Author: "Guimberteau, Matthieu" - Searchworks@Jio Institute Digital Library Search Results

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1. Deceleration of China’s human water use and its key drivers

Author: Zhou, Feng, Bo, Yan, Ciais, Philippe, Dumas, Patrice, Tang, Qiuhong, Wang, Xuhui, Liu, Junguo, Zheng, Chunmiao, Polcher, Jan, Yin, Zun, Guimberteau, Matthieu, Peng, Shushi, Ottle, Catherine, Zhao, Xining, Zhao, Jianshi, Tan, Qian, Chen, Lei, Shen, Huizhong, Yang, Hui, Piao, Shilong, Wang, Hao, and Wada, Yoshihide
Published: 2020

2. Contributions of Climate Change, CO₂, Land-Use Change, and Human Activities to Changes in River Flow across 10 Chinese Basins

Author: Xi, Yi, Peng, Shushi, Ciais, Philippe, Guimberteau, Matthieu, Li, Yue, Piao, Shilong, Wang, Xuhui, Polcher, Jan, Yu, Jiashuo, Zhang, Xuanze, Zhou, Feng, Bo, Yan, Ottle, Catherine, and Yin, Zun
Published: 2018

3. Water Balance in the Amazon Basin from a Land Surface Model Ensemble

Author: Getirana, Augusto CV, Dutra, Emanuel, Guimberteau, Matthieu, Kam, Jonghun, Li, Hong-Yi, Decharme, Bertrand, Zhang, Zhengqiu, Ducharne, Agnes, Boone, Aaron, Balsamo, Gianpaolo, Rodell, Matthew, Toure, Ally M, Xue, Yongkang, Peters-Lidard, Christa D, Kumar, Sujay V, Arsenault, Kristi, Drapeau, Guillaume, Ruby Leung, L, Ronchail, Josyane, and Sheffield, Justin
Subjects: Climate Action, Amazon region, Runoff, Hydrologic models, Land surface model, Atmospheric Sciences, Meteorology & Atmospheric Sciences
Abstract: Despite recent advances in land surfacemodeling and remote sensing, estimates of the global water budget are still fairly uncertain. This study aims to evaluate the water budget of the Amazon basin based on several state-ofthe- art land surface model (LSM) outputs. Water budget variables (terrestrial water storage TWS, evapotranspiration ET, surface runoff R, and base flow B) are evaluated at the basin scale using both remote sensing and in situ data. Meteorological forcings at a 3-hourly time step and 18 spatial resolution were used to run 14 LSMs. Precipitation datasets that have been rescaled to matchmonthly Global Precipitation Climatology Project (GPCP) andGlobal Precipitation Climatology Centre (GPCC) datasets and the daily Hydrologie du Bassin de l'Amazone (HYBAM) dataset were used to perform three experiments. The Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme was forced with R and B and simulated discharges are compared against observations at 165 gauges. Simulated ET and TWS are compared against FLUXNET and MOD16A2 evapotranspiration datasets andGravity Recovery and ClimateExperiment (GRACE)TWSestimates in two subcatchments of main tributaries (Madeira and Negro Rivers).At the basin scale, simulated ET ranges from 2.39 to 3.26mmday-1 and a low spatial correlation between ET and precipitation indicates that evapotranspiration does not depend on water availability over most of the basin. Results also show that other simulated water budget components vary significantly as a function of both the LSM and precipitation dataset, but simulated TWS generally agrees with GRACE estimates at the basin scale. The best water budget simulations resulted from experiments using HYBAM, mostly explained by a denser rainfall gauge network and the rescaling at a finer temporal scale.
Published: 2014

4. Quantifying the unauthorized lake water withdrawals and their impacts on the water budget of eutrophic lake Dianchi, China

Author: Wu, Yali, Bo, Yan, Zhou, Feng, Tang, Qiuhong, Guimberteau, Matthieu, Ciais, Philippe, Yang, Tao, Peng, Shushi, Piao, Shilong, Zheng, Jiangli, Dong, Yanjun, and Dai, Chaomeng
Published: 2018
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5. Effect of tree demography and flexible root water uptake for modeling the carbon and water cycles of Amazonia

Author: Joetzjer, Emilie, primary, Maignan, Fabienne, additional, Chave, Jérôme, additional, Goll, Daniel, additional, Poulter, Ben, additional, Barichivich, Jonathan, additional, Maréchaux, Isabelle, additional, Luyssaert, Sebastiaan, additional, Guimberteau, Matthieu, additional, Naudts, Kim, additional, Bonal, Damien, additional, and Ciais, Philippe, additional
Published: 2022
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6. Effect of tree demography and flexible root water uptake for modeling the carbon and water cycles of Amazonia

Author: Joetzjer, Emilie, Maignan, Fabienne, Chave, Jérôme, Goll, Daniel, Poulter, Ben, Barichivich, Jonathan, Marechaux, Isabelle, Luyssaert, Sebastiaan, Guimberteau, Matthieu, Naudts, K., Bonal, Damien, Ciais, P., Joetzjer, Emilie, Maignan, Fabienne, Chave, Jérôme, Goll, Daniel, Poulter, Ben, Barichivich, Jonathan, Marechaux, Isabelle, Luyssaert, Sebastiaan, Guimberteau, Matthieu, Naudts, K., Bonal, Damien, and Ciais, P.
Abstract: Amazonian forest plays a crucial role in regulating the carbon and water cycles in the global climate system. However, the representation of biogeochemical fluxes and forest structure in dynamic global vegetation models (DGVMs) remains challenging. This situation has considerable implications to simulate the state and dynamics of Amazonian forest. This study aims at simulating the dynamic of the evapotranspiration (ET), productivity (GPP), biomass (AGB) and forest structure of wet tropical forests in the Amazon basin using the updated ORCHIDEE land surface model. The latter is improved for two processes: stand structure and demography, and plant water uptake by roots. Stand structure is simulated by adapting the CAN version of ORCHIDEE, originally developed for temperate forests. Here, we account for the permanent recruitment of young individual trees, the distribution of stand level growth into 20 different cohorts of variable diameter classes, and mortality due to asymmetric competition for light. Plant water uptake is simulated by including soil-to-root hydraulic resistance (RS). To evaluate the effect of the soil resistance alone, we performed factorial simulations with demography only (CAN) and both demography and resistance (CAN-RS). AGB, ET and GPP outputs of CAN-RS are also compared with the standard version of ORCHIDEE (TRUNK) for which eco-hydrological parameters were tuned globally to fit GPP and evapotranspiration at flux tower sites. All the model versions are benchmarked against in situ and regional datasets. We show that CAN-RS correctly reproduce stand level structural variables (as CAN) like diameter classes and tree densities when validated using in-situ data. Besides offering the key advantage to simulate forest's structure, it also correctly simulates ET and GPP and improves fluxes spatial patterns when compared to TRUNK. With the new formulation of soil water uptake, which is driven by soil water availability rather than root-biomass, the sim
Published: 2022
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7. The Critical Role of the Routing Scheme in Simulating Peak River Discharge in Global Hydrological Models

Author: Zhao, Fang, Veldkamp, Ted I. E, Frieler, Katja, Schewe, Jacob, Ostberg, Sebastian, Willner, Sven, Schauberger, Bernhard, Gosling, Simon N, Schmied, Hannes Muller, Portmann, Felix T, Leng, Guoyong, Huang, Maoyi, Liu, Xingcai, Tang, Qiuhong, Hanasaki, Naota, Biemans, Hester, Gerten, Dieter, Wada, Yoshihide, Pokhrel, Yadu, Stacke, Tobias, Ciais, Philippe, Chang, Jinfeng, Ducharne, Agnes, Guimberteau, Matthieu, Kim, Hyungjun, and Yamazaki, Dai
Subjects: Meteorology And Climatology
Abstract: Global hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge which is crucial in flood simulations has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971-2010) within the ISIMIP2a (Inter-Sectoral Impact Model Intercomparison Project phase 2a) project. The runoff simulations were used as input for the global river routing model CaMa-Flood (Catchment-based Macro-scale Floodplain). The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC (Global Runoff Data Centre) stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about two-thirds of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.
Published: 2017
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8. Presentation and Evaluation of the IPSL-CM6A-LR Climate Model

