The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Vivek K Arora - One of the best experts on this subject based on the ideXlab platform.
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classic v1 0 the open source community successor to the canadian land surface scheme class and the canadian Terrestrial Ecosystem model ctem part 1 model framework and site level performance
Geoscientific Model Development, 2020Co-Authors: Joe R Melton, Vivek K Arora, Eduard Wisernigcojoc, Matthew Fortier, Ed Chan, Christian Seiler, Lina TeckentrupAbstract:Abstract. Recent reports by the Global Carbon Project highlight large uncertainties around land surface processes such as land use change, strength of CO2 fertilization, nutrient limitation and supply, and response to variability in climate. Process-based land surface models are well suited to address these complex and emerging global change problems but will require extensive development and evaluation. The coupled Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model (CLASS-CTEM) framework has been under continuous development by Environment and Climate Change Canada since 1987. As the open-source model of code development has revolutionized the software industry, scientific software is experiencing a similar evolution. Given the scale of the challenge facing land surface modellers, and the benefits of open-source, or community model, development, we have transitioned CLASS-CTEM from an internally developed model to an open-source community model, which we call the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC) v.1.0. CLASSIC contains many technical features specifically designed to encourage community use including software containerization for serial and parallel simulations, extensive benchmarking software and data (Automated Model Benchmarking; AMBER), self-documenting code, community standard formats for model inputs and outputs, amongst others. Here, we evaluate and benchmark CLASSIC against 31 FLUXNET sites where the model has been tailored to the site-level conditions and driven with observed meteorology. Future versions of CLASSIC will be developed using AMBER and these initial benchmark results to evaluate model performance over time. CLASSIC remains under active development and the code, site-level benchmarking data, software container, and AMBER are freely available for community use.
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coupling the canadian Terrestrial Ecosystem model ctem v 2 0 to environment and climate change canada s greenhouse gas forecast model v 107 glb
Geoscientific Model Development, 2017Co-Authors: Bakr Badawy, Joe R Melton, Saroja Polavarapu, Dylan B A Jones, Feng Deng, Michael Neish, Ray Nassar, Vivek K AroraAbstract:Abstract. The Canadian Land Surface Scheme and the Canadian Terrestrial Ecosystem Model (CLASS-CTEM) together form the land surface component in the family of Canadian Earth system models (CanESMs). Here, CLASS-CTEM is coupled to Environment and Climate Change Canada (ECCC)'s weather and greenhouse gas forecast model (GEM-MACH-GHG) to consistently model atmosphere–land exchange of CO2 . The coupling between the land and the atmospheric transport model ensures consistency between meteorological forcing of CO2 fluxes and CO2 transport. The procedure used to spin up carbon pools for CLASS-CTEM for multi-decadal simulations needed to be significantly altered to deal with the limited availability of consistent meteorological information from a constantly changing operational environment in the GEM-MACH-GHG model. Despite the limitations in the spin-up procedure, the simulated fluxes obtained by driving the CLASS-CTEM model with meteorological forcing from GEM-MACH-GHG were comparable to those obtained from CLASS-CTEM when it is driven with standard meteorological forcing from the Climate Research Unit (CRU) combined with reanalysis fields from the National Centers for Environmental Prediction (NCEP) to form CRU-NCEP dataset. This is due to the similarity of the two meteorological datasets in terms of temperature and radiation. However, notable discrepancies in the seasonal variation and spatial patterns of precipitation estimates, especially in the tropics, were reflected in the estimated carbon fluxes, as they significantly affected the magnitude of the vegetation productivity and, to a lesser extent, the seasonal variations in carbon fluxes. Nevertheless, the simulated fluxes based on the meteorological forcing from the GEM-MACH-GHG model are consistent to some extent with other estimates from bottom-up or top-down approaches. Indeed, when simulated fluxes obtained by driving the CLASS-CTEM model with meteorological data from the GEM-MACH-GHG model are used as prior estimates for an atmospheric CO2 inversion analysis using the adjoint of the GEOS-Chem model, the retrieved CO2 flux estimates are comparable to those obtained from other systems in terms of the global budget and the total flux estimates for the northern extratropical regions, which have good observational coverage. In data-poor regions, as expected, differences in the retrieved fluxes due to the prior fluxes become apparent. Coupling CLASS-CTEM into the Environment Canada Carbon Assimilation System (EC-CAS) is considered an important step toward understanding how meteorological uncertainties affect both CO2 flux estimates and modeled atmospheric transport. Ultimately, such an approach will provide more direct feedback to the CLASS-CTEM developers and thus help to improve the performance of CLASS-CTEM by identifying the model limitations based on atmospheric constraints.
