44 research outputs found

    Causes, impacts et projections des sécheresses en Amazonie : Une étude numérique des processus et des incertitudes

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    L'augmentation probable de la fréquence des sécheresses au cours du 21ème siècle, en réponse au réchauffement climatique, pourrait faire basculer la forêt amazonienne d'un puits à une source de carbone, déclenchant ainsi une rétroaction positive sur l'accroissement de l'effet de serre. La sensibilité des cycles de l'eau et du carbone aux sécheresses représente donc un point critique dans la stratégie d'évaluation des modèles de climat et pour la crédibilité des scénarios climatiques. Cette thèse vise à évaluer la représentation et la réponse aux sécheresses des cycles de l'eau et du carbone en Amazonie par le modèle de surface ISBA-CC mis en oeuvre dans le modèle de climat du CNRM. Pour ce faire, nous avons utilisé, outre des mesures écophysiologiques, des mesures de tours de flux ainsi que deux expériences d'assèchement artificiel. La version originale du modèle n'étant pas satisfaisante, la paramétrisation des processus métaboliques et la sensibilité de la végétation au stress hydrique ont été modifiées, puis validées, sur ces sites, mais également à l'échelle du bassin en utilisant notamment des données de débits, des reconstructions d'évapotranspiration et d'assimilation de carbone, ainsi que des observations spatiales de variations de stocks d'eau et de fluorescence chlorophyllienne. Une analyse succincte des changements climatiques régionaux a été réalisée sur la base des modèles CMIP5, mettant en évidence un certain consensus à l'allongement et au renforcement de la saison sèche au cours du 21ème siècle. Ces scénarios, après calibration des sorties de quelques modèles, nous ont ensuite permis de tester en mode off-line la sensibilité des projections du cycle de l'eau et du carbone aux modifications apportées au modèle ISBA-CC. Les résultats montrent sans surprise l'influence prépondérante du choix du modèle forceur dans ce type de simulation, mais révèle également l'importance des paramétrisations liées à la végétation. ABSTRACT : The likely increase in drought frequency as a result of climate change, might switch the Amazon forest from being a sink to a source of carbon, setting off a positive feedback on the increasing greenhouse effect. Hence, the drought sensitivity of the water and carbon cycles in the Amazon is a crucial point in the evaluation of climate models.In this PhD thesis, we evaluate in off-line mode, how the CNRM land surface model ISBACC, represents the water and carbon cycles and their response to drought in the Amazon. For this purpose, we used published ecophysiological data together with five Amazonian flux tower sitesand two artificial drought experiments. Since the standard version of the model was not satisfactory, we modified the parameterizations of the metabolic processes and the sensitivity of vegetation to water stress. We evaluated this new version against the flux tower and artificial drought sites, but also at regional scale using river discharge data, reconstructed evapotranspiration and carbon assimilation fluxes, and remotely sensed total water storage variations and chlorophyll fluorescence data. A brief analysis of the regional climate changes projected by CMIP5 models showed a relative consensus for longer and more intense dry seasons during the 21st century. Two of these climate scenarios were calibrated and used to test the sensitivity of the water and carbon cycle projections to our modifications of the ISBACC model in off-line mode. As expected, the results reveam the importance of the driving climate model, but also highlight the role of the vegetation parameterizations

    Forest fluxes and mortality response to drought: model description (ORCHIDEE-CAN-NHA r7236) and evaluation at the Caxiuanã drought experiment

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    Extreme drought events in Amazon forests are expected to become more frequent and more intense with climate change, threatening ecosystem function and carbon balance. Yet large uncertainties exist on the resilience of this ecosystem to drought. A better quantification of tree hydraulics and mortality processes is needed to anticipate future drought effects on Amazon forests. Most state-of-the-art dynamic global vegetation models are relatively poor in their mechanistic description of these complex processes. Here, we implement a mechanistic plant hydraulic module within the ORCHIDEE-CAN-NHA r7236 land surface model to simulate the percentage loss of conductance (PLC) and changes in water storage among organs via a representation of the water potentials and vertical water flows along the continuum from soil to roots, stems and leaves. The model was evaluated against observed seasonal variability in stand-scale sap flow, soil moisture and productivity under both control and drought setups at the Caxiuanã throughfall exclusion field experiment in eastern Amazonia between 2001 and 2008. A relationship between PLC and tree mortality is built in the model from two empirical parameters, the cumulated duration of drought exposure that triggers mortality, and the mortality fraction in each day exceeding the exposure. Our model captures the large biomass drop in the year 2005 observed 4 years after throughfall reduction, and produces comparable annual tree mortality rates with observation over the study period. Our hydraulic architecture module provides promising avenues for future research in assimilating experimental data to parameterize mortality due to drought-induced xylem dysfunction. We also highlight that species-based (isohydric or anisohydric) hydraulic traits should be further tested to generalize the model performance in predicting the drought risks.</p

    Climatic and biotic factors influencing regional declines and recovery of tropical forest biomass from the 2015/16 El Niño