Author: Boucher, Olivier, Servonnat, Jérôme, Albright, Anna Lea, Aumont, Olivier, Balkanski, Yves, Bastrikov, Vladislav, Bekki, Slimane, Bonnet, Rémy, Bony, Sandrine, Bopp, Laurent, Braconnot, Pascale, Brockmann, Patrick, Cadule, Patricia, Caubel, Arnaud, Cheruy, Frédérique, Codron, Francis, Cozic, Anne, Cugnet, David, d'Andrea, Fabio, Davini, Paolo, de Lavergne, Casimir, Denvil, Sébastien, Deshayes, Julie, Devilliers, Marion, Ducharne, Agnès, Dufresne, Jean-Louis, Dupont, Eliott, Éthé, Christian, Fairhead, Laurent, Falletti, Lola, Flavoni, Simona, Foujols, Marie-Alice, Gardoll, Sébastien, Gastineau, Guillaume, Ghattas, Josefine, Grandpeix, Jean-Yves, Guenet, Bertrand, Guez, Lionel, Guilyardi, Éric, Guimberteau, Matthieu, Hauglustaine, Didier, Hourdin, Frédéric, Idelkadi, Abderrahmane, Joussaume, Sylvie, Kageyama, Masa, Khodri, Myriam, Krinner, Gerhard, Lebas, Nicolas, Levavasseur, Guillaume, Lévy, Claire, Li, Laurent, Lott, François, Lurton, Thibaut, Luyssaert, Sebastiaan, Madec, Gurvan, Madeleine, Jean-Baptiste, Maignan, Fabienne, Marchand, Marion, Marti, Olivier, Mellul, Lidia, Meurdesoif, Yann, Mignot, Juliette, Musat, Ionela, Ottle, Catherine, Peylin, Philippe, Planton, Yann, Polcher, Jan, Rio, Catherine, Rochetin, Nicolas, rousset, clement, Rousset, Clément, Sepulchre, Pierre, Sima, Adriana, Swingedouw, Didier, Thiéblemont, Rémi, Traore, Abdoul Khadre, Vancoppenolle, Martin, Vial, Jessica, Vialard, Jérôme, Viovy, Nicolas, Vuichard, Nicolas, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Nucleus for European Modeling of the Ocean (NEMO R&D ), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Modélisation du climat (CLIM), Calcul Scientifique (CALCULS), Océan et variabilité du climat (VARCLIM), Istituto di Scienze dell'Atmosfera e Del Clima [Torino] (isac), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Environnements et Paléoenvironnements OCéaniques (EPOC), Observatoire aquitain des sciences de l'univers (OASU), Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), University of Amsterdam [Amsterdam] (UvA), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), ANR-17-EURE-0006,IPSL-CGS,IPSL Climate graduate school(2017), ANR-15-JCLI-0004,GOTHAM,Globally Observed Teleconnections and their role and representation in Hierarchies of Atmospheric Models(2015), ANR-18-CE01-0012,ARiSE,Rôle de la non-linéarité de la réponse atmosphérique à la température de l'océan dans la physique d'ENSO (El Niño Oscillation Australe)(2018), ANR-13-MONU-0008,CONVERGENCE,Convergence en Science du Climat à l'ère du Big Data et des challenges de l'Exascale.(2013), ANR-18-MPGA-0001,ARCHANGE,Changement climatique et Arctique et circulation océanique globale(2018), European Project: 641816,H2020,H2020-SC5-2014-two-stage,CRESCENDO(2015), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Sorbonne Université (SU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Sorbonne Université (SU), École normale supérieure - Paris (ENS Paris)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), École normale supérieure - Paris (ENS Paris), Consiglio Nazionale delle Ricerche (CNR), UMR 5805 Environnements et Paléoenvironnements Océaniques et Continentaux (EPOC), Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-École pratique des hautes études (EPHE)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Univers et Particules de Montpellier (LUPM), Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), MOSAIC (MOSAIC), Institut FRESNEL (FRESNEL), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Université Grenoble Alpes (UGA)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Météo France, Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE), École pratique des hautes études (EPHE), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), and Systems Ecology
Subjects: 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, 010502 geochemistry & geophysics, climate model, IPSL‐CM6A‐LR, 01 natural sciences, Carbon cycle, lcsh:Oceanography, climate metrics, Range (statistics), SDG 13 - Climate Action, Environmental Chemistry, lcsh:GC1-1581, Precipitation, lcsh:Physical geography, ComputingMilieux_MISCELLANEOUS, CMIP6, 0105 earth and related environmental sciences, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Global and Planetary Change, Coupled model intercomparison project, Intertropical Convergence Zone, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, Middle latitudes, General Earth and Planetary Sciences, Environmental science, Climate sensitivity, climate sensitivity, Climate model, lcsh:GB3-5030, IPSL-CM6A-LR
Abstract: International audience This study presents the global climate model IPSL-CM6A-LR developed at Institut Pierre-Simon Laplace (IPSL) to study natural climate variability and climate response to natural and anthropogenic forcings as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This article describes the different model components, their coupling, and the simulated climate in comparison to previous model versions. We focus here on the representation of the physical climate along with the main characteristics of the global carbon cycle. The model's climatology, as assessed from a range of metrics (related in particular to radiation, temperature, precipitation, and wind), is strongly improved in comparison to previous model versions. Although they are reduced, a number of known biases and shortcomings (e.g., double Intertropical Convergence Zone [ITCZ], frequency of midlatitude wintertime blockings, and El Niño–Southern Oscillation [ENSO] dynamics) persist. The equilibrium climate sensitivity and transient climate response have both increased from the previous climate model IPSL-CM5A-LR used in CMIP5. A large ensemble of more than 30 members for the historical period (1850–2018) and a smaller ensemble for a range of emissions scenarios (until 2100 and 2300) are also presented and discussed.
Published: 2020

9. Global effect of irrigation and its impact on the onset of the Indian summer monsoon

Author: Guimberteau, Matthieu, Laval, Katia, Perrier, Alain, and Polcher, Jan
Published: 2012
Full Text: View/download PDF

10. 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

Author: Bowring, Simon, Lauerwald, Ronny, Guenet, Bertrand, Zhu, Dan, Guimberteau, Matthieu, Regnier, Pierre, Tootchi, Ardalan, Ducharne, Agnes, Ciais, Philippe, Bowring, Simon, Lauerwald, Ronny, Guenet, Bertrand, Zhu, Dan, Guimberteau, Matthieu, Regnier, Pierre, Tootchi, Ardalan, Ducharne, Agnes, and Ciais, Philippe
Abstract: In this second part of a two-part study, we performed a simulation of the carbon and water budget of the Lena catchment with the land surface model ORCHIDEE MICT-LEAK, enabled to simulate dissolved organic carbon (DOC) production in soils and its transport and fate in high-latitude inland waters. The model results are evaluated for their ability to reproduce the fluxes of DOC and carbon dioxide (CO2) along the soil-inland-water continuum and the exchange of CO2 with the atmosphere, including the evasion outgassing of CO2 from inland waters. We present simulation results over the years 1901-2007 and show that the model is able to broadly reproduce observed state variables and their emergent properties across a range of interacting physical and biogeochemical processes. These include (1) net primary production (NPP), respiration and riverine hydrologic amplitude, seasonality, and inter-annual variation; (2) DOC concentrations, bulk annual flow, and their volumetric attribution at the sub-catchment level; (3) high headwater versus downstream CO2 evasion, an emergent phenomenon consistent with observations over a spectrum of high-latitude observational studies. These quantities obey emergent relationships with environmental variables like air temperature and topographic slope that have been described in the literature. This gives us confidence in reporting the following additional findings: of the ĝ'1/434TgCyr-1 left over as input to soil matter after NPP is diminished by heterotrophic respiration, 7TgCyr-1 is leached and transported into the aquatic system. Of this, over half (3.6TgCyr-1) is evaded from the inland water surface back into the atmosphere and the remainder (3.4TgCyr-1) flushed out into the Arctic Ocean, mirroring empirically derived studies. These riverine DOC exports represent ĝ'1/41.5% of NPP. DOC exported from the floodplains is dominantly sourced from recent more "labile" terrestrial production in contrast to DOC leached from the rest of the watershed, SCOPUS: ar.j, info:eu-repo/semantics/published
Published: 2020

11. 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

Author: Bowring, Simon P. K., primary, Lauerwald, Ronny, additional, Guenet, Bertrand, additional, Zhu, Dan, additional, Guimberteau, Matthieu, additional, Regnier, Pierre, additional, Tootchi, Ardalan, additional, Ducharne, Agnès, additional, and Ciais, Philippe, additional
Published: 2020
Full Text: View/download PDF

