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1
Delire, Christine, Nathalie de Noblet-Ducoudré, Adriana Sima, and Isabelle Gouirand. "Vegetation Dynamics Enhancing Long-Term Climate Variability Confirmed by Two Models." Journal of Climate 24, no. 9 (May 1, 2011): 2238–57. http://dx.doi.org/10.1175/2010jcli3664.1.
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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.
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Bacour, Cédric, Natasha MacBean, Frédéric Chevallier, Sébastien Léonard, Ernest N. Koffi, and Philippe Peylin. "Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model." Biogeosciences 20, no. 6 (March 23, 2023): 1089–111. http://dx.doi.org/10.5194/bg-20-1089-2023.
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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.
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Ryder, J., J. Polcher, P. Peylin, C. Ottlé, Y. Chen, E. van Gorsel, V. Haverd, et al. "A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations." Geoscientific Model Development 9, no. 1 (January 25, 2016): 223–45. http://dx.doi.org/10.5194/gmd-9-223-2016.
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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.
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Ryder, J., J. Polcher, P. Peylin, C. Ottlé, Y. Chen, E. van Gorsel, V. Haverd, et al. "A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations." Geoscientific Model Development Discussions 7, no. 6 (December 8, 2014): 8649–701. http://dx.doi.org/10.5194/gmdd-7-8649-2014.
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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.
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Peylin, Philippe, Cédric Bacour, Natasha MacBean, Sébastien Leonard, Peter Rayner, Sylvain Kuppel, Ernest Koffi, et al. "A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle." Geoscientific Model Development 9, no. 9 (September 20, 2016): 3321–46. http://dx.doi.org/10.5194/gmd-9-3321-2016.
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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.
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Jost, A., S. Fauquette, M. Kageyama, G. Krinner, G. Ramstein, J. P. Suc, and S. Violette. "High resolution climate and vegetation simulations of the Late Pliocene, a model-data comparison over western Europe and the Mediterranean region." Climate of the Past 5, no. 4 (October 12, 2009): 585–606. http://dx.doi.org/10.5194/cp-5-585-2009.
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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.
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Jost, A., S. Fauquette, M. Kageyama, G. Krinner, G. Ramstein, J. P. Suc, and S. Violette. "High resolution climate and vegetation simulations of the Mid-Pliocene, a model-data comparison over western Europe and the Mediterranean region." Climate of the Past Discussions 5, no. 3 (May 13, 2009): 1367–414. http://dx.doi.org/10.5194/cpd-5-1367-2009.
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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.
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Xueref-Remy, I., P. Bousquet, C. Carouge, L. Rivier, N. Viovy, and P. Ciais. "Variability and budget of CO<sub>2</sub> in Europe: analysis of the CAATER airborne campaigns – Part 2: Comparison of CO<sub>2</sub> vertical variability and fluxes from observations and a modeling framework." Atmospheric Chemistry and Physics Discussions 10, no. 2 (February 12, 2010): 4271–304. http://dx.doi.org/10.5194/acpd-10-4271-2010.
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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.
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Xueref-Remy, I., P. Bousquet, C. Carouge, L. Rivier, and P. Ciais. "Variability and budget of CO<sub>2</sub> in Europe: analysis of the CAATER airborne campaigns – Part 2: Comparison of CO<sub>2</sub> vertical variability and fluxes between observations and a modeling framework." Atmospheric Chemistry and Physics 11, no. 12 (June 20, 2011): 5673–84. http://dx.doi.org/10.5194/acp-11-5673-2011.
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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.
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Law, Vincent, Brittany Evernden, John Puskas, Gisela Caceres, Elena Ryzhova, Inna Smalley, Nam Tran, et al. "CMET-26. IN-VITRO & IN-VIVO CULTURE OF PATIENT (PT) DERIVED CSF-CTCS IN LEPTOMENINGEAL DISEASE (LMDZ) FROM MELANOMA TO IDENTIFY NOVEL TREATMENT STRATEGIES." Neuro-Oncology 21, Supplement_6 (November 2019): vi57. http://dx.doi.org/10.1093/neuonc/noz175.227.
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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.
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Law, Vincent, Brittany Evernden, Rajappa Kenchappa, John Puskas, Gisela Caceres, Elena Ryzhova, Inna Smalley, et al. "LPTO-03. IN-VITRO & IN-VIVO CULTURE OF PATIENT (PT) DERIVED CSF-CTCs IN LEPTOMENINGEAL DISEASE (LMDz) FROM MELANOMA TO IDENTIFY NOVEL TREATMENT STRATEGIES." Neuro-Oncology Advances 1, Supplement_1 (August 2019): i6—i7. http://dx.doi.org/10.1093/noajnl/vdz014.026.
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Abstract BACKGROUND: Approximately 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: 2148.60; 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-vivo culture 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.
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Messina, Palmira, Juliette Lathière, Katerina Sindelarova, Nicolas Vuichard, Claire Granier, Josefine Ghattas, Anne Cozic, and Didier A. Hauglustaine. "Global biogenic volatile organic compound emissions in the ORCHIDEE and MEGAN models and sensitivity to key parameters." Atmospheric Chemistry and Physics 16, no. 22 (November 16, 2016): 14169–202. http://dx.doi.org/10.5194/acp-16-14169-2016.
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Abstract. A new version of the biogenic volatile organic compounds (BVOCs) emission scheme has been developed in the global vegetation model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic EcosystEm), which includes an extended list of biogenic emitted compounds, updated emission factors (EFs), a dependency on light for almost all compounds and a multi-layer radiation scheme. Over the 2000–2009 period, using this model, we estimate mean global emissions of 465 Tg C yr−1 for isoprene, 107.5 Tg C yr−1 for monoterpenes, 38 Tg C yr−1 for methanol, 25 Tg C yr−1 for acetone and 24 Tg C yr−1 for sesquiterpenes. The model results are compared to state-of-the-art emission budgets, showing that the ORCHIDEE emissions are within the range of published estimates. ORCHIDEE BVOC emissions are compared to the estimates of the Model of Emissions of Gases and Aerosols from Nature (MEGAN), which is largely used throughout the biogenic emissions and atmospheric chemistry community. Our results show that global emission budgets of the two models are, in general, in good agreement. ORCHIDEE emissions are 8 % higher for isoprene, 8 % lower for methanol, 17 % higher for acetone, 18 % higher for monoterpenes and 39 % higher for sesquiterpenes, compared to the MEGAN estimates. At the regional scale, the largest differences between ORCHIDEE and MEGAN are highlighted for isoprene in northern temperate regions, where ORCHIDEE emissions are higher by 21 Tg C yr−1, and for monoterpenes, where they are higher by 4.4 and 10.2 Tg C yr−1 in northern and southern tropical regions compared to MEGAN. The geographical differences between the two models are mainly associated with different EF and plant functional type (PFT) distributions, while differences in the seasonal cycle are mostly driven by differences in the leaf area index (LAI). Sensitivity tests are carried out for both models to explore the response to key variables or parameters such as LAI and light-dependent fraction (LDF). The ORCHIDEE and MEGAN emissions are differently affected by LAI changes, with a response highly depending on the compound considered. Scaling the LAI by a factor of 0.5 and 1.5 changes the isoprene global emission by −21 and +8 % for ORCHIDEE and −15 and +7 % for MEGAN, and affects the global emissions of monoterpenes by −43 and +40 % for ORCHIDEE and −11 and +3 % for MEGAN. Performing a further sensitivity test, forcing ORCHIDEE with the MODIS LAI, confirms the high sensitivity of the ORCHIDEE emission module to LAI variation. We find that MEGAN is more sensitive to variation in the LDF parameter than ORCHIDEE. Our results highlight the importance and the need to further explore the BVOC emission estimate variability and the potential for using models to investigate the estimated uncertainties.
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Messina, P., J. Lathière, K. Sindelarova, N. Vuichard, C. Granier, J. Ghattas, A. Cozic, and D. A. Hauglustaine. "Global biogenic volatile organic compound emissions in the ORCHIDEE and MEGAN models and sensitivity to key parameters." Atmospheric Chemistry and Physics Discussions 15, no. 23 (December 2, 2015): 33967–4033. http://dx.doi.org/10.5194/acpd-15-33967-2015.
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Abstract. A new version of the BVOC emission scheme has been developed in the global vegetation model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic EcosystEm), including an extended list of biogenic emitted compounds, updated emission factors (EFs), a dependency on light for almost all compounds and a multi-layer radiation scheme. For the 2000–2009 period, we estimate with this model, mean global emissions of 465 Tg C yr-1 for isoprene, 107.5 Tg C yr-1 for monoterpenes, 38 Tg C yr-1 for methanol, 25 Tg C yr-1 for acetone and 24 Tg C yr-1 for sesquiterpenes. The model results are compared to state-of-the-art emission budgets, showing that the ORCHIDEE emissions are within the range of published estimates. ORCHIDEE BVOC emissions are compared to the estimates of the Model of Emissions of Gases and Aerosols from Nature (MEGAN), largely used throughout the biogenic emissions and atmospheric chemistry community. Our results show that global emission budgets are, in general, in good agreement between the two models. ORCHIDEE emissions are 8 % higher for isoprene, 8 % lower for methanol, 17 % higher for acetone, 18 % higher for monoterpenes and 39 % higher for sesquiterpenes compared to MEGAN estimates. At the regional scale, the largest differences between ORCHIDEE and MEGAN are highlighted for isoprene in northern temperate regions, with the ORCHIDEE emissions being higher by 21 Tg C yr-1, and for monoterpenes being higher by 10 and 18 Tg C yr-1 in northern and southern tropical regions compared to MEGAN. The geographical differences, between the two models, are mainly associated with different EF and PFT distribution, while differences in the seasonal cycle are mostly driven by differences in the Leaf Area Index (LAI). Sensitivity tests are carried out for both models to explore the response to key variables or parameters such as LAI and Light Dependent Fraction (LDF). The ORCHIDEE and MEGAN emissions are differently affected by LAI changes, with a response highly sensitive to the considered compound. When the LAI is scaled by a factor of 0.5 (1.5), the global emission change is −21 % (+8 %) for ORCHIDEE and −15 % (+7 %) for MEGAN regarding isoprene, and is −43 % (+40 %) for ORCHIDEE and −11 % (+3 %) for MEGAN regarding monoterpenes. We find that MEGAN is more sensitive to variation of LDF parameter than ORCHIDEE. Our results highlight the importance and the need to further explore the BVOC emission estimate variability and the interest of using models to investigate the estimate uncertainties.
