Letteratura scientifica selezionata sul tema "ORCHIDEE and LMDZ models"

Abstract Two different coupled climate–vegetation models, the Community Climate Model version 3 coupled to the Integrated Biosphere Simulator (CCM3–IBIS) and the Laboratoire de Météorologie Dynamique’s climate model coupled to the Organizing Carbon and Hydrology in Dynamic Ecosystems model (LMDz–ORCHIDEE), are used to study the effects of vegetation dynamics on climate variability. Two sets of simulations of the preindustrial climate are performed using fixed climatological sea surface temperatures: one set taking into account vegetation cover dynamics and the other keeping the vegetation cover fixed. Spectral analysis of the simulated precipitation and temperature over land shows that for both models the interactions between vegetation dynamics and the atmosphere enhance the low-frequency variability of the biosphere–atmosphere system at time scales ranging from a few years to a century. Despite differences in the magnitude of the signal between the two models, this confirms that vegetation dynamics introduces a long-term memory into the climate system by slowly modifying the physical characteristics of the land surface (albedo, roughness evapotranspiration). Unrealistic modeled feedbacks between the vegetation and the atmosphere would cast doubts on this result. The simulated feedback processes in the models used in this work are compared to the observed using a recently developed statistical approach. The models simulate feedbacks of the right sign and order of magnitude over large regions of the globe: positive temperature feedback in the mid- to high latitudes, negative feedback in semiarid regions, and positive precipitation feedback in semiarid regions. The models disagree in the tropics, where there is no statistical significance in the observations. The realistic modeled vegetation–atmosphere feedback gives us confidence that the vegetation dynamics enhancement of the long-term climate variability is not a model artifact.

Abstract. In spite of the importance of land ecosystems in offsetting carbon dioxide emissions released by anthropogenic activities into the atmosphere, the spatiotemporal dynamics of terrestrial carbon fluxes remain largely uncertain at regional to global scales. Over the past decade, data assimilation (DA) techniques have grown in importance for improving these fluxes simulated by terrestrial biosphere models (TBMs), by optimizing model parameter values while also pinpointing possible parameterization deficiencies. Although the joint assimilation of multiple data streams is expected to constrain a wider range of model processes, their actual benefits in terms of reduction in model uncertainty are still under-researched, also given the technical challenges. In this study, we investigated with a consistent DA framework and the ORCHIDEE-LMDz TBM–atmosphere model how the assimilation of different combinations of data streams may result in different regional to global carbon budgets. To do so, we performed comprehensive DA experiments where three datasets (in situ measurements of net carbon exchange and latent heat fluxes, spaceborne estimates of the normalized difference vegetation index, and atmospheric CO2 concentration data measured at stations) were assimilated alone or simultaneously. We thus evaluated their complementarity and usefulness to constrain net and gross C land fluxes. We found that a major challenge in improving the spatial distribution of the land C sinks and sources with atmospheric CO2 data relates to the correction of the soil carbon imbalance.

Abstract. In Earth system modelling, a description of the energy budget of the vegetated surface layer is fundamental as it determines the meteorological conditions in the planetary boundary layer and as such contributes to the atmospheric conditions and its circulation. The energy budget in most Earth system models has been based on a big-leaf approach, with averaging schemes that represent in-canopy processes. Furthermore, to be stable, that is to say, over large time steps and without large iterations, a surface layer model should be capable of implicit coupling to the atmospheric model. Surface models with large time steps, however, have difficulties in reproducing consistently the energy balance in field observations. Here we outline a newly developed numerical model for energy budget simulation, as a component of the land surface model ORCHIDEE-CAN (Organising Carbon and Hydrology In Dynamic Ecosystems – CANopy). This new model implements techniques from single-site canopy models in a practical way. It includes representation of in-canopy transport, a multi-layer long-wave radiation budget, height-specific calculation of aerodynamic and stomatal conductance, and interaction with the bare-soil flux within the canopy space. Significantly, it avoids iterations over the height of the canopy and so maintains implicit coupling to the atmospheric model LMDz (Laboratoire de Météorologie Dynamique Zoomed model). As a first test, the model is evaluated against data from both an intensive measurement campaign and longer-term eddy-covariance measurements for the intensively studied Eucalyptus stand at Tumbarumba, Australia. The model performs well in replicating both diurnal and annual cycles of energy and water fluxes, as well as the vertical gradients of temperature and of sensible heat fluxes.