12. 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

Author: Bowring, Simon, Lauerwald, Ronny, Guenet, Bertrand, Zhu, Dan, Guimberteau, Matthieu, Tootchi, Ardalan, Ducharne, Agnes, Ciais, Philippe, Bowring, Simon, Lauerwald, Ronny, Guenet, Bertrand, Zhu, Dan, Guimberteau, Matthieu, Tootchi, Ardalan, Ducharne, Agnes, and Ciais, Philippe
Abstract: Few Earth system models adequately represent the unique permafrost soil biogeochemistry and its respective processes; this significantly contributes to uncertainty in estimating their responses, and that of the planet at large, to warming. Likewise, the riverine component of what is known as the "boundless carbon cycle" is seldom recognised in Earth system modelling. The hydrological mobilisation of organic material from a ∼ 1330-1580 PgC carbon stock to the river network results in either sedimentary settling or atmospheric "evasion", processes widely expected to increase with amplified Arctic climate warming. Here, the production, transport, and atmospheric release of dissolved organic carbon (DOC) from high-latitude permafrost soils into inland waters and the ocean are explicitly represented for the first time in the land surface component (ORCHIDEE) of a CMIP6 global climate model (Institut Pierre Simon Laplace - IPSL). The model, ORCHIDEE MICT-LEAK, which represents the merger of previously described ORCHIDEE versions MICT and LEAK, mechanistically represents (a) vegetation and soil physical processes for high-latitude snow, ice, and soil phenomena and (b) the cycling of DOC and CO2, including atmospheric evasion, along the terrestrial-aquatic continuum from soils through the river network to the coast at 0.5 to 2° resolution. This paper, the first in a two-part study, presents the rationale for including these processes in a high-latitude-specific land surface model, then describes the model with a focus on novel process implementations, followed by a summary of the model configuration and simulation protocol. The results of these simulation runs, conducted for the Lena River basin, are evaluated against observational data in the second part of this study., SCOPUS: ar.j, info:eu-repo/semantics/published
Published: 2019

13. ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation

Author: Guimberteau, Matthieu, Zhu, Dan, Maignan, Fabienne, Huang, Ye, Yue, Chao, Dantec-Nédélec, Sarah, Ottlé, Catherine, Jornet-Puig, Albert, Bastos, Ana, Laurent, Pierre, Goll, Daniel S., Bowring, Simon, Chang, Jinfeng, Guenet, Bertrand, Tifafi, Marwa, Peng, Shushi, Krinner, Gerhard, Ducharne, Agnès, Wang, Fuxing, Wang, Tao, Wang, Xuhui, Wang, Yilong, Yin, Zun, Lauerwald, Ronny, Joetzjer, Emilie, Qiu, Chunjing, Kim, Hyungjun, Ciais, Philippe, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] ( LSCE ), Université de Versailles Saint-Quentin-en-Yvelines ( UVSQ ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ), Huazhong University of Science & Technology [Wuhan] ( HUST ), Joint Unit, LSCE, Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ), Instituto de Geociências, Universidade Federal do Rio Grande do Sul [Porto Alegre] ( UFRGS ), Département de Physique des Particules (ex SPP) ( DPP ), Institut de Recherches sur les lois Fondamentales de l'Univers ( IRFU ), Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay, Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques ( LOCEAN ), Muséum National d'Histoire Naturelle ( MNHN ) -Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ), Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University [Beijing], Laboratoire de glaciologie et géophysique de l'environnement ( LGGE ), Observatoire des Sciences de l'Univers de Grenoble ( OSUG ), Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Centre National de la Recherche Scientifique ( CNRS ), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols ( METIS ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -École pratique des hautes études ( EPHE ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de Météorologie Dynamique (UMR 8539) ( LMD ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -École polytechnique ( X ) -École des Ponts ParisTech ( ENPC ) -Centre National de la Recherche Scientifique ( CNRS ) -Département des Géosciences - ENS Paris, École normale supérieure - Paris ( ENS Paris ) -École normale supérieure - Paris ( ENS Paris ), Laboratoire d'Informatique pour l'Entreprise et les Systèmes de Production ( LIESP ), Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Université Libre de Bruxelles [Bruxelles] ( ULB ), Montana State University ( MSU ), Korea Advanced Institute of Science and Technology ( KAIST ), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Universidade Federal do Rio Grande do Sul [Porto Alegre] (UFRGS), Ingénierie des Matériaux Polymères - Laboratoire des Matériaux Macromoléculaires (IMP-LMM), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet [Saint-Étienne] (UJM)-Centre National de la Recherche Scientifique (CNRS), Institut des Géosciences de l’Environnement [2017-2019] (IGE [2017-2019]), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), École pratique des hautes études (EPHE)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Université libre de Bruxelles (ULB), Montana State University (MSU), Korea Advanced Institute of Science and Technology (KAIST), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Huazhong University of Science and Technology [Wuhan] (HUST), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Département de Physique des Particules (ex SPP) (DPhP), Institut de Recherches sur les lois Fondamentales de l'Univers (IRFU), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research - Chinese Academy of Sciences, CAS Center for Excellence in Tibetan Plateau Earth Sciences, Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Département de Physique des Particules (ex SPP) (DPP), Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE), and Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [ SDU.OCEAN ] Sciences of the Universe [physics]/Ocean, Atmosphere, [SDE.MCG]Environmental Sciences/Global Changes, ddc:550, [ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces, environment, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS
Abstract: International audience; The high-latitude regions of the Northern Hemisphere are a nexus for the interaction between land surface physical properties and their exchange of carbon and energy with the atmosphere. At these latitudes, two carbon pools of planetary significance-those of the permanently frozen soils (permafrost), and of the great expanse of boreal forest-are vulnerable to destabilization in the face of currently observed climatic warming, the speed and intensity of which are expected to increase with time. Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO 2 fluxes, in addition to a recently developed fire module. Outputs from ORCHIDEE-MICT, when forced by two climate input datasets, are extensively evaluated against (i) temperature gradients between the atmosphere and deep soils, (ii) the hydrological components comprising the water balance of the largest high-latitude basins, and (iii) CO 2 flux and carbon stock observations. The model performance is good with respect to empirical data, despite a simulated excessive plant water stress and Published by Copernicus Publications on behalf of the European Geosciences Union. 122 M. Guimberteau et al.: ORCHIDEE-MICT, a LSM for the high latitudes a positive land surface temperature bias. In addition, acute model sensitivity to the choice of input forcing data suggests that the calibration of model parameters is strongly forcing-dependent. Overall, we suggest that this new model design is at the forefront of current efforts to reliably estimate future perturbations to the high-latitude terrestrial environment.
Published: 2018

14. 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

Author: Bowring, Simon P. K., primary, Lauerwald, Ronny, additional, Guenet, Bertrand, additional, Zhu, Dan, additional, Guimberteau, Matthieu, additional, Tootchi, Ardalan, additional, Ducharne, Agnès, additional, and Ciais, Philippe, additional
Published: 2019
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15. Supplementary material to "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"

Author: Bowring, Simon P. K., primary, Lauerwald, Ronny, additional, Guenet, Bertrand, additional, Zhu, Dan, additional, Guimberteau, Matthieu, additional, Regnier, Pierre, additional, Tootchi, Ardalan, additional, Ducharne, Agnès, additional, and Ciais, Philippe, additional
Published: 2019
Full Text: View/download PDF

16. 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

Author: Bowring, Simon P. K., primary, Lauerwald, Ronny, additional, Guenet, Bertrand, additional, Zhu, Dan, additional, Guimberteau, Matthieu, additional, Regnier, Pierre, additional, Tootchi, Ardalan, additional, Ducharne, Agnès, additional, and Ciais, Philippe, additional
Published: 2019
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17. A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: an example from the Amazon region

Author: Rammig, Anja, Heinke, Jens, Hofhansl, Florian, Verbeeck, Hans, Baker, Timothy R., Christoffersen, Bradley, Ciais, Philippe, De Deurwaerder, Hannes, Fleischer, Katrin, Galbraith, David, Guimberteau, Matthieu, Huth, Andreas, Johnson, Michelle, Krujit, Bart, Langerwisch, Fanny, Meir, Patrick, Papastefanou, Phillip, Sampaio, Gilvan, Thonicke, Kirsten, von Randow, Celso, Zang, Christian, and Rödig, Edna
Subjects: ddc
Published: 2017

