A., Fauquette, S., Kageyama, M., Krinner, G., Ramstein, G., Sue, J. P., and Violette, S.: High resolution climate and vegetation simulations of the late Pliocene, a model-data comparison over western Europe and the Mediterranean region, Climate of the Past, 5, 585-606 (link)
      • Koven, C., Friedlingstein, P., Ciais, P., Khvorostyanov, D., Krinner, G., and Tarnocai, C.: On the formation of high-latitude soil carbon stocks: Effects of cryoturbation and insulation by organic matter in a land surface model, Geophysical Research Letters, 36, L21501, 10.1029/2009gl040150 (link)
      • Piao, S. L., Fang, J. Y., Ciais, P., Peylin, P., Huang, Y., Sitch, S., and Wang, T.: The Carbon balance of terrestrial ecosystems in China, Nature, 458, 1009-U1082, Doi 10.1038/Nature07944 (link)
      • Piao, S. L., Friedlingstein, P., Ciais, P., Peylin, P., Zhu, B., and Reichstein, M.: Footprint of temperature changes in the temperate and boreal forest carbon balance, Geophysical Research Letters, 36, Artn L07404, Doi 10.1029/2009gl037381 (link)
      • Rosnay, P. de, Drusch, M., Boone, A., Balsamo, G., Decharme, B., Harris, P., Kerr, Y., Pellarin, T., Polcher, J., and Wigneron, J.-P. (2009).: AMMA Land Surface Model Intercomparison Experiment coupled to the Community Microwave Emission Model: ALMIP-MEM. Journal of Geophysical Research, Volume 114, Issue D5, 16 March 2009 (link)
      • Werth, S., Güntner, A., Petrovic, S., and Schmidt, R. (2009). : Integration of GRACE mass variations into a global hydrological model.Earth and Planetary Science Letters, 277(1-2), 166–173. (link)



      • Abramowitz, Gab, Leuning, Ray, Clark, Martyn, and Pitman, Andy (2008). Evaluating the Performance of Land Surface Models. Journal of Climate, 21(21), 5468–5481. (link)
      • Ciais, P., Schelhaas, M. J., Zaehle, S., Piao, S. L., Cescatti, A., Liski, J., Luyssaert, S., Le-Maire, G., Schulze, E. D., Bouriaud, O., Freibauer, A., Valentini, R., and Nabuurs, G. J.: Carbon accumulation in European forests, Nature Geoscience, 1, 425-429 (link)
      • Ciais, P., Piao, S.-L., Cadule, P., Friedlingstein, P., and Chédin, A. (2008). Variability and recent trends in the African carbon balance. Biogeosciences Discuss., 5(4), 3497–3532. (link)
      • Gervois, Sébastien, Ciais, Philippe, Noblet-Ducoudré, Nathalie de, Brisson, Nadine, Vuichard, Nicolas, and Viovy, Nicolas (2008). Carbon and water balance of European croplands throughout the 20th century. Global Biogeochemical Cycles, Volume 22, Issue 2, June 2008 (link)
      • Hollingsworth, A., Engelen, R. J., Textor, C., Benedetti, A., Boucher, O., Chevallier, F., Dethof, A., Elbern, H., Eskes, H., Flemming, J., Granier, C., Kaiser, J. W., Morcrette, J.-J., Rayner, P., Peuch, V.-H., Rouil, L., Schultz, M. G., and Simmons, A. J. (2008). Toward a Monitoring and Forecasting System For Atmospheric Composition: The GEMS Project. Bulletin of the American Meteorological Society, 89(8), 1147–1164. (link)
      • d’Orgeval, T., and Polcher, J.: Impacts of precipitation events and land-use changes on West African river discharges during the years 1951-2000, Climate Dynamics, 31, 249-262, DOI 10.1007/s00382-007-0350-x (link)
      • d’Orgeval, T., Polcher, J., and de Rosnay, P.: Sensitivity of the West African hydrological cycle in ORCHIDEE to infiltration processes, Hydrology and Earth System Sciences, 12, 1387-1401 (link)
      • Khvorostyanov, D. V., Ciais, P., Krinner, G., and Zimov, S. A.: Vulnerability of East Siberia’s frozen carbon stores to future warming, Geophysical Research Letters, 35, L10703, 10.1029/2008gl033639 (link)
      • Piao, S. L., Ciais, P., Friedlingstein, P., Peylin, P., Reichstein, M., Luyssaert, S., Margolis, H., Fang, J. Y., Barr, A., Chen, A. P., Grelle, A., Hollinger, D. Y., Laurila, T., Lindroth, A., Richardson, A. D., and Vesala, T.: Net Carbon Dioxide losses of northern ecosystems in response to autumn warming, Nature, 451, 49-U43, Doi 10.1038/Nature06444 (link)
      • Richardson, A. D., Mahecha, M. D., Falge, E., Kattge, J., Moffat, A. M., Papale, D., Reichstein, M., Stauch, V. J., Braswell, B. H., and Churkina, G. (2008). Statistical properties of random CO2 flux measurement uncertainty inferred from model residuals. Agricultural and Forest Meteorology, 148(1), 38–50.
      • Sterling, S., and Ducharne, A.: Comprehensive data set of global land cover change for land surface model applications, Global Biogeochemical Cycles, 22, Artn Gb3017, Doi 10.1029/2007gb002959 (link)
      • Vetter, M., Churkina, G., Jung, M., Reichstein, M., Zaehle, S., Bondeau, A., Chen, Y., Ciais, P., Feser, F., Freibauer, A., Geyer, R., Jones, C., Papale, D., Tenhunen, J., Tomelleri, E., Trusilova, K., Viovy, N., and Heimann, M. (2008). Analyzing the causes and spatial pattern of the European 2003 carbon flux anomaly using seven models. Biogeosciences, 5(2), 561–583. (link)
      • Weber, U., Jung, M., Reichstein, M., Beer, C., Braakhekke, M., Lehsten, V., Ghent, D., Kaduk, J., Viovy, N., Ciais, P., Gobron, N., and Rödenbeck, C. (2008). The inter-annual variability of Africa’s ecosystem productivity: a multi-model analysis. Biogeosciences Discuss., 5(5), 4035–4069. (link)