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Cámara, Alvaro de la, François Lott, Valérian Jewtoukoff, Riwal Plougonven, and Albert Hertzog. "On the Gravity Wave Forcing during the Southern Stratospheric Final Warming in LMDZ." Journal of the Atmospheric Sciences 73, no. 8 (July 26, 2016): 3213–26. http://dx.doi.org/10.1175/jas-d-15-0377.1.
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Abstract The austral stratospheric final warming date is often predicted with substantial delay in several climate models. This systematic error is generally attributed to insufficient parameterized gravity wave (GW) drag in the stratosphere around 60°S. A simulation with a general circulation model [Laboratoire de Météorologie Dynamique zoom model (LMDZ)] with a much less pronounced bias is used to analyze the contribution of the different types of waves to the dynamics of the final warming. For this purpose, the resolved and unresolved wave forcing of the middle atmosphere during the austral spring are examined in LMDZ and reanalysis data, and a good agreement is found between the two datasets. The role of parameterized orographic and nonorographic GWs in LMDZ is further examined, and it is found that orographic and nonorographic GWs contribute evenly to the GW forcing in the stratosphere, unlike in other climate models, where orographic GWs are the main contributor. This result is shown to be in good agreement with GW-resolving operational analysis products. It is demonstrated that the significant contribution of the nonorographic GWs is due to highly intermittent momentum fluxes produced by the source-related parameterizations used in LMDZ, in qualitative agreement with recent observations. This yields sporadic high-amplitude GWs that break in the stratosphere and force the circulation at lower altitudes than more homogeneously distributed nonorographic GW parameterizations do.
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Gryazin, V., C. Risi, J. Jouzel, N. Kurita, J. Worden, C. Frankenberg, V. Bastrikov, K. Gribanov, and O. Stukova. "The added value of water isotopic measurements for understanding model biases in simulating the water cycle over Western Siberia." Atmospheric Chemistry and Physics Discussions 14, no. 4 (February 20, 2014): 4457–503. http://dx.doi.org/10.5194/acpd-14-4457-2014.
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Abstract. We evaluate the isotopic composition of water vapor and precipitation simulated by the LMDZ GCM over Siberia using several datasets: TES and GOSAT satellite observations of tropospheric water vapor, GNIP and SNIP precipitation networks, and daily, in-situ measurements of water vapor and precipitation at the Kourovka site in Western Siberia. We use δD vs. humidity diagrams to explore the complementarity of these two variables to interpret model biases in terms of the representation of processes. LMDZ captures the spatial, seasonal and daily variations reasonably well. It systematically overestimates δD in the vapor and precipitation, a bias that is most likely associated with a misrepresentation of air mass origin. The performance of LMDZ is put in the context of other isotopic models from the SWING2 models. There is significant spread among models in the simulation of δD, and of the δD vs. humidity relationship. This confirms that δD brings additional information compared to humidity only. We specifically investigate the added value of water isotopic measurements to interpret the warm and dry bias feature by most GCMs over mid and high latitude continents in summer. LMDZ simulates the strongest dry bias on days when it simulates the strongest enriched bias in δD. The analysis of the slopes in δD vs. humidity diagrams and of processes controlling δD and humidity variations suggests that the cause of the moist bias could be either a problem in the large-scale advection transporting too much dry and warm air from the south, or insufficient surface evaporation.
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Lafont, S., Y. Zhao, J. C. Calvet, P. Peylin, P. Ciais, F. Maignan, and M. Weiss. "Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE." Biogeosciences Discussions 8, no. 4 (July 22, 2011): 7399–439. http://dx.doi.org/10.5194/bgd-8-7399-2011.
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Abstract. The Leaf Area Index (LAI) is a measure of the amount of photosynthetic leaves and governs the canopy conductance to water vapor and carbon dioxide. Four different estimates of LAI were compared over France: two LAI products derived from satellite remote sensing, and two LAI simulations derived from land surface modelling. The simulated LAI was produced by the ISBA-A-gs model and by the ORCHIDEE model (developed by CNRM-GAME and by IPSL, respectively), for the 1994–2007 period. The two models were driven by the same atmospheric variables and used the same land cover map (SAFRAN and ECOCLIMAP-II, respectively). The MODIS and CYCLOPES satellite LAI products were used. Both products were available from 2000 to 2007 and this relatively long period allowed to investigate the interannual and the seasonal variability of monthly LAI values. In particular the impact of the 2003 and 2005 droughts were analyzed. The two models presented contrasting results, with a difference of one month between the average leaf onset dates simulated by the two models, and a maximum interannual variability of LAI simulated at springtime by ORCHIDEE and at summertime by ISBA-A-gs. The comparison with the satellite LAI products showed that, in general, the seasonality was better represented by ORCHIDEE, while ISBA-A-gs tended to better represent the interannual variability, especially for grasslands. While the two models presented comparable values of net carbon fluxes, ORCHIDEE simulated much higher photosynthesis rates than ISBA-A-gs (+70 %), while providing lower transpiration estimates (−8 %).
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Lafont, S., Y. Zhao, J. C. Calvet, P. Peylin, P. Ciais, F. Maignan, and M. Weiss. "Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE." Biogeosciences 9, no. 1 (January 25, 2012): 439–56. http://dx.doi.org/10.5194/bg-9-439-2012.
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Abstract. The Leaf Area Index (LAI) is a measure of the amount of photosynthetic leaves and governs the canopy conductance to water vapor and carbon dioxide. Four different estimates of LAI were compared over France: two LAI products derived from satellite remote sensing, and two LAI simulations derived from land surface modelling. The simulated LAI was produced by the ISBA-A-gs model and by the ORCHIDEE model (developed by CNRM-GAME and by IPSL, respectively), for the 1994–2007 period. The two models were driven by the same atmospheric variables and used the same land cover map (SAFRAN and ECOCLIMAP-II, respectively). The MODIS and CYCLOPES satellite LAI products were used. Both products were available from 2000 to 2007 and this relatively long period allowed to investigate the interannual and the seasonal variability of monthly LAI values. In particular the impact of the 2003 and 2005 droughts were analyzed. The two models presented contrasting results, with a difference of one month between the average leaf onset dates simulated by the two models, and a maximum interannual variability of LAI simulated at springtime by ORCHIDEE and at summertime by ISBA-A-gs. The comparison with the satellite LAI products showed that, in general, the seasonality was better represented by ORCHIDEE, while ISBA-A-gs tended to better represent the interannual variability, especially for grasslands. While the two models presented comparable values of net carbon fluxes, ORCHIDEE simulated much higher photosynthesis rates than ISBA-A-gs (+70%), while providing lower transpiration estimates (−8%).
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Valade, A., P. Ciais, N. Vuichard, N. Viovy, A. Caubel, N. Huth, F. Marin, and J. F. Martiné. "Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values." Geoscientific Model Development 7, no. 3 (June 30, 2014): 1225–45. http://dx.doi.org/10.5194/gmd-7-1225-2014.
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Abstract. Agro-land surface models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil–vegetation–atmosphere continuum. When developing agro-LSM models, particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugarcane biomass production with the agro-LSM ORCHIDEE–STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE–STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte Carlo sampling method associated with the calculation of partial ranked correlation coefficients is used to quantify the sensitivity of harvested biomass to input parameters on a continental scale across the large regions of intensive sugarcane cultivation in Australia and Brazil. The ten parameters driving most of the uncertainty in the ORCHIDEE–STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting different climate-mediated sensitivities of modeled sugarcane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.
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Valade, A., P. Ciais, N. Vuichard, N. Viovy, N. Huth, F. Marin, and J. F. Martiné. "Modeling sugar cane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values." Geoscientific Model Development Discussions 7, no. 1 (January 31, 2014): 1197–244. http://dx.doi.org/10.5194/gmdd-7-1197-2014.
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Abstract. Agro-Land Surface Models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, a particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of Agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS' phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte-Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used to quantify the sensitivity of harvested biomass to input parameters on a continental scale across the large regions of intensive sugar cane cultivation in Australia and Brazil. Ten parameters driving most of the uncertainty in the ORCHIDEE-STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting climate-mediated different sensitivities of modeled sugar cane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.