18. A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: an example from the Amazon region

Author: Rammig, Anja, primary, Heinke, Jens, additional, Hofhansl, Florian, additional, Verbeeck, Hans, additional, Baker, Timothy R., additional, Christoffersen, Bradley, additional, Ciais, Philippe, additional, De Deurwaerder, Hannes, additional, Fleischer, Katrin, additional, Galbraith, David, additional, Guimberteau, Matthieu, additional, Huth, Andreas, additional, Johnson, Michelle, additional, Krujit, Bart, additional, Langerwisch, Fanny, additional, Meir, Patrick, additional, Papastefanou, Phillip, additional, Sampaio, Gilvan, additional, Thonicke, Kirsten, additional, von Randow, Celso, additional, Zang, Christian, additional, and Rödig, Edna, additional
Published: 2018
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19. A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: An example from the Amazon region

Author: RAMMIG, Anja, Heinke, Jens, Hofhansl, Florian, Verbeeck, Hans, Baker, T R, Christoffersen, Brad, DE DEURWAERDER, Hannes, Fleischer, Katrin, Galbraith, David R, GUIMBERTEAU, MATTHIEU, Meir, Patrick, RAMMIG, Anja, Heinke, Jens, Hofhansl, Florian, Verbeeck, Hans, Baker, T R, Christoffersen, Brad, DE DEURWAERDER, Hannes, Fleischer, Katrin, Galbraith, David R, GUIMBERTEAU, MATTHIEU, and Meir, Patrick
Abstract: Comparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25 % and up to 60 %, respectively. Our comparison metrics provide a quantitative measure for model–data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving bi
Published: 2018

20. Le climat à découvert

Author: Ablain, Michaël, Allard, Patrick, Anquetin, Sandrine, Balkanski, Yves, Bard, Édouard, Bekki, Slimane, Berthier, Étienne, Blamart, Dominique, Blard, Pierre-Henri, Blay, Michel, Blayo, Éric, Bony, Sandrine, Bopp, Laurent, Braconnot, Pascale, Brenguier, Jean-Louis, Bustarret, Étienne, Cadule, Patricia, Cassou, Christophe, Cazenave, Anny, Céron, Jean-Pierre, Chappellaz, Jérôme, Chauvaud, Laurent, Ciais, Philippe, Codron, Francis, Corrège, Thierry, Cortijo, Elsa, Cottet, Georges-Henri, Criqui, Patrick, Dandin, Philippe, Daux, Valérie, Davin, Édouard, Decharme, Bertrand, Delcroix, Thierry, Delecluse, Pascale, Delire, Christine, Déqué, Michel, de Marsily, Ghislain, de Noblet-Ducoudré, Nathalie, Donnadieu, Yannick, Douville, Hervé, Dubuisson, Philippe, Dudok de Wit, Thierry, Dufresne, Jean-Louis, Durand, Gaël, Féral, Jean-Pierre, Fluteau, Frédéric, France-Lanord, Christian, Friedlingstein, Pierre, Friess, Benjamin, Fuchs, Alain, Gaillardet, Jérôme, Garnier, Emmanuel, Genty, Dominique, Gerbeau, Jean-Frédéric, Goddéris, Yves, Grousset, Francis, Guillemot, Hélène, Guilyardi, Éric, Guimberteau, Matthieu, Guiot, Joël, Hall, Nick, Hourcade, Jean-Charles, Hourdin, Frédéric, Jeandel, Catherine, Joussaume, Sylvie, Jouzel, Jean, Kageyama, Masa, Khodri, Myriam, Klein, Patrice, Krinner, Gerhard, Laj, Paolo, Landais, Amaelle, Laval, Katia, Legras, Bernard, Le Bohec, Céline, Le Hir, Guillaume, Le Maho, Yvon, Le Treut, Hervé, Lilensten, Jean, Llovel, William, Lott, François, Maisonnave, Éric, Marchesiello, Patrick, Mascart, Patrick, Masson-Delmotte, Valérie, Mémery, Laurent, Metzl, Nicolas, Meurdesoif, Yann, Mignot, Juliette, Mosseri, Rémy, Naveau, Philippe, Petit, Jean-Robert, Peyron, Odile, Picon, Laurence, Pironneau, Olivier, Planton, Serge, Polcher, Jan, Pucéat, Emmanuelle, Rabatel, Antoine, Ramonet, Michel, Ramstein, Gilles, Reverdin, Gilles, Ribes, Aurélien, Roche, Didier, Roullet, Guillaume, Roux, Frank, Salas y Mélia, David, Sicre, Marie-Alexandrine, Swingedouw, Didier, Talagrand, Olivier, Tanré, Didier, Tatoni, Thierry, Thouret, Valérie, Thuillier, Gérard, Valcke, Sophie, Verron, Jacques, Vincent, Christian, Viovy, Nicolas, von Ballmoos, Peter, Wagnon, Patrick, Yiou, Pascal, GEOMAR LEGOS, Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Théorique de la Matière Condensée (LPTMC), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), and Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)
Subjects: effet de serre, climatologie, History & Philosophy Of Science, climat, [SDE.MCG]Environmental Sciences/Global Changes, SCI042000, météorologie, 01 natural sciences, 010305 fluids & plasmas, Outils et méthodes en recherche climatique, RBP, 0103 physical sciences, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 010306 general physics
Abstract: Qu'est ce que l'effet de serre ? Le rôle de l'homme sur le climat est-il détectable et comment ? Comment mesure-t-on la fonte de la banquise, le recul des glaciers de montagne ou bien encore l'élévation du niveau de la mer ? Comment les chercheurs font-ils pour modéliser un système aussi complexe que la planète terre ? Quelles données permettent de décrire et modéliser les climats passés ? Comment s'y prend-on pour prévoir l'évolution à venir du climat ? À l'écart de la polémique médiatique, Catherine Jeandel et Rémy Mosseri ont mobilisé plus d'une centaine de contributeurs qui livrent ici un panorama large des méthodes et outils mis en oeuvre pour étudier notre climat et son avenir. Ils montrent que, pour résoudre cette question extraordinairement complexe, une approche pluridisciplinaire est plus que jamais nécessaire, à la croisée de l'expérimentation, de l'observation, de la simulation et de la théorie. Un livre majeur.
Published: 2017

21. 7. L’usage des terres

Author: de Noblet-Ducoudré, Nathalie, Davin, Édouard, Laval, Katia, Guimberteau, Matthieu, Friedlingstein, Pierre, and Delire, Christine
Abstract: La reconnaissance du rôle de l’Homme sur le climat est généralement associée à l’augmentation de la concentration atmosphérique en gaz à effet de serre* (GES) et en aérosols d’origine anthropique, et à leurs implications sur le forçage radiatif* de la Terre (IPCC 2007). Pourtant l’Homme a également profondément modifié les paysages dès sa sédentarisation et pour divers usages. Le terme « usage des sols » regroupe des perturbations variées (mises en cultures, pâturages, urbanisation, exploitat...
Published: 2017