      • Abramowitz, Gab, Pitman, Andy, Gupta, Hoshin, Kowalczyk, Eva, and Wang, Yingping (2007). Systematic Bias in Land Surface Models.Journal of Hydrometeorology, 8(5), 989–1001. (link)
      • Canadell, Josep G., Quér\’e, Corinne Le, Raupach, Michael R., Field, Christopher B., Buitenhuis, Erik T., Ciais, Philippe, Conway, Thomas J., Gillett, Nathan P., Houghton, R. A., and Marland, Gregg (2007). Contributions to accelerating atmospheric CO2 growth from economic (link)activity, carbon intensity, and efficiency of natural sinks. Proceedings of the National Academy of Sciences, 104(47), 18866–18870. (link)
      • Davin, E. L., Noblet-Ducoudré, N. de, and Friedlingstein, P. Impact of land cover change on surface climate: Relevance of the radiative forcing concept. Geophysical Research Letters. Volume 34, Issue 13, 16 July 2007 (link)
      • Demarty, J., Chevallier, F., Friend, A. D., Viovy, N., Piao, S., and Ciais, P.: Assimilation of global MODIS leaf area index retrievals within a terrestrial biosphere model, Geophysical Research Letters, 34, Artn L15402, Doi 10.1029/2007gl030014 (link)
      • Friend, AD, Arneth, A, Kiang, NY, Lomas, M, Ogee, J, Rodenbeckk, C, Running, SW, Santaren, JD, Sitch, S, Viovy, N, Woodward, FI, and Zaehle, S (2007). FLUXNET and modelling the global carbon cycle.Global change Biology, 13(3), 610–633.
      • Jung, M., Le Maire, G., Zaehle, S., Luyssaert, S., Vetter, M., Churkina, G., Ciais, P., Viovy, N., and Reichstein, M.: Assessing the ability of three land ecosystem models to simulate gross carbon uptake of forests from boreal to Mediterranean climate in Europe, Biogeosciences, 4, 647-656 (link)
      • Jung, Martin, Vetter, Mona, Herold, Martin, Churkina, Galina, Reichstein, Markus, Zaehle, Soenke, Ciais, Philippe, Viovy, Nicolas, Bondeau, Alberte, Chen, Youmin, Trusilova, Kristina, Feser, Frauke, and Heimann, Martin . Uncertainties of modeling gross primary productivity over Europe: A systematic study on the effects of using different drivers and terrestrial biosphere models. Global Biogeochemical Cycles Volume 21, Issue 4, December 2007 (link)
      • Ngo-Duc, T., Laval, K., Ramillien, G., Polcher, J., and Cazenave, A.: Validation of the land water storage simulated by organising Carbon and Hydrology in dynamic ecosystems (ORCHIDEE) with gravity recovery and climate experiment (GRACE) data, Water Resources Research, 43, Artn W04427, Doi 10.1029/2006wr004941 (link)
      • Piao, Shilong, Friedlingstein, Pierre, Ciais, Philippe, Noblet-Ducoudré, Nathalie de, Labat, David, and Zaehle, Sönke (2007).Changes in climate and land use have a larger direct impact than rising CO2 on global river runoff trends.Proceedings of the National Academy of Sciences, 104(39), 15242–15247.(link)
      • Piao, Shilong, Friedlingstein, Pierre, Ciais, Philippe, Viovy, Nicolas, and Demarty, Jér\^ome (2007). Growing season extension and its impact on terrestrial carbon cycle in the Northern Hemisphere over the past 2 decades.(link)
      • Reichstein, M, Ciais, P, Papale, D, Valentini, R, Running, S, Viovy, N, Cramer, W, Granier, A, Ogee, J, Allard, V, Aubinet, M, Bernhofer, C, Buchmann, N, Carrara, A, Grunwald, T, Heimann, M, Heinesch, B, Knohl, A, Kutsch, W, Loustau, D, Manca, G, Matteucci, G, Miglietta, F, Ourcival, JM, Pilegaard, K, Pumpanen, J, Rambal, S, Schaphoff, S, Seufert, G, Soussana, JF, Sanz, MJ, Vesala, T, and Zhao, M (2007).Reduction of ecosystem productivity and respiration during the European summer 2003 climate anomaly: a joint flux tower, remote sensing and modelling analysis.Global Change Biology, 13(3), 634–651. (link)
      • Santaren D., Philippe Peylin, Nicolas Viovy, and Philippe Ciais, Optimizing a Process based Ecosystem Model with Eddy-Covariance Flux Measurements: Part 1. A Pine Forest in Southern France, Global Biogeochemical Cycles, 21 (2) (link)
      • Seguin, Bernard, Arrouays, Dominique, Balesdent, Jérome, Soussana, Jean-François, Bondeau, Alberte, Smith, Pascalle, Zaehle, Sönke, Noblet, Nathalie de, and Viovy, Nicolas (2007).Moderating the impact of agriculture on climate.Agricultural and Forest Meteorology, 142(2-4), 278–287. (link)
      • Vautard, R., Yiou, P., D’Andrea, F., Noblet, N. de, Viovy, N., Cassou, C., Polcher, J., Ciais, P., Kageyama, M., and Fan, Y. (2007).Summertime European heat and drought waves induced by wintertime Mediterranean rainfall deficit. (link)