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Ringeval, B., P. O. Hopcroft, P. J. Valdes, P. Ciais, G. Ramstein, A. J. Dolman, and M. Kageyama. "Response of methane emissions from wetlands to the Last Glacial Maximum and an idealized Dansgaard–Oeschger climate event: insights from two models of different complexity." Climate of the Past 9, no. 1 (January 23, 2013): 149–71. http://dx.doi.org/10.5194/cp-9-149-2013.
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Abstract. The role of different sources and sinks of CH4 in changes in atmospheric methane ([CH4]) concentration during the last 100 000 yr is still not fully understood. In particular, the magnitude of the change in wetland CH4 emissions at the Last Glacial Maximum (LGM) relative to the pre-industrial period (PI), as well as during abrupt climatic warming or Dansgaard–Oeschger (D–O) events of the last glacial period, is largely unconstrained. In the present study, we aim to understand the uncertainties related to the parameterization of the wetland CH4 emission models relevant to these time periods by using two wetland models of different complexity (SDGVM and ORCHIDEE). These models have been forced by identical climate fields from low-resolution coupled atmosphere–ocean general circulation model (FAMOUS) simulations of these time periods. Both emission models simulate a large decrease in emissions during LGM in comparison to PI consistent with ice core observations and previous modelling studies. The global reduction is much larger in ORCHIDEE than in SDGVM (respectively −67 and −46%), and whilst the differences can be partially explained by different model sensitivities to temperature, the major reason for spatial differences between the models is the inclusion of freezing of soil water in ORCHIDEE and the resultant impact on methanogenesis substrate availability in boreal regions. Besides, a sensitivity test performed with ORCHIDEE in which the methanogenesis substrate sensitivity to the precipitations is modified to be more realistic gives a LGM reduction of −36%. The range of the global LGM decrease is still prone to uncertainty, and here we underline its sensitivity to different process parameterizations. Over the course of an idealized D–O warming, the magnitude of the change in wetland CH4 emissions simulated by the two models at global scale is very similar at around 15 Tg yr−1, but this is only around 25% of the ice-core measured changes in [CH4]. The two models do show regional differences in emission sensitivity to climate with much larger magnitudes of northern and southern tropical anomalies in ORCHIDEE. However, the simulated northern and southern tropical anomalies partially compensate each other in both models limiting the net flux change. Future work may need to consider the inclusion of more detailed wetland processes (e.g. linked to permafrost or tropical floodplains), other non-wetland CH4 sources or different patterns of D–O climate change in order to be able to reconcile emission estimates with the ice-core data for rapid CH4 events.
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Ringeval, B., P. O. Hopcroft, P. J. Valdes, P. Ciais, G. Ramstein, A. J. Dolman, and M. Kageyama. "Response of methane emissions from wetlands to the Last Glacial Maximum and an idealized Dansgaard-Oeschger climate event: insights from two models of different complexity." Climate of the Past Discussions 8, no. 4 (August 1, 2012): 3093–142. http://dx.doi.org/10.5194/cpd-8-3093-2012.
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Abstract. The role of different sources and sinks of CH4 in changes in atmospheric methane ([CH4]) concentration during the last 100 000 yr is still not fully understood. In particular, the magnitude of the change in wetland CH4 emissions at the last glacial maximum (LGM) relative to the pre-industrial period (PI) as well as during abrupt climatic warmings or Dansgaard-Oeschger events of the last glacial period, is largely unconstrained. In the present study, we aim to understand the uncertainties related to the parameterization of the wetland CH4 emissions models relevant to these time periods by using two wetland models of different complexity (SDGVM and ORCHIDEE). These models have been forced by identical climate fields from low resolution coupled atmosphere-ocean general circulation model (FAMOUS) simulations of these time periods. Both emissions models simulate a large decrease in emissions during LGM in comparison to PI consistent with ice core observations and previous modeling studies. The global reduction is much larger in ORCHIDEE than in SDGVM (respectively −67 and −46%), and whilst the differences can be partially explained by different model sensitivities to temperature (i.e. Q10 values), the major reason for spatial differences between the models, is the inclusion of freezing of soil water in ORCHIDEE and the resultant impact on methanogenesis substrate availability in boreal regions. Besides, a sensitivity test performed with ORCHIDEE in which the methanogenesis substrate sensitivity to the precipitations is modified to be more realistic gives a LGM reduction of −36%. The range of the global LGM decrease is still prone to uncertainty and here, we underline its sensitivity to different process parameterizations. Over the course of an idealized D-O warming, the magnitude of the change in wetland CH4 emissions simulated by the two models at global scale is very similar at around 15 Tg yr−1, but this is only around 25% of the ice-core measured changes in [CH4]. The two models do show regional differences in emissions sensitivity to climate with much larger magnitudes of Northern and Southern tropical anomalies in ORCHIDEE. However, the simulated Northern and Southern tropical anomalies partially compensate each other in both models limiting the net flux change. Future work may need to consider the inclusion of more detailed wetland processes (e.g. linked to permafrost or tropical floodplains), other non-wetland CH4 sources or different patterns of D-O climate change in order to be able to reconcile emissions estimates with the ice-core data for rapid CH4 events.
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Maignan, F., F. M. Bréon, F. Chevallier, N. Viovy, P. Ciais, C. Garrec, J. Trules, and M. Mancip. "Evaluation of a Global Vegetation Model using time series of satellite vegetation indices." Geoscientific Model Development 4, no. 4 (December 5, 2011): 1103–14. http://dx.doi.org/10.5194/gmd-4-1103-2011.
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Abstract. Atmospheric CO2 drives most of the greenhouse effect increase. One major uncertainty on the future rate of increase of CO2 in the atmosphere is the impact of the anticipated climate change on the vegetation. Dynamic Global Vegetation Models (DGVM) are used to address this question. ORCHIDEE is such a DGVM that has proven useful for climate change studies. However, there is no objective and methodological way to accurately assess each new available version on the global scale. In this paper, we submit a methodological evaluation of ORCHIDEE by correlating satellite-derived Vegetation Index time series against those of the modeled Fraction of absorbed Photosynthetically Active Radiation (FPAR). A perfect correlation between the two is not expected, however an improvement of the model should lead to an increase of the overall performance. We detail two case studies in which model improvements are demonstrated, using our methodology. In the first one, a new phenology version in ORCHIDEE is shown to bring a significant impact on the simulated annual cycles, in particular for C3 Grasses and C3 Crops. In the second case study, we compare the simulations when using two different weather fields to drive ORCHIDEE. The ERA-Interim forcing leads to a better description of the FPAR interannual anomalies than the simulation forced by a mixed CRU-NCEP dataset. This work shows that long time series of satellite observations, despite their uncertainties, can identify weaknesses in global vegetation models, a necessary first step to improving them.
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Maignan, F., F. M. Bréon, F. Chevallier, N. Viovy, P. Ciais, C. Garrec, J. Trules, and M. Mancip. "Evaluation of a Dynamic Global Vegetation Model using time series of satellite vegetation indices." Geoscientific Model Development Discussions 4, no. 2 (April 29, 2011): 907–41. http://dx.doi.org/10.5194/gmdd-4-907-2011.
Full textAbstract:
Abstract. Atmospheric CO2 drives most of the greenhouse effect increase and one major uncertainty on the future rate of increase of CO2 in the atmosphere is the impact of the anticipated climate change on the vegetation. Dynamic Global Vegetation Models (DGVM) are used to address this question. ORCHIDEE is such a DGVM that has proven useful for climate change studies. However, there is no objective and methodological way to accurately assess each new available version on the global scale. In this paper, we submit a methodological evaluation of ORCHIDEE by correlating satellite-derived Vegetation Index time series against those of the modeled Fraction of absorbed Photosynthetically Active Radiation (FPAR). A perfect correlation between the two is not expected, however an improvement of the model should lead to an increase of the median correlation. We detail two case studies in which model improvements are demonstrated, using our methodology. In the first one, a new phenology version in ORCHIDEE is shown to bring a significant impact on the simulated annual cycles, in particular for C3 Grasses and C3 Crops. In the second case study, we compare the simulations when using two different weather fields to drive ORCHIDEE. The ERA-Interim forcing leads to a better description of the FPAR interannual anomalies than the simulation forced by a mixed CRU-NCEP dataset. This work shows that long time series of satellite observations, despite their uncertainties, can identify weaknesses in global vegetation models, a necessary first step to improving them.
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Quaas, J., O. Boucher, and U. Lohmann. "Constraining the total aerosol indirect effect in the LMDZ and ECHAM4 GCMs using MODIS satellite data." Atmospheric Chemistry and Physics Discussions 5, no. 5 (October 7, 2005): 9669–90. http://dx.doi.org/10.5194/acpd-5-9669-2005.
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Abstract. Aerosol indirect effects are considered to be the most uncertain yet important anthropogenic forcing of climate change. The goal of the present study is to reduce this uncertainty by constraining two different general circulation models (LMDZ and ECHAM4) with satellite data. We build a statistical relationship between cloud droplet number concentration and the optical depth of the fine aerosol mode as a measure of the aerosol indirect effect using MODerate Resolution Imaging Spectroradiometer (MODIS) satellite data, and constrain the model parameterizations to match this relationship. We include here ''empirical'' formulations for the cloud albedo effect as well as parameterizations of the cloud lifetime effect. When fitting the model parameterizations to the satellite data, consistently in both models, the radiative forcing by the combined aerosol indirect effect is reduced considerably, down to −0.5 and −0.3 Wm-2, for LMDZ and ECHAM4, respectively.