22. A representation of the phosphorus cycle for ORCHIDEE (revision 4520)

Author: Goll, Daniel S., Vuichard, Nicolas, Maignan, Fabienne, Jornet-Puig, Albert, Sardans, Jordi, Violette, Aurelie, Peng, Shushi, Sun, Yan, Kvakic, Marko, Guimberteau, Matthieu, Guenet, Bertrand, Zaehle, Soenke, Penuelas, Josep, Janssens, Ivan, Ciais, Philippe, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Global Ecology Unit CREAF-CEAB-CSIC, Universitat Autònoma de Barcelona (UAB), Laboratoire des Mécanismes et Transfert en Géologie (LMTG), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Swedish Defence Research Agency [Stockholm] (FOI), Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University [Beijing], Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, University of Antwerp (UA), ICOS-ATC (ICOS-ATC), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Universitat Autònoma de Barcelona [Barcelona] (UAB), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (ISPA), Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)-Université Pierre et Marie Curie - Paris 6 (UPMC), Institut Pierre-Simon-Laplace (IPSL), École normale supérieure - Paris (ENS Paris)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National d'Études Spatiales [Toulouse] (CNES)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), and Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE)
Subjects: cycle du carbone, Orchidee, [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], Physics, surface terrestre, hawai, chronoséquence, modèle, modèle orchidée, hawaii, nutrition, vegetation, ddc:550, phosphore du sol
Abstract: Paper contact with Daniel Goll: daniel.goll@lsce.ipsl.fr Agraïments: S. Zaehle was supported by the QUINCY project of the European Research Council (ERC-2014-CoG-647204). We thank two anonymous referees and the editor H. Sato for their constructive comments. Further, we thank the TRY initiative and database, which is hosted, developed, and maintained by J. Kattge and G. Boenisch (Max Planck Institute for Biogeochemistry, Jena, DE), for additional leaf stoichiometric data on Metrosideros, Ying-Ping Wang and Ben Houlton for sharing their data compilation on the Hawaiian sites, and Sebastiaan Luysseart for the discussions related to biomass allocation. Land surface models rarely incorporate the terrestrial phosphorus cycle and its interactions with the carbon cycle, despite the extensive scientific debate about the importance of nitrogen and phosphorus supply for future land carbon uptake. We describe a representation of the terrestrial phosphorus cycle for the ORCHIDEE land surface model, and evaluate it with data from nutrient manipulation experiments along a soil formation chronosequence in Hawaii. ORCHIDEE accounts for the influence of the nutritional state of vegetation on tissue nutrient concentrations, photosynthesis, plant growth, biomass allocation, biochemical (phosphatase-mediated) mineralization, and biological nitrogen fixation. Changes in the nutrient content (quality) of litter affect the carbon use efficiency of decomposition and in return the nutrient availability to vegetation. The model explicitly accounts for root zone depletion of phosphorus as a function of root phosphorus uptake and phosphorus transport from the soil to the root surface. The model captures the observed differences in the foliage stoichiometry of vegetation between an early (300-year) and a late (4.1?Myr) stage of soil development. The contrasting sensitivities of net primary productivity to the addition of either nitrogen, phosphorus, or both among sites are in general reproduced by the model. As observed, the model simulates a preferential stimulation of leaf level productivity when nitrogen stress is alleviated, while leaf level productivity and leaf area index are stimulated equally when phosphorus stress is alleviated. The nutrient use efficiencies in the model are lower than observed primarily due to biases in the nutrient content and turnover of woody biomass. We conclude that ORCHIDEE is able to reproduce the shift from nitrogen to phosphorus limited net primary productivity along the soil development chronosequence, as well as the contrasting responses of net primary productivity to nutrient addition.
Published: 2017

23. 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

Author: Guimberteau, Matthieu, Ciais, Philippe, Pablo Boisier, Juan, Paula Dutra Aguiar, Ana, Biemans, Hester, De Deurwaerder, Hannes, Galbraith, David, Kruijt, Bart, Langerwisch, Fanny, Poveda, German, Rammig, Anja, Andres Rodriguez, Daniel, Tejada, Graciela, Thonicke, Kirsten, Von Randow, Celso, Randow, Rita, Zhang, Ke, and Verbeeck, Hans
Subjects: Climate Resilience, WIMEK, Water and Food, Klimaatbestendigheid, Water en Voedsel, Life Science
Abstract: Deforestation in Amazon is expected to decrease evapotranspiration (ET) and to increase soil moisture and river discharge under prevailing energy-limited conditions. The magnitude and sign of the response of ET to deforestation depend both on the magnitude and regional patterns of land-cover change (LCC), as well as on climate change and CO2 levels. On the one hand, elevated CO2 decreases leaf-scale transpiration, but this effect could be offset by increased foliar area density. Using three regional LCC scenarios specifically established for the Brazilian and Bolivian Amazon, we investigate the impacts of climate change and deforestation on the surface hydrology of the Amazon Basin for this century, taking 2009 as a reference. For each LCC scenario, three land surface models (LSMs), LPJmL-DGVM, INLAND-DGVM and ORCHIDEE, are forced by bias-corrected climate simulated by three general circulation models (GCMs) of the IPCC 4th Assessment Report (AR4). On average, over the Amazon Basin with no deforestation, the GCM results indicate a temperature increase of 3.3ĝ€°C by 2100 which drives up the evaporative demand, whereby precipitation increases by 8.5 %, with a large uncertainty across GCMs. In the case of no deforestation, we found that ET and runoff increase by 5.0 and 14ĝ€%, respectively. However, in south-east Amazonia, precipitation decreases by 10ĝ€% at the end of the dry season and the three LSMs produce a 6ĝ€% decrease of ET, which is less than precipitation, so that runoff decreases by 22 %. For instance, the minimum river discharge of the Rio Tapajós is reduced by 31ĝ€% in 2100. To study the additional effect of deforestation, we prescribed to the LSMs three contrasted LCC scenarios, with a forest decline going from 7 to 34ĝ€% over this century. All three scenarios partly offset the climate-induced increase of ET, and runoff increases over the entire Amazon. In the south-east, however, deforestation amplifies the decrease of ET at the end of dry season, leading to a large increase of runoff (up to +27ĝ€% in the extreme deforestation case), offsetting the negative effect of climate change, thus balancing the decrease of low flows in the Rio Tapajós. These projections are associated with large uncertainties, which we attribute separately to the differences in LSMs, GCMs and to the uncertain range of deforestation. At the subcatchment scale, the uncertainty range on ET changes is shown to first depend on GCMs, while the uncertainty of runoff projections is predominantly induced by LSM structural differences. By contrast, we found that the uncertainty in both ET and runoff changes attributable to uncertain future deforestation is low.
Published: 2017

24. Deceleration of China’s human water use and its key drivers.

Author: Feng Zhou, Yan Bo, Ciais, Philippe, Dumas, Patrice, Qiuhong Tang, Xuhui Wang, Junguo Liu, Chunmiao Zheng, Polcher, Jan, Zun Yin, Guimberteau, Matthieu, Shushi Peng, Ottle, Catherine, Xining Zhao, Jianshi Zhao, Qian Tan, Lei Chen, Huizhong Shen, Hui Yang, and Shilong Piao
Subjects: WATER use, WATER shortages, ACCELERATION (Mechanics), IRRIGATION water, WATER efficiency
Abstract: Increased human water use combined with climate change have aggravated water scarcity from the regional to global scales. However, the lack of spatially detailed datasets limits our understanding of the historical water use trend and its key drivers. Here, we present a survey-based reconstruction of China’s sectoral water use in 341 prefectures during 1965 to 2013. The data indicate that water use has doubled during the entire study period, yet with a widespread slowdown of the growth rates from 10.66 km³·y−² before 1975 to 6.23 km³·y−² in 1975 to 1992, and further down to 3.59 km³·y−² afterward. These decelerations were attributed to reduced water use intensities of irrigation and industry, which partly offset the increase driven by pronounced socioeconomic development (i.e., economic growth, population growth, and structural transitions) by 55% in 1975 to 1992 and 83% after 1992. Adoptions for highly efficient irrigation and industrial water recycling technologies explained most of the observed reduction of water use intensities across China. These findings challenge conventional views about an acceleration in water use in China and highlight the opposing roles of different drivers for water use projections. [ABSTRACT FROM AUTHOR]
Published: 2020
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25. Matrix-Based Sensitivity Assessment of Soil Organic Carbon Storage: A Case Study from the ORCHIDEE-MICT Model

Author: Huang, Yuanyuan, primary, Zhu, Dan, additional, Ciais, Philippe, additional, Guenet, Bertrand, additional, Huang, Ye, additional, Goll, Daniel S., additional, Guimberteau, Matthieu, additional, Jornet-Puig, Albert, additional, Lu, Xingjie, additional, and Luo, Yiqi, additional
Published: 2018
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26. Supplementary material to "A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: an example from the Amazon region"

Author: Rammig, Anja, primary, Heinke, Jens, additional, Hofhansl, Florian, additional, Verbeeck, Hans, additional, Baker, Timothy R., additional, Christoffersen, Bradley, additional, Ciais, Phillipe, additional, De Deurwaerder, Hannes, additional, Fleischer, Katrin, additional, Galbraith, David, additional, Guimberteau, Matthieu, additional, Huth, Andreas, additional, Johnson, Michelle, additional, Krujit, Bart, additional, Langerwisch, Fanny, additional, Meir, Patrick, additional, Papastefanou, Phillip, additional, Sampaio, Gilvan, additional, Thonicke, Kirsten, additional, von Randow, Celso, additional, Zang, Christian, additional, and Rödig, Edna, additional
Published: 2018
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27. Supplementary material to "The importance of tree demography and root water uptake for modelling the carbon and water cycles of Amazonia"