Abstract. In Earth system modelling, a description of the energy budget of the vegetated surface layer is fundamental as it determines the meteorological conditions in the planetary boundary layer and as such contributes to the atmospheric conditions and its circulation. The energy budget in most Earth system models has long been based on a "big-leaf approach", with averaging schemes that represent in-canopy processes. Such models have difficulties in reproducing consistently the energy balance in field observations. We here outline a newly developed numerical model for energy budget simulation, as a component of the land surface model ORCHIDEE-CAN (Organising Carbon and Hydrology In Dynamic Ecosystems – CANopy). This new model implements techniques from single-site canopy models in a practical way. It includes representation of in-canopy transport, a multilayer longwave radiation budget, height-specific calculation of aerodynamic and stomatal conductance, and interaction with the bare soil flux within the canopy space. Significantly, it avoids iterations over the height of tha canopy and so maintains implicit coupling to the atmospheric model LMDz. As a first test, the model is evaluated against data from both an intensive measurement campaign and longer term eddy covariance measurements for the intensively studied Eucalyptus stand at Tumbarumba, Australia. The model performs well in replicating both diurnal and annual cycles of fluxes, as well as the gradients of sensible heat fluxes. However, the model overestimates sensible heat flux against an underestimate of the radiation budget. Improved performance is expected through the implementation of a more detailed calculation of stand albedo and a more up-to-date stomatal conductance calculation.

Abstract. Large uncertainties in land surface models (LSMs) simulations still arise from inaccurate forcing, poor description of land surface heterogeneity (soil and vegetation properties), incorrect model parameter values and incomplete representation of biogeochemical processes. The recent increase in the number and type of carbon cycle-related observations, including both in situ and remote sensing measurements, has opened a new road to optimize model parameters via robust statistical model–data integration techniques, in order to reduce the uncertainties of simulated carbon fluxes and stocks. In this study we present a carbon cycle data assimilation system that assimilates three major data streams, namely the Moderate Resolution Imaging Spectroradiometer (MODIS)-Normalized Difference Vegetation Index (NDVI) observations of vegetation activity, net ecosystem exchange (NEE) and latent heat (LE) flux measurements at more than 70 sites (FLUXNET), as well as atmospheric CO2 concentrations at 53 surface stations, in order to optimize the main parameters (around 180 parameters in total) of the Organizing Carbon and Hydrology in Dynamics Ecosystems (ORCHIDEE) LSM (version 1.9.5 used for the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations). The system relies on a stepwise approach that assimilates each data stream in turn, propagating the information gained on the parameters from one step to the next. Overall, the ORCHIDEE model is able to achieve a consistent fit to all three data streams, which suggests that current LSMs have reached the level of development to assimilate these observations. The assimilation of MODIS-NDVI (step 1) reduced the growing season length in ORCHIDEE for temperate and boreal ecosystems, thus decreasing the global mean annual gross primary production (GPP). Using FLUXNET data (step 2) led to large improvements in the seasonal cycle of the NEE and LE fluxes for all ecosystems (i.e., increased amplitude for temperate ecosystems). The assimilation of atmospheric CO2, using the general circulation model (GCM) of the Laboratoire de Météorologie Dynamique (LMDz; step 3), provides an overall constraint (i.e., constraint on large-scale net CO2 fluxes), resulting in an improvement of the fit to the observed atmospheric CO2 growth rate. Thus, the optimized model predicts a land C (carbon) sink of around 2.2 PgC yr−1 (for the 2000–2009 period), which is more compatible with current estimates from the Global Carbon Project (GCP) than the prior value. The consistency of the stepwise approach is evaluated with back-compatibility checks. The final optimized model (after step 3) does not significantly degrade the fit to MODIS-NDVI and FLUXNET data that were assimilated in the first two steps, suggesting that a stepwise approach can be used instead of the more “challenging” implementation of a simultaneous optimization in which all data streams are assimilated together. Most parameters, including the scalar of the initial soil carbon pool size, changed during the optimization with a large error reduction. This work opens new perspectives for better predictions of the land carbon budgets.