      • Chevallier, Fréd\’eric, Viovy, Nicolas, Reichstein, Markus, and Ciais, Philippe (2006).On the assignment of prior errors in Bayesian inversions of CO2 surface fluxes. Geophysical Research Letters Volume 33, Issue 13, July 2006 (link)
      • Hordoir, R., Nguyen, K. D., and Polcher, J. (2006). Simulating tropical river plumes, a set of parametrizations based on macroscale data: A test case in the Mekong Delta region.Journal of Geophysical Research: Oceans (1978–2012) Volume 111, Issue C9, September 2006 (link)
      • Lathiere, J., Hauglustaine, D. A., De Noblet-Ducoudre, N., Krinner, G., and Folberth, G. A.: Past and future changes in biogenic volatile organic compound emissions simulated with a global dynamic vegetation model, Geophysical Research Letters, 32, L20818, 10.1029/2005gl024164 (link)
      • Piao, SL, Fang, JY, Zhou, LM, Ciais, P, and Zhu, B (2006). Variations in satellite-derived phenology in China’s temperate vegetation.Global Change Biology, 12(4), 672–685.(link)
      • Piao, SL, Fang, JY, Zhou, LM, Ciais, P, and Zhu, B (2006). Variations in satellite-derived phenology in China’s temperate vegetation. Global Change Biology, 12(4), 672–685. (link)
      • Piao, Shilong, Friedlingstein, Pierre, Ciais, Philippe, Zhou, Liming, and Chen, Anping (2006). Effect of climate and CO2 changes on the greening of the Northern Hemisphere over the past two decades. Geophysical Research Letters Volume 33, Issue 23, December 2006 (link)