Author: Joetzjer, Emilie, primary, Maignan, Fabienne, additional, Chave, Jérôme, additional, Goll, Daniel, additional, Poulter, Ben, additional, Barichivich, Jonathan, additional, Maréchaux, Isabelle, additional, Luyssaert, Sebastiaan, additional, Guimberteau, Matthieu, additional, Naudts, Kim, additional, Bonal, Damien, additional, and Ciais, Philippe, additional
Published: 2018
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28. The importance of tree demography and root water uptake for modelling the carbon and water cycles of Amazonia

Author: Joetzjer, Emilie, primary, Maignan, Fabienne, additional, Chave, Jérôme, additional, Goll, Daniel, additional, Poulter, Ben, additional, Barichivich, Jonathan, additional, Maréchaux, Isabelle, additional, Luyssaert, Sebastiaan, additional, Guimberteau, Matthieu, additional, Naudts, Kim, additional, Bonal, Damien, additional, and Ciais, Philippe, additional
Published: 2018
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29. ORCHILEAK (revision 3875): A new model branch to simulate carbon transfers along the terrestrial-aquatic continuum of the Amazon basin

Author: Lauerwald, Ronny, Regnier, Pierre, Camino-Serrano, Marta, Guenet, Bertrand, Guimberteau, Matthieu, Ducharne, Agnes, Polcher, Jan, Ciais, Phillipe, Lauerwald, Ronny, Regnier, Pierre, Camino-Serrano, Marta, Guenet, Bertrand, Guimberteau, Matthieu, Ducharne, Agnes, Polcher, Jan, and Ciais, Phillipe
Abstract: Lateral transfer of carbon (C) from terrestrial ecosystems into the inland water network is an important component of the global C cycle, which sustains a large aquatic CO2 evasion flux fuelled by the decomposition of allochthonous C inputs. Globally, estimates of the total C exports through the terrestrial-aquatic interface range from 1.5 to 2.7PgCyr-1 (Cole et al. 2007; Battin et al. 2009; Tranvik et al. 2009), i.e. of the order of 2-5% of the terrestrial NPP. Earth system models (ESMs) of the climate system ignore these lateral transfers of C, and thus likely overestimate the terrestrial C sink. In this study, we present the implementation of fluvial transport of dissolved organic carbon (DOC) and CO2 into ORCHIDEE (Organising Carbon and Hydrology in Dynamic Ecosystems), the land surface scheme of the Institut Pierre-Simon Laplace ESM. This new model branch, called ORCHILEAK, represents DOC production from canopy and soils, DOC and CO2 leaching from soils to streams, DOC decomposition, and CO2 evasion to the atmosphere during its lateral transport in rivers, as well as exchange with the soil carbon and litter stocks on floodplains and in swamps. We parameterized and validated ORCHILEAK for the Amazon basin, the world's largest river system with regard to discharge and one of the most productive ecosystems in the world. With ORCHILEAK, we are able to reproduce observed terrestrial and aquatic fluxes of DOC and CO2 in the Amazon basin, both in terms of mean values and seasonality. In addition, we are able to resolve the spatio-temporal variability in C fluxes along the canopy-soil-water continuum at high resolution (1°, daily) and to quantify the different terrestrial contributions to the aquatic C fluxes. We simulate that more than two-thirds of the Amazon's fluvial DOC export are contributed by the decomposition of submerged litter. Throughfall DOC fluxes from canopy to ground are about as high as the total DOC inputs to inland waters. The latter, however, are ma, SCOPUS: ar.j, info:eu-repo/semantics/published
Published: 2017

30. ORCHILEAK (revision 3875): a new model branch to simulate carbon transfers along the terrestrial–aquatic continuum of the Amazon basin

Author: Lauerwald, Ronny, primary, Regnier, Pierre, additional, Camino-Serrano, Marta, additional, Guenet, Bertrand, additional, Guimberteau, Matthieu, additional, Ducharne, Agnès, additional, Polcher, Jan, additional, and Ciais, Philippe, additional
Published: 2017
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31. RESPONSE TO THE REFEREE #1 COMMENTS

Author: Guimberteau, Matthieu, primary
Published: 2017
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32. RESPONSE TO THE REFEREE #2 COMMENTS

Author: Guimberteau, Matthieu, primary
Published: 2017
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33. Response to the interactive comment from Executive editor

Author: Guimberteau, Matthieu, primary
Published: 2017
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34. Diagnosing phosphorus limitations in natural terrestrial ecosystems in carbon cycle models

Author: Sun, Yan, primary, Peng, Shushi, additional, Goll, Daniel S., additional, Ciais, Philippe, additional, Guenet, Bertrand, additional, Guimberteau, Matthieu, additional, Hinsinger, Philippe, additional, Janssens, Ivan A., additional, Peñuelas, Josep, additional, Piao, Shilong, additional, Poulter, Benjamin, additional, Violette, Aurélie, additional, Yang, Xiaojuan, additional, Yin, Yi, additional, and Zeng, Hui, additional
Published: 2017
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35. Supplementary material to "ORCHIDEE-MICT (revision 4126), a land surface model for the high-latitudes: model description and validation"

Author: Guimberteau, Matthieu, primary, Zhu, Dan, additional, Maignan, Fabienne, additional, Huang, Ye, additional, Yue, Chao, additional, Dantec-Nédélec, Sarah, additional, Ottlé, Catherine, additional, Jornet-Puig, Albert, additional, Bastos, Ana, additional, Laurent, Pierre, additional, Goll, Daniel, additional, Bowring, Simon, additional, Chang, Jinfeng, additional, Guenet, Bertrand, additional, Tifafi, Marwa, additional, Peng, Shushi, additional, Krinner, Gerhard, additional, Ducharne, Agnès, additional, Wang, Fuxing, additional, Wang, Tao, additional, Wang, Xuhui, additional, Wang, Yilong, additional, Yin, Zun, additional, Lauerwald, Ronny, additional, Joetzjer, Emilie, additional, Qiu, Chunjing, additional, Kim, Hyungjun, additional, and Ciais, Philippe, additional
Published: 2017
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36. ORCHIDEE-MICT (revision 4126), a land surface model for the high-latitudes: model description and validation

Author: Guimberteau, Matthieu, primary, Zhu, Dan, additional, Maignan, Fabienne, additional, Huang, Ye, additional, Yue, Chao, additional, Dantec-Nédélec, Sarah, additional, Ottlé, Catherine, additional, Jornet-Puig, Albert, additional, Bastos, Ana, additional, Laurent, Pierre, additional, Goll, Daniel, additional, Bowring, Simon, additional, Chang, Jinfeng, additional, Guenet, Bertrand, additional, Tifafi, Marwa, additional, Peng, Shushi, additional, Krinner, Gerhard, additional, Ducharne, Agnès, additional, Wang, Fuxing, additional, Wang, Tao, additional, Wang, Xuhui, additional, Wang, Yilong, additional, Yin, Zun, additional, Lauerwald, Ronny, additional, Joetzjer, Emilie, additional, Qiu, Chunjing, additional, Kim, Hyungjun, additional, and Ciais, Philippe, additional
Published: 2017
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37. A representation of the phosphorus cycle for ORCHIDEE (revision 3985)

Author: Goll, Daniel S., primary, Vuichard, Nicolas, additional, Maignan, Fabienne, additional, Jornet-Puig, Albert, additional, Sardans, Jordi, additional, Violette, Aurelie, additional, Peng, Shushi, additional, Sun, Yan, additional, Kvakic, Marko, additional, Guimberteau, Matthieu, additional, Guenet, Bertrand, additional, Zaehle, Soenke, additional, Peñuelas, Josep, additional, Janssens, Ivan, additional, and Ciais, Philippe, additional
Published: 2017
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38. Supplementary material to "ORCHILEAK: A new model branch to simulate carbon transfers along the terrestrial-aquatic continuum of the Amazon basin"

Author: Lauerwald, Ronny, primary, Regnier, Pierre, additional, Camino-Serrano, Marta, additional, Guenet, Bertrand, additional, Guimberteau, Matthieu, additional, Ducharne, Agnès, additional, Polcher, Jan, additional, and Ciais, Philippe, additional
Published: 2017
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39. ORCHILEAK: A new model branch to simulate carbon transfers along the terrestrial-aquatic continuum of the Amazon basin