Abstract. Here we perform a detailed comparison between climate model results and climate reconstructions in western Europe and the Mediterranean area for the mid-Piacenzian warm interval (ca 3 Myr ago) of the Late Pliocene epoch. This region is particularly well suited for such a comparison as several quantitative climate estimates from local pollen records are available. They show evidence for temperatures significantly warmer than today over the whole area, mean annual precipitation higher in northwestern Europe and equivalent to modern values in its southwestern part. To improve our comparison, we have performed high resolution simulations of the mid-Piacenzian climate using the LMDz atmospheric general circulation model (AGCM) with a stretched grid which allows a finer resolution over Europe. In a first step, we applied the PRISM2 (Pliocene Research, Interpretation, and Synoptic Mapping) boundary conditions except that we used modern terrestrial vegetation. Second, we simulated the vegetation for this period by forcing the ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) dynamic global vegetation model (DGVM) with the climatic outputs from the AGCM. We then supplied this simulated terrestrial vegetation cover as an additional boundary condition in a second AGCM run. This gives us the opportunity to investigate the model's sensitivity to the simulated vegetation changes in a global warming context. Model results and data show a great consistency for mean annual temperatures, indicating increases by up to 4°C in the study area, and some disparities, in particular in the northern Mediterranean sector, as regards winter and summer temperatures. Similar continental mean annual precipitation and moisture patterns are predicted by the model, which broadly underestimates the wetter conditions indicated by the data in northwestern Europe. The biogeophysical effects due to the changes in vegetation simulated by ORCHIDEE are weak, both in terms of the hydrological cycle and of the temperatures, at the regional scale of the European and Mediterranean mid-latitudes. In particular, they do not contribute to improve the model-data comparison. Their main influence concerns seasonal temperatures, with a decrease of the temperatures of the warmest month, and an overall reduction of the intensity of the continental hydrological cycle.

Abstract. The Middle Pliocene (around 3 Ma) is a period characterized by a climate significantly warmer than today, at the global scale, as attested by abundant paleoclimate archives as well as several climate modelling studies. There we perform a detailed comparison between climate model results and climate reconstructions in western Europe and the Mediterranean area. This region is particularly well suited for such a comparison as several climate reconstructions from local pollen records covering the Mid-Pliocene provide quantitative terrestrial climate estimates. They show evidence for temperatures significantly warmer than today over the whole area, mean annual precipitation higher in northwestern Europe and equivalent to modern values in its southwestern part. To improve our comparison, we have performed high resolution simulations of the Mid-Pliocene climate using the LMDz atmospheric general circulation model (AGCM) with a stretched grid which allows a finer resolution over Europe. In a first step, we applied the PRISM2 (Pliocene Research, Interpretation, and Synoptic Mapping) boundary conditions except that we used modern terrestrial vegetation. Second, we simulated the vegetation for this period by forcing the Dynamic Global Vegetation Model ORCHIDEE with the climatic outputs from the AGCM. We then supplied this simulated terrestrial vegetation cover as an additional boundary condition in a second AGCM run. This gives us the opportunity not only to compare the generated vegetation cover to pollen records but also to investigate the model's sensitivity to the simulated vegetation changes in a global warming context. Model results and data show a great consistency for mean annual temperatures, indicating increases by up to 4°C in the study area. Comparison of the simulated winter and summer temperatures to pollen-based estimates show some disparities, in particular in the northern Mediterranean sector. The latitudinal distribution of precipitation depicted by pollen data over land is not reproduced by the model. Most excess Mid-Pliocene precipitation occurs over the North Atlantic but a slight weakening of the atmospheric transport does not allow for wetter conditions to establish in northwestern Europe, as suggested by the data. Continental moisture patterns predicted by the model are similar to those of the mean annual precipitation. Model results broadly underestimate the levels of available moisture indicated by the data. The biogeophysical effects due to the changes in vegetation simulated by ORCHIDEE, are weak, both in terms of the hydrological cycle and of the temperatures, at the regional scale of the European and Mediterranean mid-latitudes. In particular, they do not contribute to improve the model-data comparison. Their main influence concerns seasonal temperatures, with a decrease of the temperatures of the warmest month, and an overall reduction of the intensity of the continental hydrological cycle. Predicted climatic changes do not only arise from local processes but also result from an altered large-scale circulation initiated by regional-scale land cover changes.