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Quaas, J., O. Boucher, and U. Lohmann. "Constraining the total aerosol indirect effect in the LMDZ and ECHAM4 GCMs using MODIS satellite data." Atmospheric Chemistry and Physics 6, no. 4 (March 27, 2006): 947–55. http://dx.doi.org/10.5194/acp-6-947-2006.
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Abstract. Aerosol indirect effects are considered to be the most uncertain yet important anthropogenic forcing of climate change. The goal of the present study is to reduce this uncertainty by constraining two different general circulation models (LMDZ and ECHAM4) with satellite data. We build a statistical relationship between cloud droplet number concentration and the optical depth of the fine aerosol mode as a measure of the aerosol indirect effect using MODerate Resolution Imaging Spectroradiometer (MODIS) satellite data, and constrain the model parameterizations to match this relationship. We include here "empirical" formulations for the cloud albedo effect as well as parameterizations of the cloud lifetime effect. When fitting the model parameterizations to the satellite data, consistently in both models, the radiative forcing by the combined aerosol indirect effect is reduced considerably, down to −0.5 and −0.3 Wm−2, for LMDZ and ECHAM4, respectively.
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Belviso, Sauveur, Marine Remaud, Camille Abadie, Fabienne Maignan, Michel Ramonet, and Philippe Peylin. "Ongoing Decline in the Atmospheric COS Seasonal Cycle Amplitude over Western Europe: Implications for Surface Fluxes." Atmosphere 13, no. 5 (May 16, 2022): 812. http://dx.doi.org/10.3390/atmos13050812.
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Atmospheric carbonyl sulfide (COS) was monitored at the GIF site (France) from August 2014 to November 2021. A significant decreasing trend in the seasonal cycle amplitude (SCA) of the COS was observed for the first time in the Northern Hemisphere (−27 ppt over 6 years). The lowest SCA was recorded in 2021 (80 ppt vs. 107 ppt in 2015). The trend in the SCA results revealed a steeper decline in the spring maximum than in that of the autumn minimum (−49 ppt vs. −10 ppt over 6 years, respectively). These negative trends were qualitatively consistent with those in the tropospheric COS put forward by the NDACC network of ground-based FTIR instruments, which were attributed to a slowing in the rate of COS anthropogenic emissions. Simulations using the ORCHIDEE land-surface model showed that a decrease in COS lowers the uptake of this gas by plants. Our observations suggest the existence of a causal relationship between the decline in the SCA and that in the tropospheric COS, implying that the temporal variations in the COS SCA over Western Europe are essentially driven by plant uptake. However, the transport by the LMDz 3-D model of surface fluxes for each component of the COS budget failed to reproduce this feature at GIF, pointing to a likely misrepresentation of the marine and anthropogenic fluxes in the footprint of this station.
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Szczypta, C., J. C. Calvet, F. Maignan, W. Dorigo, F. Baret, and P. Ciais. "Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts." Geoscientific Model Development Discussions 6, no. 4 (November 6, 2013): 5553–94. http://dx.doi.org/10.5194/gmdd-6-5553-2013.
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Abstract. Two new remotely sensed Leaf Area Index (LAI) and Surface Soil Moisture (SSM) satellite products are compared with two sets of simulations of the ORCHIDEE and ISBA-A-gs land surface models to investigate how recent droughts affected vegetation over the Euro-Mediterranean area. We analyze the interannual variability over the period 1991–2008. The leaf onset and the Length of the vegetation Growing Period (LGP) are derived from the satellite-derived LAI and from the modelled LAI. The LGP values produced by the photosynthesis-driven phenology model of ISBA-A-gs are closer to the satellite-derived LAI LGP than those produced by ORCHIDEE. In the latter, the phenology is based on a growing degree-day model for leaf onset, and on both climatic conditions and leaf life span for senescence. Further, the interannual variability of LAI is better captured by ISBA-A-gs than by ORCHIDEE. The summer 2003 drought case study shows a relatively good agreement of the modelled LAI anomalies with the observations, but the two models underestimate plant regrowth in the autumn. A better representation of the root-zone soil moisture profile could improve the simulations of both models. The satellite-derived SSM is compared with SSM simulations of ISBA-A-gs, only, as ORCHIDEE has no explicit representation of SSM. Overall, the ISBA-A-gs simulations of SSM agree well with the satellite-derived SSM and are used to detect regions where the satellite product could be improved. Finally, a correspondence is found between the interannual variability of detrended SSM and LAI. The predictability of LAI is less pronounced using remote sensing observations than using simulated variables. However, consistent results are found in July for the croplands of Ukraine and southern Russia.
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Naudts, K., J. Ryder, M. J. McGrath, J. Otto, Y. Chen, A. Valade, V. Bellasen, et al. "A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes." Geoscientific Model Development 8, no. 7 (July 13, 2015): 2035–65. http://dx.doi.org/10.5194/gmd-8-2035-2015.
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Abstract. Since 70 % of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate change. Yet, none of the land-surface models used in Earth system models, and therefore none of today's predictions of future climate, accounts for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrising a version of the ORCHIDEE land-surface model to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new branch called ORCHIDEE-CAN (SVN r2290) and the trunk version of ORCHIDEE (SVN r2243) are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes were introduced towards a better process representation for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrisation was revisited after introducing 12 new parameter sets that represent specific tree species or genera rather than a group of often distantly related or even unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy structure, gross primary production (GPP), albedo and evapotranspiration over Europe. For all tested variables, ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92 % chance to reproduce the spatial and temporal variability of the validation data.
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Naudts, K., J. Ryder, M. J. McGrath, J. Otto, Y. Chen, A. Valade, V. Bellasen, et al. "A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes." Geoscientific Model Development Discussions 7, no. 6 (December 5, 2014): 8565–647. http://dx.doi.org/10.5194/gmdd-7-8565-2014.
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Abstract. Since 70% of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate change. Yet, none of the land surface models used in Earth system models, and therefore none of today's predictions of future climate, account for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrizing a version of the land surface model ORCHIDEE to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new branch called ORCHIDEE-CAN (SVN r2290) and the trunk version of ORCHIDEE (SVN r2243) are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes towards a~better process representation occurred for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a~numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrization was revisited after introducing twelve new parameter sets that represent specific tree species or genera rather than a group of unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy strucure, GPP, albedo and evapotranspiration over Europe. For all tested variables ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92% chance to reproduce the spatial and temporal variability of the validation data.
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Lemonnier, F., A. Chemison, G. Krinner, J. B. Madeleine, C. Claud, and C. Genthon. "Evaluation of coastal Antarctic precipitation in LMDz6 global atmospheric model using ground-based radar observations." Arctic and Antarctic Research 67, no. 2 (July 11, 2021): 147–64. http://dx.doi.org/10.30758/0555-2648-2021-67-2-147-164.
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In the current context of climate change in the poles, one of the objectives of the APRES3 (Antarctic Precipitation Remote Sensing from Surface and Space) project was to characterize the vertical structure of precipitation in order to better simulate it. Precipitation simulated by models in Antarctica is currently very widespread and it overestimates the data. Sensitivity studies have been conducted using a global climate model and compared to the observations obtained at the Dumont d’Urville coast station, obtained by a Micro Rain Radar (MRR). The LMDz/IPSL general circulation model, with zoomed configuration over Dumont d’Urville, has been considered for this study. A sensitivity study was conducted on the physical and numerical parameters of the LMDz model with the aim of estimating their contribution to the precipitation simulation. Sensitivity experiments revealed that changes in the sedimentation and sublimation parameters do not significantly impact precipitation rate. However, dissipation of the LMDz model, which is a numerical process that dissipates spatially excessive energy and keeps the model stable, impacts precipitation indirectly but very strongly. A suitable adjustment of the dissipation reduces significantly precipitation over Antarctic peripheral area, thus providing a simulated profile in better agreement with the MRR observations.
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Gryazin, V., C. Risi, J. Jouzel, N. Kurita, J. Worden, C. Frankenberg, V. Bastrikov, K. Gribanov, and O. Stukova. "To what extent could water isotopic measurements help us understand model biases in the water cycle over Western Siberia." Atmospheric Chemistry and Physics 14, no. 18 (September 17, 2014): 9807–30. http://dx.doi.org/10.5194/acp-14-9807-2014.
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Abstract. We evaluate the isotopic composition of water vapor and precipitation simulated by the LMDZ (Laboratoire de Météorologie Dynamique-Zoom) GCM (General Circulation Model) over Siberia using several data sets: TES (Tropospheric Emission Spectrometer) and GOSAT (Greenhouse gases Observing SATellite) satellite observations of tropospheric water vapor, GNIP (Global Network for Isotopes in Precipitation) and SNIP (Siberian Network for Isotopes in Precipitation) precipitation networks, and daily, in situ measurements of water vapor and precipitation at the Kourovka site in Western Siberia. LMDZ captures the spatial, seasonal and daily variations reasonably well, but it underestimates humidity (q) in summer and overestimates δD in the vapor and precipitation in all seasons. The performance of LMDZ is put in the context of other isotopic models from the SWING2 (Stable Water Intercomparison Group phase 2) models. There is significant spread among models in the simulation of δD, and of the δD-q relationship. This confirms that δD brings additional information compared to q only. We specifically investigate the added value of water isotopic measurements to interpret the warm and dry bias featured by most GCMs over mid and high latitude continents in summer. The analysis of the slopes in δD-q diagrams and of processes controlling δD and q variations suggests that the cause of the dry bias could be either a problem in the large-scale advection transporting too much dry and warm air from the south, or too strong boundary-layer mixing. However, δD-q diagrams using the available data do not tell the full story. Additional measurements would be needed, or a more sophisticated theoretical framework would need to be developed.