      • Abramowitz, Gab (2005).Towards a benchmark for land surface models. Geophysical Research Letters, 32, 22702.(link)
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      • Ngo-Duc, T., Laval, K., Polcher, J., Lombard, A., and Cazenave, A. (2005). Effects of land water storage on global mean sea level over the past half century. Geophysical Research Letters Volume 32, Issue 9, May 2005(link)
      • Peylin, Philippe, Bousquet, Philippe, Quér\’e, Corinne Le, Sitch, Stephen, Friedlingstein, Pierre, McKinley, Galen, Gruber, Nicolas, Rayner, Peter, and Ciais, Philippe (2005).Multiple constraints on regional CO2 flux variations over land and oceans.Global Biogeochemical Cycles, Volume 19, Issue 1, March 2005. (link)


      • Best, M. J., Beljaars, A., Polcher, J., and Viterbo, P. (2004).A Proposed Structure for Coupling Tiled Surfaces with the Planetary Boundary Layer. Journal of Hydrometeorology, 5(6), 1271–1278. (link)
      • Gervois, S., Noblet-Ducoudré, N. de, Viovy, N., Ciais, P., Brisson, N., Seguin, B., and Perrier, A. (2004). Including croplands in a global biosphere model: methodology and evaluation at specific sites. Earth Interactions, 8(1234567891012111415131617181920212223), 1–25.
      • de Noblet-Ducoudre, N., Gervois, S., Ciais, P., Viovy, N., Brisson, N., Seguin, B., and Perrier, A.: Coupling the soil-vegetation-atmosphere-transfer scheme ORCHIDEE to the agronomy model STICS to study the influence of croplands on the European Carbon and water budgets, Agronomie, 24, 397-407, Doi 10.1051/Agro:2004038 (link)


      • de Rosnay, P., Polcher, J., Laval, K., and Sabre, M.: Integrated parameterisation of irrigation in the land surface model ORCHIDEE. Validation over Indian Peninsula, Geophysical Research Letters, 30, Artn 1986, Doi 10.1029/2003gl018024 (link)
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Ongoing developments


  • An improved canopy radiation transfer scheme
  • A multi-layer energy budget
  • Implementation of the dynamics of snow packing and snow melt
  • The inclusion of isotopes (18O and 13C)


  • Introduction of parameter sets for new PFTs, to drive the externalized version
  • Soil micro-organism representation for SOM decomposition
  • DOC/DIC production and leaching
  • Simulation of forest fires, based on the SPITFIRE model
  • Forest demography, including stochastic processes


  • Differentiating forest management
  • Biofuel crop management
  • New crop specific modules (such as rice and sugar cane)

Code structure

  • Development of the “Adjoint” code

For more further details, please don’t hesitate to contact us.



ORCHIDEE is the land surface model of the IPSL (Institut Pierre Simon Laplace) Earth System Model. Hence, by conception, the ORCHIDEE model can be run coupled to a global circulation model (Fig 1a). In a coupled set-up, the atmospheric conditions affect the land surface and the land surface, in turn, affects the atmospheric conditions. Coupled land-atmosphere models thus offer the possibility to quantify both the climate effects of changes in the land surface and the effects of climate change on the land surface. However, when a study focuses on changes in the land surface rather than on the interaction with climate, ORCHIDEE can be run off line as a stand-alone land surface model (Fig 1b). The stand-alone configuration receives the atmospheric conditions such as temperature, humidity and wind, to mention a few, from the so-called ‘forcing files’. Unlike the coupled set-up, which needs to run at the global scale (but with the possibility of a regional zoom), the stand alone configuration can cover any area ranging from the global domain to a single grid point.