Abstract. Our ability to predict future climate change relies on our understanding of current and future CO2 fluxes, particularly at the scale of regions (100–1000 km). Nowadays, CO2 regional sources and sinks are still poorly known. Inverse transport modeling, a method often used to quantify these fluxes, relies on atmospheric CO2 measurements. One of the main challenge for the transport models used in the inversions is to reproduce properly CO2 vertical gradients between the boundary layer and the free troposphere, as these gradients impact on the partitioning ot the calculated fluxes between the different model regions. Vertical CO2 profiles are very well suited to assess the performances of the models. In this paper, we conduct a comparison between observed and modeled CO2 profiles recorded during two CAATER campaigns that occurred in May 2001 and October 2002 over western Europe, and that we have described in a companion paper. We test different combinations between a global transport model (LMDZt), a mesoscale transport model (CHIMERE), and different sets of biospheric fluxes, those latter all chosen to have a diurnal cycle (CASA, SiB2 and ORCHIDEE). The vertical profile comparison shows that: (1) in most cases the influence of the biospheric flux is small but sometimes not negligeable, ORCHIDEE giving the best results in the present study; (2) LMDZt is most of the time too diffusive, as it simulates a too high boundary layer height; (3) CHIMERE reproduces better the observed gradients between the boundary layer and the free troposphere, but is sometimes too variable and gives rise to incoherent structures. We conclude there is a need for more vertical profiles to conduct further studies that will help to improve the parameterization of vertical transport in the models used for CO2 flux inversions. Furthermore, we use a modeling method to quantify CO2 fluxes at the regional scale from any observing point, coupling influence functions from the transport model LMDZt (that works quite well at the synoptic scale) with information on the space-time distribution of fluxes. This modeling method is compared to a dual tracer method (the so-called Radon method) for a case study on 25 May 2001 during which simultaneous well-correlated in-situ CO2 and Radon 222 measurements have been collected. Both methods give a similar flux within the Radon 222 method uncertainty (35%), that is an atmospheric CO2 sink of −4.2 to −4.4 gC m−2 day−1. We have estimated the uncertainty of the modeling method to be at least 33% when considering averages, even much more on individual events. This method allows the determination of the area that contributed to the CO2 observed concentration. In our case, the observation point located at 1700 m a.s.l. in the North of France, is influenced by an area of 1500×700 km2 that covers the Benelux region, part of Germany and western Poland. Furthermore, this method allows deconvolution between the different contributing fluxes. In this case study, the biospheric sink contributes for 73% of the total flux, fossil fuel emissions for 27%, the oceanic flux being negligeable. However, the uncertainties of the influence function method must be better assessed. This could be possible by applying it to other cases where the calculated fluxes can be checked independantly, for example at tall towers where simultaneous CO2 and Radon 222 measurements can be conducted. The use of optimized fluxes (from atmospheric inversions) and of mesoscale models for atmospheric transport may also significantly reduce the uncertainties.