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De Pue, Jan, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Manuela Balzarolo, Fabienne Maignan, and Françoise Gellens-Meulenberghs. "Local-scale evaluation of the simulated interactions between energy, water and vegetation in ISBA, ORCHIDEE and a diagnostic model." Biogeosciences 19, no. 17 (September 14, 2022): 4361–86. http://dx.doi.org/10.5194/bg-19-4361-2022.
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Abstract. The processes involved in the exchange of water, energy and carbon in terrestrial ecosystems are strongly intertwined. To accurately represent the terrestrial biosphere in land surface models (LSMs), the intrinsic coupling between these processes is required. Soil moisture and leaf area index (LAI) are two key variables at the nexus of water, energy and vegetation. Here, we evaluated two prognostic LSMs (ISBA and ORCHIDEE) and a diagnostic model (based on the LSA SAF, Satellite Application Facility for Land Surface Analysis, algorithms) in their ability to simulate the latent heat flux (LE) and gross primary production (GPP) coherently and their interactions through LAI and soil moisture. The models were validated using in situ eddy covariance observations, soil moisture measurements and remote-sensing-based LAI. It was found that the diagnostic model performed consistently well, regardless of land cover, whereas important shortcomings of the prognostic models were revealed for herbaceous and dry sites. Despite their different architecture and parametrization, ISBA and ORCHIDEE shared some key weaknesses. In both models, LE and GPP were found to be oversensitive to drought stress. Though the simulated soil water dynamics could be improved, this was not the main cause of errors in the surface fluxes. Instead, these errors were strongly correlated to errors in LAI. The simulated phenological cycle in ISBA and ORCHIDEE was delayed compared to observations and failed to capture the observed seasonal variability. The feedback mechanism between GPP and LAI (i.e. the biomass allocation scheme) was identified as a key element to improve the intricate coupling between energy, water and vegetation in LSMs.
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Szczypta, C., J. C. Calvet, F. Maignan, W. Dorigo, F. Baret, and P. Ciais. "Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts." Geoscientific Model Development 7, no. 3 (May 20, 2014): 931–46. http://dx.doi.org/10.5194/gmd-7-931-2014.
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Abstract. Two new remotely sensed leaf area index (LAI) and surface soil moisture (SSM) satellite-derived products are compared with two sets of simulations of the ORganizing Carbon and Hydrology In Dynamic EcosystEms (ORCHIDEE) and Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs) land surface models. We analyse the interannual variability over the period 1991–2008. The leaf onset and the length of the vegetation growing period (LGP) are derived from both the satellite-derived LAI and modelled LAI. The LGP values produced by the photosynthesis-driven phenology model of ISBA-A-gs are closer to the satellite-derived LAI and LGP than those produced by ORCHIDEE. In the latter, the phenology is based on a growing degree day model for leaf onset, and on both climatic conditions and leaf life span for senescence. Further, the interannual variability of LAI is better captured by ISBA-A-gs than by ORCHIDEE. In order to investigate how recent droughts affected vegetation over the Euro-Mediterranean area, a case study addressing the summer 2003 drought is presented. It shows a relatively good agreement of the modelled LAI anomalies with the observations, but the two models underestimate plant regrowth in the autumn. A better representation of the root-zone soil moisture profile could improve the simulations of both models. The satellite-derived SSM is compared with SSM simulations of ISBA-A-gs only, as ORCHIDEE has no explicit representation of SSM. Overall, the ISBA-A-gs simulations of SSM agree well with the satellite-derived SSM and are used to detect regions where the satellite-derived product could be improved. Finally, a correspondence is found between the interannual variability of detrended SSM and LAI. The predictability of LAI is less pronounced using remote sensing observations than using simulated variables. However, consistent results are found in July for the croplands of the Ukraine and southern Russia.
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Caram, Cyril, Sophie Szopa, Anne Cozic, Slimane Bekki, Carlos A. Cuevas, and Alfonso Saiz-Lopez. "Sensitivity of tropospheric ozone to halogen chemistry in the chemistry–climate model LMDZ-INCA vNMHC." Geoscientific Model Development 16, no. 14 (July 18, 2023): 4041–62. http://dx.doi.org/10.5194/gmd-16-4041-2023.
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Abstract. The atmospheric chemistry of halogenated species (Cl, Br, I) participates in the global chemical sink of tropospheric ozone and perturbs the oxidising capacity of the troposphere, notably by influencing the atmospheric lifetime of methane. Global chemistry–climate models are commonly used to assess the global budget of ozone and its sensitivity to emissions of its precursors, as well as to project its long-term evolution. Here, we report on the implementation of tropospheric sources and chemistry of halogens in the chemistry–climate model LMDZ-INCA (Laboratoire de Météorologie Dynamique general circulation model, LMDZ, and Interactions with Chemistry and Aerosols, INCA, version with Non-Methane HydroCarbon chemistry, vNMHC) and evaluate halogen effects on the tropospheric ozone budget. Overall, the results show that the model simulates satisfactorily the impact of halogens on the photo-oxidising system in the troposphere, in particular in the marine boundary layer. To quantify the effects of halogen chemistry in LMDZ-INCA, standard metrics representative of the behaviour of the tropospheric chemical system (Ox, HOx, NOx, CH4 and non-methane volatile organic compounds – NMVOCs) are computed with and without halogens. The addition of tropospheric halogens in the LMDZ-INCA model leads to a decrease of 22 % in the ozone burden, 8 % in OH and 33 % in NOx. Sensitivity simulations show for the first time that the inclusion of halogen chemistry makes ozone more sensitive to perturbations in CH4, NOx and NMVOCs. Consistent with other global model studies, the sensitivity of the tropospheric ozone burden to changes from pre-industrial to present-day emissions is found to be ∼20 % lower when tropospheric halogens are taken into account.
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Gielen, B., J. Neirynck, H. Verbeeck, D. A. Sampson, F. Vermeiren, and I. A. Janssens. "Decadal water balance of a temperate Scots pine forest (<i>Pinus sylvestris</i> L.) based on measurements and modelling." Biogeosciences Discussions 6, no. 6 (November 11, 2009): 10519–55. http://dx.doi.org/10.5194/bgd-6-10519-2009.
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Abstract. Multi-year, multi-technique studies often yield key insights into methodological limitations but also process-level interactions that would otherwise go un-noticed if analysed at one point in time or in isolation. We examined the components of forest water balance for an 80-year-old Scots pine (Pinus sylvestris L.) stand in the Campine region of Belgium over a ten year period using five very different approaches; our methods ranged from data intensive measurements to process model simulations. Specifically, we used the conservative ion method (CI), the Eddy Covariance technique (EC), an empirical model (WATBAL), and two process models that vary greatly in their temporal and spatial scaling, the ORCHIDEE global land-surface model and SECRETS a stand- to ecosystem-scale biogeochemical process model. Herein we used the EC technique as a standard for the evapotranspiration (ET) estimates. We also examined ET and drainage in ORCHIDEE as influenced by climate change scenarios from the Hadley model. Results demonstrated that the two process models corresponded well to the seasonal patterns and yearly totals of ET from the EC approach. However, both WATBAL and CI approaches overestimated ET when compared to the EC estimates. Overestimation of ET by WATBAL increased as ET increased. We found positive relationships between ET and the process drivers to ET (i.e., vapour pressure deficit [VPD], mean air temperature [Tair], and global radiation [Rg]) for SECRETS, ORCHIDEE, and the EC estimates, though few were significant. Estimates of ET from WATBAL and the CI approach were uncoupled from VPD, Tair, and Rg. Independent of the method examined, ET exhibited low interannual variability. Consequently, drainage fluxes were highly correlated with annual precipitation for all five approaches examined. Estimates of ET increased in climate change scenarios for ORCHIDEE while drainage decreased.
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Chen, Yi-Ying, Barry Gardiner, Ferenc Pasztor, Kristina Blennow, James Ryder, Aude Valade, Kim Naudts, et al. "Simulating damage for wind storms in the land surface model ORCHIDEE-CAN (revision 4262)." Geoscientific Model Development 11, no. 2 (March 2, 2018): 771–91. http://dx.doi.org/10.5194/gmd-11-771-2018.
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Abstract. Earth system models (ESMs) are currently the most advanced tools with which to study the interactions among humans, ecosystem productivity, and the climate. The inclusion of storm damage in ESMs has long been hampered by their big-leaf approach, which ignores the canopy structure information that is required for process-based wind-throw modelling. Recently the big-leaf assumptions in the large-scale land surface model ORCHIDEE-CAN were replaced by a three-dimensional description of the canopy structure. This opened the way to the integration of the processes from the small-scale wind damage risk model ForestGALES into ORCHIDEE-CAN. The integration of ForestGALES into ORCHIDEE-CAN required, however, developing numerically efficient solutions to deal with (1) landscape heterogeneity, i.e. account for newly established forest edges for the parameterization of gusts; (2) downscaling spatially and temporally aggregated wind fields to obtain more realistic wind speeds that would represents gusts; and (3) downscaling storm damage within the 2500 km2 pixels of ORCHIDEE-CAN. This new version of ORCHIDEE-CAN was parameterized over Sweden. Subsequently, the performance of the model was tested against data for historical storms in southern Sweden between 1951 and 2010 and south-western France in 2009. In years without big storms, here defined as a storm damaging less than 15 × 106 m3 of wood in Sweden, the model error is 1.62 × 106 m3, which is about 100 % of the observed damage. For years with big storms, such as Gudrun in 2005, the model error increased to 5.05 × 106 m3, which is between 10 and 50 % of the observed damage. When the same model parameters were used over France, the model reproduced a decrease in leaf area index and an increase in albedo, in accordance with SPOT-VGT and MODIS records following the passing of Cyclone Klaus in 2009. The current version of ORCHIDEE-CAN (revision 4262) is therefore expected to have the capability to capture the dynamics of forest structure due to storm disturbance on both regional and global scales, although the empirical parameters calculating gustiness from the gridded wind fields and storm damage from critical wind speeds may benefit from regional fitting.