Author: Lauerwald, Ronny, primary, Regnier, Pierre, additional, Camino-Serrano, Marta, additional, Guenet, Bertrand, additional, Guimberteau, Matthieu, additional, Ducharne, Agnès, additional, Polcher, Jan, additional, and Ciais, Philippe, additional
Published: 2017
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40. Answer to Editor

Author: Guimberteau, Matthieu, primary
Published: 2017
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41. Answers to Anonymous Referee #2

Author: Guimberteau, Matthieu, primary
Published: 2016
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42. Answers to Anonymous Referee #3

Author: Guimberteau, Matthieu, primary
Published: 2016
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43. Answers to Anonymous Referee #1

Author: Guimberteau, Matthieu, primary
Published: 2016
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44. Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Author: Johnson, Michelle O., Galbraith, David, Gloor, Manuel, De Deurwaerder, Hannes, Guimberteau, Matthieu, Rammig, Anja, Thonicke, Kirsten, Verbeeck, Hans, Von Randow, Celso, Monteagudo, Abel, Phillips, Oliver L., Brienen, Roel J.W., Feldpausch, Ted R., Lopez Gonzalez, Gabriela, Fauset, Sophie, Quesada, Carlos A., Christoffersen, Bradley, Ciais, Philippe, Sampaio, Gilvan, Kruijt, Bart, Meir, Patrick, Moorcroft, Paul, Zhang, Ke, Alvarez-Davila, Esteban, Alves De Oliveira, Atila, Amaral, Ieda, Andrade, Ana, Aragao, Luiz E.O.C., Araujo-Murakami, Alejandro, Arets, Eric J.M.M., Arroyo, Luzmila, Aymard, Gerardo A., Baraloto, Christopher, Barroso, Jocely, Bonal, Damien, Boot, Rene, Camargo, Jose, Chave, Jerome, Cogollo, Alvaro, Cornejo Valverde, Fernando, Lola Da Costa, Antonio C., Di Fiore, Anthony, Ferreira, Leandro, Higuchi, Niro, Honorio, Euridice N., Killeen, Tim J., Laurance, Susan G., Laurance, William F., Licona, Juan, Lovejoy, Thomas, Malhi, Yadvinder, Marimon, Bia, Marimon, Ben Hur, Matos, Darley C.L., Mendoza, Casimiro, Neill, David A., Pardo, Guido, Peña-Claros, Marielos, Pitman, Nigel C.A., Poorter, Lourens, Prieto, Adriana, Ramirez-Angulo, Hirma, Roopsind, Anand, Rudas, Agustin, Salomao, Rafael P., Silveira, Marcos, Stropp, Juliana, Ter Steege, Hans, Terborgh, John, Thomas, Raquel, Toledo, Marisol, Torres-Lezama, Armando, van der Heijden, Geertje M.F., Vasquez, Rodolfo, Guimarães Vieira, Ima Cèlia, Vilanova, Emilio, Vos, Vincent A., Baker, Timothy R., Johnson, Michelle O., Galbraith, David, Gloor, Manuel, De Deurwaerder, Hannes, Guimberteau, Matthieu, Rammig, Anja, Thonicke, Kirsten, Verbeeck, Hans, Von Randow, Celso, Monteagudo, Abel, Phillips, Oliver L., Brienen, Roel J.W., Feldpausch, Ted R., Lopez Gonzalez, Gabriela, Fauset, Sophie, Quesada, Carlos A., Christoffersen, Bradley, Ciais, Philippe, Sampaio, Gilvan, Kruijt, Bart, Meir, Patrick, Moorcroft, Paul, Zhang, Ke, Alvarez-Davila, Esteban, Alves De Oliveira, Atila, Amaral, Ieda, Andrade, Ana, Aragao, Luiz E.O.C., Araujo-Murakami, Alejandro, Arets, Eric J.M.M., Arroyo, Luzmila, Aymard, Gerardo A., Baraloto, Christopher, Barroso, Jocely, Bonal, Damien, Boot, Rene, Camargo, Jose, Chave, Jerome, Cogollo, Alvaro, Cornejo Valverde, Fernando, Lola Da Costa, Antonio C., Di Fiore, Anthony, Ferreira, Leandro, Higuchi, Niro, Honorio, Euridice N., Killeen, Tim J., Laurance, Susan G., Laurance, William F., Licona, Juan, Lovejoy, Thomas, Malhi, Yadvinder, Marimon, Bia, Marimon, Ben Hur, Matos, Darley C.L., Mendoza, Casimiro, Neill, David A., Pardo, Guido, Peña-Claros, Marielos, Pitman, Nigel C.A., Poorter, Lourens, Prieto, Adriana, Ramirez-Angulo, Hirma, Roopsind, Anand, Rudas, Agustin, Salomao, Rafael P., Silveira, Marcos, Stropp, Juliana, Ter Steege, Hans, Terborgh, John, Thomas, Raquel, Toledo, Marisol, Torres-Lezama, Armando, van der Heijden, Geertje M.F., Vasquez, Rodolfo, Guimarães Vieira, Ima Cèlia, Vilanova, Emilio, Vos, Vincent A., and Baker, Timothy R.
Abstract: Understanding the processes that determine aboveground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity (woody NPP) and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size-structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influence AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates, and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP, and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs
Published: 2016

45. Evaluation of the ORCHIDEE ecosystem model over Africa against 25 years of satellite-based water and carbon measurements

Author: Traore, Abdoul Khadre, Ciais, Philippe, Vuichard, Nicolas, Poulter, Benjamin, Viovy, Nicolas, Guimberteau, Matthieu, Jung, Martin, Myneni, Ranga, Fisher, Joshua, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Montana State University (MSU), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, Boston University [Boston] (BU), University of California [Berkeley] (UC Berkeley), University of California (UC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), University of California [Berkeley], and University of California
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology
Abstract: International audience; Few studies have evaluated land surface models for African ecosystems. Here we evaluate the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process-based model for the interannual variability (IAV) of the fraction of absorbed active radiation, the gross primary productivity (GPP), soil moisture, and evapotranspiration (ET). Two ORCHIDEE versions are tested, which differ by their soil hydrology parameterization, one with a two-layer simple bucket and the other a more complex 11-layer soil-water diffusion. In addition, we evaluate the sensitivity of climate forcing data, atmospheric CO 2 , and soil depth. Beside a very generic vegetation parameterization, ORCHIDEE simulates rather well the IAV of GPP and ET (0.5 < r < 0.9 interannual correlation) over Africa except in forestlands. The ORCHIDEE 11-layer version outperforms the two-layer version for simulating IAV of soil moisture, whereas both versions have similar performance of GPP and ET. Effects of CO 2 trends, and of variable soil depth on the IAV of GPP, ET, and soil moisture are small, although these drivers influence the trends of these variables. The meteorological forcing data appear to be quite important for faithfully reproducing the IAV of simulated variables, suggesting that in regions with sparse weather station data, the model uncertainty is strongly related to uncertain meteorological forcing. Simulated variables are positively and strongly correlated with precipitation but negatively and weakly correlated with temperature and solar radiation. Model-derived and observation-based sensitivities are in agreement for the driving role of precipitation. However, the modeled GPP is too sensitive to precipitation, suggesting that processes such as increased water use efficiency during drought need to be incorporated in ORCHIDEE.
Published: 2014

46. 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

Author: Guimberteau, Matthieu, primary, Ciais, Philippe, additional, Ducharne, Agnès, additional, Boisier, Juan Pablo, additional, Aguiar, Ana Paula Dutra, additional, Biemans, Hester, additional, De Deurwaerder, Hannes, additional, Galbraith, David, additional, Kruijt, Bart, additional, Langerwisch, Fanny, additional, Poveda, German, additional, Rammig, Anja, additional, Rodriguez, Daniel Andres, additional, Tejada, Graciela, additional, Thonicke, Kirsten, additional, Von Randow, Celso, additional, Von Randow, Rita C. S., additional, Zhang, Ke, additional, and Verbeeck, Hans, additional
Published: 2016
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47. Supplementary material to "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"