Abstract. Our ability to predict future climate change relies on our understanding of current and future CO2 fluxes, particularly on a regional scale (100–1000 km). CO2 regional sources and sinks are still poorly understood. Inverse transport modeling, a method often used to quantify these fluxes, relies on atmospheric CO2 measurements. One of the main challenges for the transport models used in the inversions is to properly reproduce CO2 vertical gradients between the boundary layer and the free troposphere, as these gradients impact on the partitioning of the calculated fluxes between the different model regions. Vertical CO2 profiles are very well suited to assess the performances of the models. In this paper, we conduct a comparison between observed and modeled CO2 profiles recorded during two CAATER campaigns that occurred in May 2001 and October 2002 over Western Europe, as described in a companion paper. We test different combinations between a global transport model (LMDZt), a mesoscale transport model (CHIMERE), and different sets of biospheric fluxes, all chosen with a diurnal cycle (CASA, SiB2 and ORCHIDEE). The vertical profile comparison shows that: 1) in most cases the influence of the biospheric flux is small but sometimes not negligible, ORCHIDEE giving the best results in the present study; 2) LMDZt is most of the time too diffuse, as it simulates a too high boundary layer height; 3) CHIMERE better reproduces the observed gradients between the boundary layer and the free troposphere, but is sometimes too variable and gives rise to incoherent structures. We conclude there is a need for more vertical profiles to conduct further studies to improve the parameterization of vertical transport in the models used for CO2 flux inversions. Furthermore, we use a modeling method to quantify CO2 fluxes at the regional scale from a chosen observing point, coupling influence functions from the transport model LMDZt (that works quite well at the synoptic scale) with information on the space-time distribution of fluxes. This modeling method is compared to a dual tracer method (the so-called Radon method) for a case study on 25 May 2001 during which simultaneous well-correlated in situ CO2 and Radon 222 measurements have been collected. Both methods give a similar result: a flux within the Radon 222 method uncertainty (35%), that is an atmospheric CO2 sink of −4.2 to −4.4 gC m−2 day−1. We have estimated the uncertainty of the modeling method to be at least 33% on average, and even more for specific individual events. This method allows the determination of the area that contributed to the CO2 observed concentration. In our case, the observation point located at 1700 m a.s.l. in the north of France, is influenced by an area of 1500×700 km2 that covers the Benelux region, part of Germany and western Poland. Furthermore, this method allows deconvolution between the different contributing fluxes. In this case study, the biospheric sink contributes 73% of the total flux, fossil fuel emissions for 27%, the oceanic flux being negligible. However, the uncertainties of the influence function method need to be better assessed. This could be possible by applying it to other cases where the calculated fluxes can be checked independently, for example at tall towers where simultaneous CO2 and Radon 222 measurements can be conducted. The use of optimized fluxes (from atmospheric inversions) and of mesoscale models for atmospheric transport may also significantly reduce the uncertainties.

Abstract BACKGROUND Approx. 5% of melanoma pts develop LMDz. There are essentially no models of LMDz available for therapeutic development. Here we report, the in-vitro & in-vivo culturing of CSF-CTCs. METHODS CSF-CTCs were detected by the Veridex CellSearch® System. Cell-free DNA and cell-associated DNA were extracted, sequenced and profiled. Expanded ex-vivo CSF-CTCs were grown in-vitro and tested for drug sensitivity. CSF-CTCs were grown successfully in-vivo from 1 pt; labeled human Braf V600E WM164 cells were injected IT in as a control. RESULTS CSF-CTCs: 12 LMDz pts and 8 melanoma pts without LMDz were studied. All but 1 LMDz pts (92%) had CSF-CTCs (avg: 2148.6; range 23 - 3055 CTCs/ml). In contrast, 3/8 (37%) melanoma Brain Mets pts without LMDz had CSF-CTCs but fewer of them (avg: 0.31; range 0.13 - 0.6 CTCs/ml CSF). CSF-CTCs Profile: These had BrafV600E (83%), and GNAQ Q209P & NRAS Q61R in 1 pt each. Ex-vivoculture of CSF-CTCs and PDX model: After lengthy optimization of conditions we successfully expanded CSF-CTCs in vitro(~25% of pts), and in-vivo in immunodeficient mice from 1 pt (~10% of samples). Ceritinib, used as a FAK inhibitor, with MEKi was effective in-vitro (p=3.17e-6) and prolonged survival in-vivo in LMDz (median survival: >32 days vs control: 18 days; p=7.81e-5). CONCLUSIONS Though the sample size is small, this is the first report of the successful in-vitro & in-vivo culture of CSF-CTCs from pts with LMDz. Single cell analysis to determine how representative these models are and further in-vivo testing are in progress.