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Huneeus, N., O. Boucher, and F. Chevallier. "Simplified aerosol modeling for variational data assimilation." Geoscientific Model Development 2, no. 2 (November 16, 2009): 213–29. http://dx.doi.org/10.5194/gmd-2-213-2009.
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Abstract. We have developed a simplified aerosol model together with its tangent linear and adjoint versions for the ultimate aim of optimizing global aerosol and aerosol precursor emission using variational data assimilation. The model was derived from the general circulation model LMDz; it groups together the 24 aerosol species simulated in LMDz into 4 species, namely gaseous precursors, fine mode aerosols, coarse mode desert dust and coarse mode sea salt. The emissions have been kept as in the original model. Modifications, however, were introduced in the computation of aerosol optical depth and in the processes of sedimentation, dry and wet deposition and sulphur chemistry to ensure consistency with the new set of species and their composition. The simplified model successfully manages to reproduce the main features of the aerosol distribution in LMDz. The largest differences in aerosol load are observed for fine mode aerosols and gaseous precursors. Differences between the original and simplified models are mainly associated to the new deposition and sedimentation velocities consistent with the definition of species in the simplified model and the simplification of the sulphur chemistry. Furthermore, simulated aerosol optical depth remains within the variability of monthly AERONET observations for all aerosol types and all sites throughout most of the year. Largest differences are observed over sites with strong desert dust influence. In terms of the daily aerosol variability, the model is less able to reproduce the observed variability from the AERONET data with larger discrepancies in stations affected by industrial aerosols. The simplified model however, closely follows the daily simulation from LMDz. Sensitivity analyses with the tangent linear version show that the simplified sulphur chemistry is the dominant process responsible for the strong non-linearity of the model.
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Dufour, G., S. Szopa, M. P. Barkley, C. D. Boone, A. Perrin, P. I. Palmer, and P. F. Bernath. "Global upper-tropospheric formaldehyde: seasonal cycles observed by the ACE-FTS satellite instrument." Atmospheric Chemistry and Physics 9, no. 12 (June 16, 2009): 3893–910. http://dx.doi.org/10.5194/acp-9-3893-2009.
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Abstract. Seasonally-resolved upper tropospheric profiles of formaldehyde (HCHO) observed by the ACE Fourier transform spectrometer (ACE-FTS) on a near-global scale are presented for the time period from March 2004 to November 2006. Large upper tropospheric HCHO mixing ratios (>150 pptv) are observed during the growing season of the terrestrial biosphere in the Northern Hemisphere and during the biomass burning season in the Southern Hemisphere. The total errors estimated for the retrieved mixing ratios range from 30 to 40% in the upper troposphere and increase in the lower stratosphere. The sampled HCHO concentrations are in satisfactory agreement with previous aircraft and satellite observations with a negative bias (<25%) within observation errors. An overview of the seasonal cycle of the upper tropospheric HCHO is given for different latitudes, with a particular focus on mid-to-high latitudes that are well sampled by the observations. A maximum is observed during summer, i.e. during the growing season, in the northern mid- and high latitudes. The influence of biomass burning is visible in HCHO upper tropospheric concentrations during the September-to-October period in the southern tropics and subtropics. Comparisons with two state-of-the-art models (GEOS-Chem and LMDz-INCA) show that the models capture well the seasonal variations observed in the Northern Hemisphere (correlation >0.9). Both models underestimate the summer maximum over Europe and Russia and differences in the emissions used for North America result in a good reproduction of the summer maximum by GEOS-Chem but in an underestimate by LMDz-INCA. Globally, GEOS-Chem reproduces well the observations on average over one year but has some difficulties in reproducing the spatial variability of the observations. LMDz-INCA shows significant bias in the Southern Hemisphere, perhaps related to an underestimation of methane, but better reproduces the temporal and spatial variations. The differences between the models underline the large uncertainties that remain in the emissions of HCHO precursors.
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Huneeus, N., O. Boucher, and F. Chevallier. "Simplified aerosol modeling for variational data assimilation." Geoscientific Model Development Discussions 2, no. 1 (June 23, 2009): 639–80. http://dx.doi.org/10.5194/gmdd-2-639-2009.
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Abstract. We have developed a simplified aerosol model together with its tangent linear and adjoint versions for variational assimilation of aerosol optical depth with the aim to optimize aerosol emissions over the globe. The model was derived from the general circulation model LMDz; it groups together the 24 aerosol species simulated in LMDz into 4 species, namely gaseous precursors, fine mode aerosols, coarse mode desert dust and coarse mode sea salt. The emissions have been kept as in the original model. Modifications, however, were introduced in the computation of aerosol optical depth and in the processes of sedimentation, dry and wet deposition and sulfur chemistry to ensure consistency with the new set of species and their composition. The simplified model successfully manages to reproduce the main features of the aerosol distribution in LMDz. Differences between the original and simplified models are mainly associated to the new deposition and sedimentation velocities consistent with the definition of species in the simplified model and the simplification of the sulfur chemistry. Furthermore, simulated aerosol optical depth remains within the variability of AERONET observations for all aerosol types and all sites throughout most of the year. Sensitivity analyses with the tangent linear version show that the simplified sulfur chemistry is the dominant process responsible for the strong non-linearity of the model.
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Guenet, B., F. E. Moyano, N. Vuichard, G. J. D. Kirk, P. H. Bellamy, S. Zaehle, and P. Ciais. "Can we model observed soil carbon changes from a dense inventory? A case study over England and Wales using three versions of the ORCHIDEE ecosystem model (AR5, AR5-PRIM and O-CN)." Geoscientific Model Development 6, no. 6 (December 19, 2013): 2153–63. http://dx.doi.org/10.5194/gmd-6-2153-2013.
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Abstract. A widespread decrease of the topsoil carbon content was observed over England and Wales during the period 1978–2003 in the National Soil Inventory (NSI), amounting to a carbon loss of 4.44 Tg yr−1 over 141 550 km2. Subsequent modelling studies have shown that changes in temperature and precipitation could only account for a small part of the observed decrease, and therefore that changes in land use and management and resulting changes in heterotrophic respiration or net primary productivity were the main causes. So far, all the models used to reproduce the NSI data have not accounted for plant–soil interactions and have only been soil carbon models with carbon inputs forced by data. Here, we use three different versions of a process-based coupled soil–vegetation model called ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems), in order to separate the effect of trends in soil carbon input from soil carbon mineralization induced by climate trends over 1978–2003. The first version of the model (ORCHIDEE-AR5), used for IPCC-AR5 CMIP5 Earth System simulations, is based on three soil carbon pools defined with first-order decomposition kinetics, as in the CENTURY model. The second version (ORCHIDEE-AR5-PRIM) built for this study includes a relationship between litter carbon and decomposition rates, to reproduce a priming effect on decomposition. The last version (O-CN) takes into account N-related processes. Soil carbon decomposition in O-CN is based on CENTURY, but adds N limitations on litter decomposition. We performed regional gridded simulations with these three versions of the ORCHIDEE model over England and Wales. None of the three model versions was able to reproduce the observed NSI soil carbon trend. This suggests either that climate change is not the main driver for observed soil carbon losses or that the ORCHIDEE model even with priming or N effects on decomposition lacks the basic mechanisms to explain soil carbon change in response to climate, which would raise a caution flag about the ability of this type of model to project soil carbon changes in response to future warming. A third possible explanation could be that the NSI measurements made on the topsoil are not representative of the total soil carbon losses integrated over the entire soil depth, and thus cannot be compared with the model output.
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Guenet, B., F. E Moyano, N. Vuichard, G. J. D. Kirk, P. H. Bellamy, S. Zaehle, and P. Ciais. "Can we model observed soil carbon changes from a dense inventory? A case study over england and wales using three version of orchidee ecosystem model (AR5, AR5-PRIM and O-CN)." Geoscientific Model Development Discussions 6, no. 3 (July 12, 2013): 3655–80. http://dx.doi.org/10.5194/gmdd-6-3655-2013.