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    International audienceThe 2015/16 El Niño brought severe drought and record-breaking temperatures in the tropics. Here, using satellite-based L-band microwave vegetation optical depth, we mapped changes of above-ground biomass (AGB) during the drought and in subsequent years up to 2019. Over more than 60% of drought-affected intact forests, AGB reduced during the drought, except in the wettest part of the central Amazon, where it declined 1 y later. By the end of 2019, only 40% of AGB reduced intact forests had fully recovered to the predrought level. Using random-forest models, we found that the magnitude of AGB losses during the drought was mainly associated with regionally distinct patterns of soil water deficits and soil clay content. For the AGB recovery, we found strong influences of AGB losses during the drought and of γ . γ is a parameter related to canopy structure and is defined as the ratio of two relative height (RH) metrics of Geoscience Laser Altimeter System (GLAS) waveform data—RH25 (25% energy return height) and RH100 (100% energy return height; i.e., top canopy height). A high γ may reflect forests with a tall understory, thick and closed canopy, and/or without degradation. Such forests with a high γ ( γ ≥ 0.3) appear to have a stronger capacity to recover than low- γ ones. Our results highlight the importance of forest structure when predicting the consequences of future drought stress in the tropics

    Temperature extremes of 2022 reduced carbon uptake by forests in Europe

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    The year 2022 saw record breaking temperatures in Europe during both summer and fall. Similar to the recent 2018 drought, close to 30% (3.0 million km2) of the European continent was under severe summer drought. In 2022, the drought was located in central and southeastern Europe, contrasting the Northern-centered 2018 drought. We show, using multiple sets of observations, a reduction of net biospheric carbon uptake in summer (56-62 TgC) over the drought area. Specific sites in France even showed a widespread summertime carbon release by forests, additional to wildfires. Partial compensation (32%) for the decreased carbon uptake due to drought was offered by a warm autumn with prolonged biospheric carbon uptake. The severity of this second drought event in 5 years suggests drought-induced reduced carbon uptake to no longer be exceptional, and important to factor into Europe’s developing plans for net-zero greenhouse gas emissions that rely on carbon uptake by forests

    Are Terrestrial Biosphere Models Fit for Simulating the Global Land Carbon Sink?

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    The Global Carbon Project estimates that the terrestrial biosphere has absorbed about one-third of anthropogenic CO2_2 emissions during the 1959–2019 period. This sink-estimate is produced by an ensemble of terrestrial biosphere models and is consistent with the land uptake inferred from the residual of emissions and ocean uptake. The purpose of our study is to understand how well terrestrial biosphere models reproduce the processes that drive the terrestrial carbon sink. One challenge is to decide what level of agreement between model output and observation-based reference data is adequate considering that reference data are prone to uncertainties. To define such a level of agreement, we compute benchmark scores that quantify the similarity between independently derived reference data sets using multiple statistical metrics. Models are considered to perform well if their model scores reach benchmark scores. Our results show that reference data can differ considerably, causing benchmark scores to be low. Model scores are often of similar magnitude as benchmark scores, implying that model performance is reasonable given how different reference data are. While model performance is encouraging, ample potential for improvements remains, including a reduction in a positive leaf area index bias, improved representations of processes that govern soil organic carbon in high latitudes, and an assessment of causes that drive the inter-model spread of gross primary productivity in boreal regions and humid tropics. The success of future model development will increasingly depend on our capacity to reduce and account for observational uncertainties

    ORCHIDEE-MICT (revision 4126), a land surface model for the high-latitudes: model description and validation

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    Abstract. 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 CO2 fluxes, in addition to a recently-developed fire module. Outputs from ORCHIDEE-MICT, when forced by two climate input data sets, 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) CO2 flux and carbon stock observations. The model performance is good with respect to empirical data, despite a simulated excessive plant water stress and 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. </jats:p

    Temperature extremes of 2022 reduced carbon uptake by forests in Europe

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    The year 2022 saw record breaking temperatures in Europe during both summer and fall. Close to 30% of the European continent was under severe summer drought with a similarly large area affected (3.0 million km2) as during the recent 2018 drought, but now located in central and southeastern Europe. Multiple sets of observations suggest a reduction of net ecosystem carbon exchange in summer (57-62 TgC) over this area, and specific sites in France even showed a widespread summertime carbon release by forests, as well as wildfires. A warm fall with prolonged carbon uptake offered only partial compensation (up to 32%) for the carbon uptake lost due to drought. This severity of this second drought event in 5 years suggests these impacts to no longer be exceptional, and important to factor into Europe's developing plans for net-zero greenhouse gas emissions that rely on carbon sequestration by forests

    Carbon-concentration and carbon-climate feedbacks in CMIP6 models, and their comparison to CMIP5 models

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    Abstract. Results from the fully-, biogeochemically-, and radiatively-coupled simulations in which CO2 increases at a rate of 1 % per year (1pctCO2) from its pre-industrial value are analyzed to quantify the magnitude of two feedback parameters which characterize the coupled carbon-climate system. These feedback parameters quantify the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate. The results are based on eight comprehensive Earth system models from the fifth Coupled Model Intercomparison Project (CMIP5) and eleven models from the sixth CMIP (CMIP6). The comparison of model results from two CMIP phases shows that, for both land and ocean, the model mean values of the feedback parameters and their multi-model spread has not changed significantly across the two CMIP phases. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The sensitivity of feedback parameters to the three different ways in which they may be calculated is shown and, consistent with existing studies, the most relevant definition is that calculated using results from the fully- and biogeochemically-coupled configurations. Based on these two simulations simplified expressions for the feedback parameters are obtained when the small temperature change in the biogeochemically-coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters allows identification of the reasons for differing responses among ocean and land carbon cycle models. </jats:p
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