La forêt amazonienne joue un rôle essentiel en tant que régulateur du système climatique et principal puits de carbone terrestre. Il contrôle les processus hydroclimatiques et atténue les effets des sécheresses grâce au couplage végétation-atmosphère. En fait, les forêts amazoniennes peuvent potentiellement affecter les régimes de précipitations grâce à des processus biophysiques tels que le recyclage de l'eau. Cependant, ces capacités ont été réduites au cours des dernières décennies en raison des perturbations du système climat-végétation ainsi que de l'intensification des sécheresses. Cela a accentué un processus de transition biophysique d'un écosystème à prédominance forestière vers une savane. Par conséquent, compte tenu de ces complexités, il est extrêmement important de comprendre la direction des changements.À l'aide de plusieurs ensembles de données et du modèle couplé ORCHIDEE-LMDZ, cette thèse approfondit l'étude des interactions entre l'hydroclimatologie et la végétation amazonienne. En outre, il cherche à élargir notre compréhension des modifications du système végétation-atmosphère et de ses liens avec le climat et des changements du LULC. De même, en tenant compte des taux croissants de déforestation, il étudie les effets et les rétroactions résultant d'un scénario de perte forestière à grande échelle sur les processus hydrologiques.Les résultats montrent que, dans le sud-ouest de l'Amazonie, les forêts passant d'un état influencé par la disponibilité énergétique à un état dépendant de la disponibilité en eau tout au long de l'année. Pendant la saison des pluies, la croissance de la végétation est principalement influencée par la disponibilité en énergie plutôt que par la disponibilité en eau. Cependant, en dehors de cette période, les forêts réagissent positivement aux précipitations et au stockage terrestre de l'eau, ce qui suggère que la végétation dépend principalement de l'approvisionnement hydrique. Toutefois, une analyse spatiale révèle que la déforestation récente modifie ces transitions et déstabilise l'équilibre naturel du système climat-végétation.La nature de ces déséquilibres en Amazonie n'est pas complètement claire. En examinant les liens entre les flux d'eau/énergie et les conditions de végétation, nous explorons si ces changements sont inhérents au climat ou résultent de processus anthropiques. 67% du sud-ouest a connu une transition vers un état majoritairement sec en raison du climat (forçage externe), tandis que 21% a connu une transition vers un état dominé par la déforestation (forçage interne). Cependant, les moteurs externes et internes entraînent simultanément des changements. En quantifiant les forçages, nous montrons que les synergies ont amené 74% du sud-ouest de l'Amazonie à un état de stress hydrique élevé. Or, ces dernières années, 30% des changements sont strictement dominés par des forçages internes. Cela suggère que les processus internes jouent un rôle croissant dans la transition vers des états caractérisés par un stress hydrique forestier élevé, particulièrement là où la déforestation et la pression anthropique augmentent.À l'aide du modèle couplé ORCHIDEE-LMDZ, les effets de la déforestation projetée de l'Amazonie d'ici 2050 sur le cycle de l'eau et la sécheresse sont examinés. La déforestation diminue les précipitations, réduit l'évapotranspiration et augmente le ruissellement. De plus, elle accentue le stress hydrique, notamment dans le sud-ouest de l'Amazonie (retour positif). La demande en eau dans l'atmosphère, à la surface et même dans la zone racinaire du sol s'intensifie pendant la saison sèche. Pendant la saison des pluies, le déficit d'humidité atmosphérique devient encore plus aigu vers les Andes tropicales, sur la région de l'Altiplano. Ces résultats permettent de mieux comprendre les effets possibles du déboisement massif sur la disponibilité en eau et la résilience de l'Amazonie dans un contexte où les changements se produisent à un rythme accéléré
The Amazon rainforest plays a vital role by functioning as a regulator of the climate system and as the main terrestrial carbon sink. It drives hydroclimatic processes and mitigates the effects of droughts through vegetation-atmosphere coupling. Indeed, Amazon forests have the potential to impact rainfall patterns through biophysical processes like water recycling. However, these capacities have been reduced during the last decades due to disturbances in the climate-vegetation system together with the intensification of droughts. All this has accentuated a process of biophysical transition from a predominantly forested ecosystem to a Savanna. Therefore, given these complexities, understanding the direction of changes is of vital importance.Using multiple datasets and the coupled ORCHIDEE and LMDZ models, this thesis delves into the study of the interactions