Full textAbstract:
Abstract. A widespread decrease of the top soil carbon content was observed over England and Wales during the period 1978–2003 in the National Soil Inventory (NSI), amounting to a carbon loss of 4.44 Tg yr-1 over 141 550 km2. Subsequent modelling studies have shown that changes in temperature and precipitation could only account for a small part of the observed decrease, and therefore that changes in land use and management and resulting changes in soil respiration or primary production were the main causes. So far, all the models used to reproduce the NSI data did not account for plant-soil interactions and were only soil carbon models with carbon inputs forced by data. Here, we use three different versions of a process-based coupled soil-vegetation model called ORCHIDEE, in order to separate the effect of trends in soil carbon input, and soil carbon mineralisation induced by climate trends over 1978–2003. The first version of the model (ORCHIDEE-AR5) used for IPCC-AR5 CMIP5 Earth System simulations, is based on three soil carbon pools defined with first order decomposition kinetics, as in the CENTURY model. The second version (ORCHIDEE-AR5-PRIM) built for this study includes a relationship between litter carbon and decomposition rates, to reproduce a priming effect on decomposition. The last version (O-CN) takes into account N-related processes. Soil carbon decomposition in O-CN is based on CENTURY, but adds N limitations on litter decomposition. We performed regional gridded simulations with these three versions of the ORCHIDEE model over England and Wales. None of the three model versions was able to reproduce the observed NSI soil carbon trend. This suggests that either climate change is not the main driver for observed soil carbon losses, or that the ORCHIDEE model even with priming or N-effects on decomposition lacks the basic mechanisms to explain soil carbon change in response to climate, which would raise a caution flag about the ability of this type of model to project soil carbon changes in response to future warming. A third possible explanation could be that the NSI measurements made on the topsoil are not representative of the total soil carbon losses integrated over the entire soil depth, and thus cannot be compared with the model output.
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Woillez, M. N., M. Kageyama, N. Combourieu-Nebout, and G. Krinner. "Simulating the vegetation response to abrupt climate changes under glacial conditions with the ORCHIDEE/IPSL models." Biogeosciences Discussions 9, no. 9 (September 19, 2012): 12895–950. http://dx.doi.org/10.5194/bgd-9-12895-2012.
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Abstract. The last glacial period has been punctuated by two types of abrupt climatic events, the Dansgaard-Oeschger (DO) and Heinrich (HE) events. These events, recorded in Greenland ice and in marine sediments, involved changes in the Atlantic Meridional Overturning Circulation (AMOC) and led to major changes in the terrestrial biosphere. Here we use the dynamical global vegetation model ORCHIDEE to simulate the response of vegetation to abrupt changes in the AMOC strength. To do so, we force ORCHIDEE off-line with outputs from the IPSL_CM4 general circulation model, in which we have forced the AMOC to change by adding freshwater fluxes in the North Atlantic. We investigate the impact of a collapse and recovery of the AMOC, at different rates, and focus on Western Europe, where many pollen records are available to compare with. The impact of an AMOC collapse on the European mean temperatures and precipitations simulated by the GCM is relatively small but sufficient to drive an important regression of forests and expansion of grasses in ORCHIDEE, in qualitative agreement with pollen data for an HE event. On the contrary, a run with a rapid shift of the AMOC to an hyperactive state of 30 Sv, mimicking the warming phase of a DO event, does not exhibit a strong impact on the European vegetation compared to the glacial control state. For our model, simulating the impact of an HE event thus appears easier than simulating the abrupt transition towards the interstadial phase of a DO. For both a collapse or a recovery of the AMOC the vegetation starts to respond to climatic changes immediately but reaches equilibrium about 200 yr after the climate equilibrates, suggesting a possible bias in the climatic reconstructions based on pollen records, which assume equilibrium between climate and vegetation. However, our study does not take into account vegetation feedbacks on the atmosphere.
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Ahmadov, R., C. Gerbig, R. Kretschmer, S. Körner, C. Rödenbeck, P. Bousquet, and M. Ramonet. "Can we use hourly CO<sub>2</sub> concentration data in inversions? Comparing high resolution WRF-VPRM simulations with coastal tower measurements of CO<sub>2</sub>." Biogeosciences Discussions 5, no. 6 (December 5, 2008): 4745–76. http://dx.doi.org/10.5194/bgd-5-4745-2008.
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Abstract. In order to better understand the effects that mesoscale transport has on atmospheric CO2 distributions, we have used the WRF model coupled to the diagnostic biospheric model VPRM, which provides high-resolution biospheric CO2 fluxes based on MODIS satellite indices. We have run WRF-VPRM for the period from 16 May to 15 June in 2005 covering the intensive period of the CERES experiment, using the CO2 fields from the global model LMDZ for initialization and lateral boundary conditions. The comparison of modeled CO2 concentration time series against observations at the Biscarosse tower and against output from two global models – LMDZ and TM3 – clearly reveals that WRF-VPRM can capture the measured CO2 signal much better than the global models with lower resolution. Also the diurnal variability of the atmospheric CO2 field caused by recirculation of nighttime respired CO2 is simulated by WRF-VRPM reasonably well. Analysis of the nighttime data indicates that with high resolution modeling tools such as WRF-VPRM a large fraction of the time periods that are impossible to utilize in global models, can be used quantitatively and help constraining respiratory fluxes. The paper concludes that we need to utilize a high-resolution model such as WRF-VPRM to use continental observations of CO2 concentration data with more spatial and temporal coverage and to link them to the global inversion models.
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Ahmadov, R., C. Gerbig, R. Kretschmer, S. Körner, C. Rödenbeck, P. Bousquet, and M. Ramonet. "Comparing high resolution WRF-VPRM simulations and two global CO<sub>2</sub> transport models with coastal tower measurements of CO<sub>2</sub>." Biogeosciences 6, no. 5 (May 15, 2009): 807–17. http://dx.doi.org/10.5194/bg-6-807-2009.
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Abstract. In order to better understand the effects that mesoscale transport has on atmospheric CO2 distributions, we have used the atmospheric WRF model coupled to the diagnostic biospheric model VPRM, which provides high resolution biospheric CO2 fluxes based on MODIS satellite indices. We have run WRF-VPRM for the period from 16 May to 15 June in 2005 covering the intensive period of the CERES experiment, using the CO2 fields from the global model LMDZ for initialization and lateral boundary conditions. The comparison of modeled CO2 concentration time series against observations at the Biscarosse tower and against output from two global models – LMDZ and TM3 – clearly reveals that WRF-VPRM can capture the measured CO2 signal much better than the global models with lower resolution. Also the diurnal variability of the atmospheric CO2 field caused by recirculation of nighttime respired CO2 is simulated by WRF-VRPM reasonably well. Analysis of the nighttime data indicates that with high resolution modeling tools such as WRF-VPRM a large fraction of the time periods that are impossible to utilize in global models, can be used quantitatively and may help to constrain respiratory fluxes. The paper concludes that we need to utilize a high-resolution model such as WRF-VPRM to use continental observations of CO2 concentration data with more spatial and temporal coverage and to link them to the global inversion models.
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Zhang, Yuan, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan. "Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)." Geoscientific Model Development 15, no. 24 (December 20, 2022): 9111–25. http://dx.doi.org/10.5194/gmd-15-9111-2022.
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Abstract. Plant transpiration dominates terrestrial latent heat fluxes (LE) and plays a central role in regulating the water cycle and land surface energy budget. However, Earth system models (ESMs) currently disagree strongly on the amount of transpiration, and thus LE, leading to large uncertainties in simulating future climate. Therefore, it is crucial to correctly represent the mechanisms controlling the transpiration in models. At the leaf scale, transpiration is controlled by stomatal regulation, and at the canopy scale, through turbulence, which is a function of canopy structure and wind. The coupling of vegetation to the atmosphere can be characterized by the coefficient Ω. A value of Ω→0 implies a strong coupling of vegetation and the atmosphere, leaving a dominant role to stomatal conductance in regulating water (H2O) and carbon dioxide (CO2) fluxes, while Ω→1 implies a complete decoupling of leaves from the atmosphere, i.e., the transfer of H2O and CO2 is limited by aerodynamic transport. In this study, we investigated how well the land surface model (LSM) Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) (v7266) simulates the coupling of vegetation to the atmosphere by using empirical daily estimates of Ω derived from flux measurements from 90 FLUXNET sites. Our results show that ORCHIDEE generally captures the Ω in forest vegetation types (0.27 ± 0.12) compared with observation (0.26 ± 0.09) but underestimates Ω in grasslands (GRA) and croplands (CRO) (0.25 ± 0.15 for model, 0.33 ± 0.17 for observation). The good model performance in forests is due to compensation of biases in surface conductance (Gs) and aerodynamic conductance (Ga). Calibration of key parameters controlling the dependence of the stomatal conductance to the water vapor deficit (VPD) improves the simulated Gs and Ω estimates in grasslands and croplands (0.28 ± 0.20). To assess the underlying controls of Ω, we applied random forest (RF) models to both simulated and observation-based Ω. We found that large observed Ω are associated with periods of low wind speed, high temperature and low VPD; it is also related to sites with large leaf area index (LAI) and/or short vegetation. The RF models applied to ORCHIDEE output generally agree with this pattern. However, we found that the ORCHIDEE underestimated the sensitivity of Ω to VPD when the VPD is high, overestimated the impact of the LAI on Ω, and did not correctly simulate the temperature dependence of Ω when temperature is high. Our results highlight the importance of observational constraints on simulating the vegetation–atmosphere coupling strength, which can help to improve predictive accuracy of water fluxes in Earth system models.
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Remaud, Marine, Frédéric Chevallier, Anne Cozic, Xin Lin, and Philippe Bousquet. "On the impact of recent developments of the LMDz atmospheric general circulation model on the simulation of CO<sub>2</sub> transport." Geoscientific Model Development 11, no. 11 (November 9, 2018): 4489–513. http://dx.doi.org/10.5194/gmd-11-4489-2018.