Author: Guimberteau, Matthieu, primary, Ciais, Philippe, additional, Ducharne, Agnès, additional, Boisier, Juan Pablo, additional, Aguiar, Ana Paula Dutra, additional, Biemans, Hester, additional, De Deurwaerder, Hannes, additional, Galbraith, David, additional, Kruijt, Bart, additional, Langerwisch, Fanny, additional, Poveda, German, additional, Rammig, Anja, additional, Rodriguez, Daniel Andres, additional, Tejada, Graciela, additional, Thonicke, Kirsten, additional, Von Randow, Celso, additional, Von Randow, Rita C. S., additional, Zhang, Ke, additional, and Verbeeck, Hans, additional
Published: 2016
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48. Variation in stem mortality rates determines patterns of above‐ground biomass in A mazonian forests: implications for dynamic global vegetation models

Author: Johnson, Michelle O., primary, Galbraith, David, additional, Gloor, Manuel, additional, De Deurwaerder, Hannes, additional, Guimberteau, Matthieu, additional, Rammig, Anja, additional, Thonicke, Kirsten, additional, Verbeeck, Hans, additional, Randow, Celso, additional, Monteagudo, Abel, additional, Phillips, Oliver L., additional, Brienen, Roel J. W., additional, Feldpausch, Ted R., additional, Lopez Gonzalez, Gabriela, additional, Fauset, Sophie, additional, Quesada, Carlos A., additional, Christoffersen, Bradley, additional, Ciais, Philippe, additional, Sampaio, Gilvan, additional, Kruijt, Bart, additional, Meir, Patrick, additional, Moorcroft, Paul, additional, Zhang, Ke, additional, Alvarez‐Davila, Esteban, additional, Alves de Oliveira, Atila, additional, Amaral, Ieda, additional, Andrade, Ana, additional, Aragao, Luiz E. O. C., additional, Araujo‐Murakami, Alejandro, additional, Arets, Eric J. M. M., additional, Arroyo, Luzmila, additional, Aymard, Gerardo A., additional, Baraloto, Christopher, additional, Barroso, Jocely, additional, Bonal, Damien, additional, Boot, Rene, additional, Camargo, Jose, additional, Chave, Jerome, additional, Cogollo, Alvaro, additional, Cornejo Valverde, Fernando, additional, Lola da Costa, Antonio C., additional, Di Fiore, Anthony, additional, Ferreira, Leandro, additional, Higuchi, Niro, additional, Honorio, Euridice N., additional, Killeen, Tim J., additional, Laurance, Susan G., additional, Laurance, William F., additional, Licona, Juan, additional, Lovejoy, Thomas, additional, Malhi, Yadvinder, additional, Marimon, Bia, additional, Marimon, Ben Hur, additional, Matos, Darley C. L., additional, Mendoza, Casimiro, additional, Neill, David A., additional, Pardo, Guido, additional, Peña‐Claros, Marielos, additional, Pitman, Nigel C. A., additional, Poorter, Lourens, additional, Prieto, Adriana, additional, Ramirez‐Angulo, Hirma, additional, Roopsind, Anand, additional, Rudas, Agustin, additional, Salomao, Rafael P., additional, Silveira, Marcos, additional, Stropp, Juliana, additional, Steege, Hans, additional, Terborgh, John, additional, Thomas, Raquel, additional, Toledo, Marisol, additional, Torres‐Lezama, Armando, additional, Heijden, Geertje M. F., additional, Vasquez, Rodolfo, additional, Guimarães Vieira, Ima Cèlia, additional, Vilanova, Emilio, additional, Vos, Vincent A., additional, and Baker, Timothy R., additional
Published: 2016
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49. Multicriteria evaluation of discharge simulation in dynamic global vegetation models

Author: Yang, Hui, Piao, Shilong, Zeng, Zhenzhong, Ciais, Philippe, Yin, Yi, Friedlingstein, Pierre, Sitch, Stephen, Ahlström, Anders, Guimberteau, Matthieu, Huntingford, Chris, Levis, Sam, Levy, Peter E., Huang, Mengtian, Li, Yue, Li, Xiran, Lomas, Mark R., Peylin, Philippe, Poulter, Ben, Viovy, Nicolas, Zaehle, Soenke, Zeng, Ning, Zhao, Fang, Wang, Lei, Yang, Hui, Piao, Shilong, Zeng, Zhenzhong, Ciais, Philippe, Yin, Yi, Friedlingstein, Pierre, Sitch, Stephen, Ahlström, Anders, Guimberteau, Matthieu, Huntingford, Chris, Levis, Sam, Levy, Peter E., Huang, Mengtian, Li, Yue, Li, Xiran, Lomas, Mark R., Peylin, Philippe, Poulter, Ben, Viovy, Nicolas, Zaehle, Soenke, Zeng, Ning, Zhao, Fang, and Wang, Lei
Abstract: In this study, we assessed the performance of discharge simulations by coupling the runoff from seven Dynamic Global Vegetation Models (DGVMs; LPJ, ORCHIDEE, Sheffield-DGVM, TRIFFID, LPJ-GUESS, CLM4CN, and OCN) to one river routing model for 16 large river basins. The results show that the seasonal cycle of river discharge is generally modeled well in the low and middle latitudes but not in the high latitudes, where the peak discharge (due to snow and ice melting) is underestimated. For the annual mean discharge, the DGVMs chained with the routing model show an underestimation. Furthermore, the 30 year trend of discharge is also underestimated. For the interannual variability of discharge, a skill score based on overlapping of probability density functions (PDFs) suggests that most models correctly reproduce the observed variability (correlation coefficient higher than 0.5; i.e., models account for 50% of observed interannual variability) except for the Lena, Yenisei, Yukon, and the Congo river basins. In addition, we compared the simulated runoff from different simulations where models were forced with either fixed or varying land use. This suggests that both seasonal and annual mean runoff has been little affected by land use change but that the trend itself of runoff is sensitive to land use change. None of the models when considered individually show significantly better performances than any other and in all basins. This suggests that based on current modeling capability, a regional-weighted average of multimodel ensemble projections might be appropriate to reduce the bias in future projection of global river discharge.
Published: 2015

50. Evaluation of ORCHIDEE-MICT-simulated soil moisture over China and impacts of different atmospheric forcing data.

Author: Yin, Zun, Ottlé, Catherine, Ciais, Philippe, Guimberteau, Matthieu, Wang, Xuhui, Zhu, Dan, Maignan, Fabienne, Peng, Shushi, Piao, Shilong, Polcher, Jan, Zhou, Feng, Kim, Hyungjun, and other China-Trend-Stream project members
Subjects: SOIL moisture, ATMOSPHERIC models, LAND surface temperature, HYDROLOGY, WEATHER forecasting
Abstract: Soil moisture is a key variable of land surface hydrology, and its correct representation in land surface models is crucial for local to global climate predictions. The errors may come from the model itself (structure and parameterization) but also from the meteorological forcing used. In order to separate the two source of errors, four atmospheric forcing datasets, GSWP3 (Global Soil Wetness Project Phase 3), PGF (Princeton Global meteorological Forcing), CRU-NCEP (Climatic Research Unit-National Center for Environmental Prediction), and WFDEI (WATCH Forcing Data methodology applied to ERA-Interim reanalysis data), were used to drive simulations in China by the land surface model ORCHIDEE-MICT(ORganizing Carbon and Hydrology in Dynamic EcosystEms: aMeliorated Interactions between Carbon and Temperature). Simulated soil moisture was compared with in situ and satellite datasets at different spatial and temporal scales in order to (1) estimate the ability of ORCHIDEE-MICT to represent soil moisture dynamics in China; (2) demonstrate the most suitable forcing dataset for further hydrological studies in Yangtze and Yellow River basins; and (3) understand the discrepancies of simulated soil moisture among simulations. Results showed that ORCHIDEE-MICT can simulate reasonable soil moisture dynamics in China, but the quality varies with forcing data. Simulated soil moisture driven by GSWP3 and WFDEI shows the best performance according to the root mean square error (RMSE) and correlation coefficient, respectively, suggesting that both GSWP3 and WFDEI are good choices for further hydrological studies in the two catchments. The mismatch between simulated and observed soil moisture is mainly explained by the bias of magnitude, suggesting that the parameterization in ORCHIDEE-MICT should be revised for further simulations in China. Underestimated soil moisture in the North China Plain demonstrates possible significant impacts of human activities like irrigation on soil moisture variation, which was not considered in our simulations. Finally, the discrepancies of meteorological variables and simulated soil moisture among the four simulations are analyzed. The result shows that the discrepancy of soil moisture is mainly explained by differences in precipitation frequency and air humidity rather than differences in precipitation amount. [ABSTRACT FROM AUTHOR]
Published: 2018
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