between Amazon hydroclimatology and vegetation. In addition, it seeks to expand our understanding of modifications in the vegetation-atmosphere system and its links with climate and LULC changes. Likewise, taking into account the increasing rates of deforestation, it investigates the effects and feedback resulting from a large-scale forest loss scenario on hydrological processes.The results show that, over the southwestern Amazon, forests undergo a transition from being influenced by energy availability to depending on water availability throughout the year. During the rainy season, vegetation growth is primarily influenced by energy availability rather than water availability. Nevertheless, outside of this period, forests respond positively to precipitation and terrestrial water storage, suggesting that vegetation is primarily dependent on water supply. However, a spatial analysis reveals that recent deforestation modifies these transitions and destabilizes the natural balance in the climate-vegetation system.The nature of these imbalances in the Amazon is not entirely clarified. Through an approach based on the relationships of water/energy fluxes and vegetation conditions over the last four decades, it is explored whether these changes are intrinsic to climate variability or are driven by anthropogenic processes. 67% of the southwestern Amazon has experienced a transition towards a predominantly dry state due to climatic factors (external forcing), while 21% has transitioned towards a state dominated by deforestation (internal forcing). However, external and internal forcings are not independent processes, as both mechanisms drive changes simultaneously. By weighing the magnitudes of these forcings, we show that the synergies have led 74% of the southwestern Amazon toward a state of greater water stress. Nevertheless, during recent years, although combined external-internal processes continue to exert significant control over changes, 30% of these are strictly dominated by internal forcing. This suggests that internal processes are playing an increasingly relevant role in the transition towards a state characterized by high forest water stress, especially in areas where deforestation and anthropogenic pressure are increasing.Using the coupled ORCHIDEE and LMDZ models, the effects of projected Amazon deforestation by 2050 on the hydrological cycle and dryness are examined. Deforestation decreases precipitation, reduces evapotranspiration and increases runoff. Furthermore, deforestation accentuates water stress especially in the southwestern Amazon (positive feedback). Water demands in the atmosphere, on the land surface and even in the soil root zone intensify during the dry season. During the wet season, the deficit of specific atmospheric humidity becomes even more acute towards the tropical Andes over the Altiplano region. These findings provide a more thorough understanding of the possible effects of massive forest removal on the water availability and resilience of the Amazon in a context where changes are occurring at an accelerated rate

Ce travail traite de la simulation numérique du climat des grandes calottes de glace, en particulier des calottes de l'Antarctique et du Groenland, toujours existantes, dans des conditions climatiques différentes, à l'aide de modèles de circulation générale de l'atmosphère (MCGA). Le MCGA à grille variable LMDz a été adapté aux spécificités du climat polaire et validé pour le climat actuel. L'approche d'une grille variable, qui permet d'utiliser le MCGA à haute résolution spatiale (autour de 100 km) sur la région d'intérêt à un coût numérique raisonnable, a été validée en analysant la dynamique atmosphérique au bord de la région ciblée à l'aide d'un schéma de suivi des cyclones individuels. Des simulations du climat du Dernier Maximum Glaciaire (DMG) ont été faites pour le Groenland et l'Antarctique et analysées en tenant compte des archives glaciaires disponibles. Une explication possible des différences entre les deux méthodes principales de reconstruction des paléotempératures - l'analyse des isotopes de l'eau et la mesure directe de la température de la glace dans le trou de forage - au centre du Groenland a pu être proposée. Cette explication est basée sur des changements de paramètres climatiques locaux. C'est la première fois que l'approche de grille variable a été utilisée dans un MCGA pour des simulations du climat polaire à l'échelle de quelques années. Les simulations paléoclimatiques faites avec LMDz sont à une résolution spatiale inégalée à ce jour. Finalement, le climat du DMG, simulé par plusieurs MCGA dans le cadre du projet international PMIP (Paleoclimate Modelling Intercomparison Programme), a été analysé, et des implications des résultats pour l'interprétation des enregistrements glaciaires ont été discutées.