Figure 1 Conceptual differences between (A) a coupled simulation and (B) an off-line simulation. Note the same model is used and the difference is in the interface and the source of the forcing data. In the coupled set-up the interface supports a two-way interaction and the climate conditions are calculated by a global circulation model. In the off-line set-up a one-way interface is used and the climate conditions are read from forcing files.

Modelled processes

The processes included in the early versions of ORCHIDEE were aimed at quantifying the terrestrial water (Fig. 2a) and the energy balance (Fig. 2b). Later versions of the model were extended with biogeochemical processes (Fig 2c), and the current version simulates the interference of anthropogenic activities with natural biogeochemical processes (Fig 2d). The biophysical process include latent (denoted ‘evaporation and transpiration’ in Fig 2a or LE in Fig 2b), sensible (denoted H in Fig 2b), and kinetic energy exchanges at the surface of soils (G in Fig 2b). Heat dissipation and water fluxes are vertically distributed in the soil (‘drainage’ in Fig. 2a and G in 2b) and the runoff (Fig 2a) is collected in rivers and lakes. The simulated processes that affect the global carbon cycle (Fig 2c) include photosynthesis, carbon allocation, litter decomposition, soil carbon decomposition, maintenance and growth respiration and vegetation dynamics. The anthropogenic interference (Fig 2d) includes land cover changes, fire, crop irrigation, and forest and grassland management.

Figure 2 The main processes simulated in ORCHIDEE. The processes are grouped in terms of the water balance (a), the energy balance (b), the biogeochemical processes (c) and anthropogenic processes (d). Although the water and energy budget were separated in this presentation, both need to be run at the same time. These processes are coded in a group of modules called ‘Sechiba’ and are the backbone of ORCHIDEE. In addition to Sechiba, the biogeochemical code and the anthropogenic code, grouped in modules called ‘Stomate’, can be activated. Several individual processes can be switched on or off, so supporting a wide range of model set-ups. Nevertheless, the model can be run without activating Stomate.

Input data

ORCHIDEE calculates its prognostic variables (i.e. a multitude of C, H2O and energy fluxes) from the following environmental drivers: air temperature, wind speed, solar radiation, air humidity, precipitation and atmospheric CO2 concentration. In off-line mode, the user should provide these drivers, and ORCHIDEE simulates their impact on ecosystem production, ecosystem respiration, the energy budget of ecosystems, the soil water budget and the surface run–off at a wide range of temporal and spatial scales (Fig. 3). When coupled to an atmospheric model, ORCHIDEE follows an implicit approach. The prognostic variables of ORCHIDEE at each timestep are therefore simultaneously calculated with the atmospheric drivers in the planetary boundary layer (Fig. 1a). For both setups, the user needs to provide files describing the boundary conditions, namely the (initial) vegetation distribution (that may change with time if the dynamic vegetation module is activated) and a soil map. When the biogeochemical processes are not activated, the leaf area index (LAI) of the vegetation is read from a map, which needs to be provided by the user. When the runoff is routed through rivers and lakes, a basin and a floodplain map are required. Finally when irrigation is applied, it needs to be prescribed by an irrigation map.

Figure 3 Mandatory (top row) and optional (bottom row) boundary conditions that need to be provided for ORCHIDEE simulations. The vegetation map specifies the location and share of the different meta-classes (13 in total), the soil types and colour map is required for soil water and energy computations as well as the calculation of the bare soil albedo. The long term temperature is required for phenological initializations. The optional maps are needed only when specific modules are to be used.

Spatial conceptualization

Although ORCHIDEE does not enforce a spatial or temporal resolution, the model does use a spatial grid and equidistant time steps. The spatial resolution is an implicit user setting that is determined by the coarsest resolution of the forcing data (Fig. 1b) and the boundary conditions (Fig 3): the vegetation distribution (default 5kmx5km), climatological forcing data (default 1°x1°) and the soil map (default 0.5°x0.5°). If higher resolution drivers are available the model can then be run at that scale. If site-level drivers are available then simulations at the site scale are feasible. When ORCHIDEE is used in a coupled set-up the grid applied by the atmospheric model determines the spatial resolution of the surface layer model (Fig 1a). For global simulations a typical grid is 2.5° latitude by 3.0° longitude.