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Abstract. The quality of the representation of greenhouse gas (GHG) transport in atmospheric general circulation models (GCMs) drives the potential of inverse systems to retrieve GHG surface fluxes to a large extent. In this work, the transport of CO2 is evaluated in the latest version of the Laboratoire de Météorologie Dynamique (LMDz) GCM, developed for the Climate Model Intercomparison Project 6 (CMIP6) relative to the LMDz version developed for CMIP5. Several key changes have been implemented between the two versions, which include a more elaborate radiative scheme, new subgrid-scale parameterizations of convective and boundary layer processes and a refined vertical resolution. We performed a set of simulations of LMDz with different physical parameterizations, two different horizontal resolutions and different land surface schemes, in order to test the impact of those different configurations on the overall transport simulation. By modulating the intensity of vertical mixing, the physical parameterizations control the interhemispheric gradient and the amplitude of the seasonal cycle in the Northern Hemisphere, as emphasized by the comparison with observations at surface sites. However, the effect of the new parameterizations depends on the region considered, with a strong impact over South America (Brazil, Amazonian forest) but a smaller impact over Europe, East Asia and North America. A finer horizontal resolution reduces the representation errors at observation sites near emission hotspots or along the coastlines. In comparison, the sensitivities to the land surface model and to the increased vertical resolution are marginal.
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Raoult, Nina, Catherine Ottlé, Philippe Peylin, Vladislav Bastrikov, and Pascal Maugis. "Evaluating and Optimizing Surface Soil Moisture Drydowns in the ORCHIDEE Land Surface Model at In Situ Locations." Journal of Hydrometeorology 22, no. 4 (April 2021): 1025–43. http://dx.doi.org/10.1175/jhm-d-20-0115.1.
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AbstractThe rate at which land surface soils dry following rain events is an important feature of terrestrial models. It determines, for example, the water availability for vegetation, the occurrences of droughts, and the surface heat exchanges. As such, surface soil moisture (SSM) “drydowns,” i.e., the SSM temporal dynamics following a significant rainfall event, are of particular interest when evaluating and calibrating land surface models (LSMs). By investigating drydowns, characterized by an exponential decay time scale τ, we aim to improve the representation of SSM in the ORCHIDEE global LSM. We consider τ calculated over 18 International Soil Moisture Network sites found within the footprint of FLUXNET towers, covering different vegetation types and climates. Using the ORCHIDEE LSM, we compare τ from the modeled SSM time series to values computed from in situ SSM measurements. We then assess the potential of using τ observations to constrain some water, carbon, and energy parameters of ORCHIDEE, selected using a sensitivity analysis, through a standard Bayesian optimization procedure. The impact of the SSM optimization is evaluated using FLUXNET evapotranspiration and gross primary production (GPP) data. We find that the relative drydowns of SSM can be well calibrated using observation-based τ estimates, when there is no need to match the absolute observed and modeled SSM values. When evaluated using independent data, τ-calibration parameters were able to improve drydowns for 73% of the sites. Furthermore, the fit of the model to independent fluxes was only minutely changed. We conclude by considering the potential of global satellite products to scale up the experiment to a global-scale optimization.
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Risi, C., A. Landais, R. Winkler, and F. Vimeux. "Can we determine what controls the spatio-temporal distribution of d-excess and <sup>17</sup>O-excess in precipitation using the LMDZ general circulation model?" Climate of the Past 9, no. 5 (September 16, 2013): 2173–93. http://dx.doi.org/10.5194/cp-9-2173-2013.
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Abstract. Combined measurements of the H218O and HDO isotopic ratios in precipitation, leading to second-order parameter D-excess, have provided additional constraints on past climates compared to the H218O isotopic ratio alone. More recently, measurements of H217O have led to another second-order parameter: 17O-excess. Recent studies suggest that 17O-excess in polar ice may provide information on evaporative conditions at the moisture source. However, the processes controlling the spatio-temporal distribution of 17O-excess are still far from being fully understood. We use the isotopic general circulation model (GCM) LMDZ to better understand what controls d-excess and 17O-excess in precipitation at present-day (PD) and during the last glacial maximum (LGM). The simulation of D-excess and 17O-excess is evaluated against measurements in meteoric water, water vapor and polar ice cores. A set of sensitivity tests and diagnostics are used to quantify the relative effects of evaporative conditions (sea surface temperature and relative humidity), Rayleigh distillation, mixing between vapors from different origins, precipitation re-evaporation and supersaturation during condensation at low temperature. In LMDZ, simulations suggest that in the tropics convective processes and rain re-evaporation are important controls on precipitation D-excess and 17O-excess. In higher latitudes, the effect of distillation, mixing between vapors from different origins and supersaturation are the most important controls. For example, the lower d-excess and 17O-excess at LGM simulated at LGM are mainly due to the supersaturation effect. The effect of supersaturation is however very sensitive to a parameter whose tuning would require more measurements and laboratory experiments. Evaporative conditions had previously been suggested to be key controlling factors of d-excess and 17O-excess, but LMDZ underestimates their role. More generally, some shortcomings in the simulation of 17O-excess by LMDZ suggest that general circulation models are not yet the perfect tool to quantify with confidence all processes controlling 17O-excess.
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Zhao, Y., P. Ciais, P. Peylin, N. Viovy, B. Longdoz, J. M. Bonnefond, S. Rambal, et al. "How errors on meteorological variables impact simulated ecosystem fluxes: a case study for six French sites." Biogeosciences Discussions 8, no. 2 (March 9, 2011): 2467–522. http://dx.doi.org/10.5194/bgd-8-2467-2011.
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Abstract. We analyze how biases of meteorological drivers impact the calculation of ecosystem CO2, water and energy fluxes by models. To do so, we drive the same ecosystem model by meteorology from gridded products and by ''true" meteorology from local observation at eddy-covariance flux sites. The study is focused on six flux tower sites in France spanning across a 7–14 °C and 600–1040 mm yr−1 climate gradient, with forest, grassland and cropland ecosystems. We evaluate the results of the ORCHIDEE process-based model driven by four different meteorological models against the same model driven by site-observed meteorology. The evaluation is decomposed into characteristic time scales. The main result is that there are significant differences between meteorological models and local tower meteorology. The seasonal cycle of air temperature, humidity and shortwave downward radiation is reproduced correctly by all meteorological models (average R2=0.90). At sites located near the coast and influenced by sea-breeze, or located in altitude, the misfit of meteorological drivers from gridded dataproducts and tower meteorology is the largest. We show that day-to-day variations in weather are not completely well reproduced by meteorological models, with R2 between modeled grid point and measured local meteorology going from 0.35 (REMO model) to 0.70 (SAFRAN model). The bias of meteorological models impacts the flux simulation by ORCHIDEE, and thus would have an effect on regional and global budgets. The forcing error defined by the simulated flux difference resulting from prescribing modeled instead than observed local meteorology drivers to ORCHIDEE is quantified for the six studied sites and different time scales. The magnitude of this forcing error is compared to that of the model error defined as the modeled-minus-observed flux, thus containing uncertain parameterizations, parameter values, and initialization. The forcing error is the largest on a daily time scale, for which it is as large as the model error. The forcing error incurring from using gridded meteorological model to drive vegetation models is therefore an important component of the uncertainty budget of regional CO2, water and energy fluxes simulations, and should be taken into consideration in up-scaling studies.
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Dufour, G., S. Szopa, M. P. Barkley, C. D. Boone, A. Perrin, P. I. Palmer, and P. F. Bernath. "Global upper-tropospheric formaldehyde: seasonal cycles observed by the ACE-FTS satellite instrument." Atmospheric Chemistry and Physics Discussions 9, no. 1 (January 13, 2009): 1051–95. http://dx.doi.org/10.5194/acpd-9-1051-2009.
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Abstract. Seasonally-resolved upper tropospheric profiles of formaldehyde (HCHO) observed by the ACE Fourier transform spectrometer (ACE-FTS) on a near-global scale are presented for the time period from March 2004 to November 2006. Large upper tropospheric HCHO mixing ratios (>150 pptv) are observed during the growing season of the terrestrial biosphere in the Northern Hemisphere and during the biomass burning season in the Southern Hemisphere. The total errors estimated for the retrieved mixing ratios range from 30 to 40% in the upper troposphere and increase in the lower stratosphere. The sampled HCHO concentrations are in satisfactory agreement with previous aircraft and satellite observations with a negative bias (<25%) within observation errors. An overview of the seasonal cycle of the upper tropospheric HCHO is given for different latitudes. A maximum is observed during summer, i.e. during the growing season, in the northern mid- and high latitudes. The influence of biomass burning is visible in HCHO upper tropospheric concentrations during the September-to-October period in the southern tropics and subtropics. Comparisons with two state-of-the-art models (GEOS-Chem and LMDz-INCA) show that the models fail to reproduce the seasonal variations observed in the southern tropics and subtropics but they capture well the variations observed in the Northern Hemisphere (correlation >0.9). Both models underestimate the summer maximum over Europe and Russia and differences in the emissions used for North America result in a good reproduction of the summer maximum by GEOS-Chem but in an underestimate by LMDz-INCA. Globally, GEOS-Chem reproduces well the observations on average over one year but has some difficulties in reproducing the spatial variability of the observations. LMDz-INCA shows significant bias in the Southern Hemisphere, likely related to an underestimation of methane, but better reproduces the temporal and spatial variations. The differences between the models underline the large uncertainties that remain in the emissions of HCHO precursors. Observations of the HCHO upper tropospheric profile provided by the ACE-FTS represent a unique data set for investigating and improving our current understanding of the formaldehyde budget and upper tropospheric chemistry.