The standard version of ORCHIDEE builds on the concept of meta-classes to describe vegetation distribution. By default it distinguishes 13 such meta-classes (one for bare soil, eight for forests, two for grasslands and two for croplands). Each meta-class can be subdivided in an unlimited number of Plant functional types (PFTs). By default, each meta-class has a single PFT. Biogeochemical and biophysical variables are calculated for each PFT (Fig 4a), where most of the biogeochemical variables are reported at the PFT level, the biophysical variables are aggregated at the pixel level because the atmospheric model does not distinguish PFTs and hence its spatial resolution is limited to the pixel scale.

For the water and heat balance of the soil, three soil columns are distinguished: one containing each meta-class that includes forest, one for every meta-class with grass and crops and, finally, one for bare soils. Water and heat related soil variables are calculated separately for each column.

Figure 4 Spatial conceptualization of ORCHIDEE. ORCHIDEE is run at a regular grid, hence, its basic spatial unit is a grid cell, a grid cell having a known longitude and latitude. (a) The vegetation within a grid cell can be composed of 13 different meta-classes and an unlimited number of PFTs (Plant Functional Types) within each meta-class. Meta-class and PFT have no known location within a grid cell – they simply take up a share of the grid cell. The biogeochemical soil processes such as litter decomposition follow the meta-class based subdivision. (b) A similar concept is used to model the biophysical soil processes such as soil water and heat storage, however, three columns cutting across several meta-class are now used. One column is saved for the soil under tall vegetation (i.e. all meta-classes containing forest), one for short vegetation (i.e. meta-classes that contain grass and crops) and one for soil without vegetation. The three different soil columns do not have a known location within the grid cell.

Temporal conceptualization

ORCHIDEE can run on any temporal resolution, however, this apparent flexibility is rather restricted as the processes are formalized at given time steps: half-hourly (i.e. photosynthesis and energy budget), daily (i.e. net primary production) and annual time step (i.e. vegetation dynamics) (Fig. 5). Hence, meaningful simulations have a temporal resolution of 15 minutes to one hour for the energy balance, water balance and photosynthesis calculations.

Figure 5 ORCHIDEE has no prescribed time resolution, nevertheless, the way processes were formalized largely reduces this flexibility. Four different time steps can be defined within the model. One time step, typically 30 minutes, defines the fast processes such as photosynthesis, autotrophic respiration, water and energy fluxes. A second time step controls the water routing in lakes and rivers. This is typically the same as the fast time step but can deviate slightly from it. A third time step, typically one day, controls the medium-fast processes such as heterotrophic respiration, carbon allocation within the plant and leaf area index. The final time step controls the slow processes which need only to be calculated once per year, such as vegetation dynamics, and ecosystem management.


Main ORCHIDEE version

The ‘trunk’ version of ORCHIDEE:

Thematic versions

The following branches have been carefully validated and tested:

  • ORCHIDEE-multi-soil-hydro – a more detailed simulation soil hydrology over 11 layers
  • ORCHIDEE-CN– this branch includes both Carbon and Nitrogen cycling
  • ORCHIDEE-FM – includes a generic description of forest management
  • ORCHIDEE-HIGHLATITUDE – this branch includes the 11-layer hydrology, wetland dynamics and permafrost dynamics
  • ORCHIDEE-EXT – in this branch all parameters have been externalized, and so is the appropriate choice for sensitivity analysis
  • ORCHIDEE-STICS – an evolution of the ORCHIDEE ecosystem model that is coupled to the STICS agronomy model, which describes crop phenology
  • ORCHIDEE-PASIM – ORCHIDEE coupled to an implementation of the PASIM, which is a model of prairie management developed by the INRA institute
  • ORCHIDEE-BVOC – a version that implements the emission and interactions of Biogenic Volatile Organic Compounds

At present, a core team of more than 25 people are working on extending the functionality of the trunk and developing new branches with additional features.