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fire as an interactive component of dynamic vegetation models
Journal of Geophysical Research, 2005Co-Authors: Vivek K Arora, G J BoerAbstract:[1] Fire affects Ecosystems by altering both their structure and the cycling of carbon and nutrients. The emissions from fires represent an important biogeochemical pathway by which the biosphere affects climate. For climate change studies it is important to model fire as a mechanistic climate-dependent process in dynamic global vegetation models (DGVMs) and the Terrestrial Ecosystem components of climate models. We expand on those current approaches which neglect disturbance by fire, which use constant specified loss rates, or which depend on simple empirical relationships, and develop a process-based fire parameterization for use in the Terrestrial Ecosystem components of climate and Earth system models. The approach is straightforward and general enough to apply globally and for current and future climates. All three aspects of the fire triangle, fuel availability, the readiness of fuel to burn depending on conditions, and the presence of an ignition source, are taken into account. The approach also represents some anthropogenic effects on natural fire regimes, albeit in a simple manner. The fire parameterization is incorporated in the Canadian Terrestrial Ecosystem Model (CTEM) which simulates net primary productivity, leaf area index, and vegetation biomass. The fire parameterization generates burned area, alters vegetation biomass, and generates CO2 emissions. The parameterization is tested by comparing simulated fire return intervals and CO2 emissions with observation-based estimates for tropical savanna, tropical humid forests, mediterranean, and boreal forest locations.
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a parameterization of leaf phenology for the Terrestrial Ecosystem component of climate models
Global Change Biology, 2005Co-Authors: Vivek K Arora, G J BoerAbstract:Leaf phenology remains one of the most difficult processes to parameterize in Terrestrial Ecosystem models because our understanding of the physical processes that initiate leaf onset and senescence is incomplete. While progress has been made at the molecular level, for example by identifying genes that are associated with senescence and flowering for selected plant species, a picture of the processes controlling leaf phenology is only beginning to emerge. A variety of empirical formulations have been used with varying degrees of success in Terrestrial Ecosystem models for both extratropical and tropical biomes. For instance, the use of growing degree-days (GDDs) to initiate leaf onset has received considerable recognition and this approach is used in a number of models. There are, however, limitations when using GDDs and other empirically based formulations in global transient climate change simulations. The phenology scheme developed for the Canadian Terrestrial Ecosystem Model (CTEM), designed for inclusion in the Canadian Centre for Climate Modelling and Analysis coupled general circulation model, is described. The representation of leaf phenology is general enough to be applied over the globe and sufficiently robust for use in transient climate change simulations. Leaf phenology is functionally related to the (possibly changing) climate state and to atmospheric composition rather than to geographical boundaries or controls implicitly based on current climate. In this approach, phenology is controlled by environmental conditions as they affect the carbon balance. A carbon-gain-based scheme initiates leaf onset when it is beneficial for the plant, in carbon terms, to produce new leaves. Leaf offset is initiated by unfavourable environmental conditions that incur carbon losses and these include shorter day length, cooler temperatures, and dry soil moisture conditions. The comparison of simulated leaf onset and offset times with observation-based estimates for temperate and boreal deciduous, tropical evergreen, and tropical deciduous plant functional types at selected locations indicates that the phenology scheme performs satisfactorily. Model simulated leaf area index and stem and root biomass are also compared with observational estimates to illustrate the performance of CTEM.
Joe R Melton - One of the best experts on this subject based on the ideXlab platform.
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classic v1 0 the open source community successor to the canadian land surface scheme class and the canadian Terrestrial Ecosystem model ctem part 1 model framework and site level performance
Geoscientific Model Development, 2020Co-Authors: Joe R Melton, Vivek K Arora, Eduard Wisernigcojoc, Matthew Fortier, Ed Chan, Christian Seiler, Lina TeckentrupAbstract:Abstract. Recent reports by the Global Carbon Project highlight large uncertainties around land surface processes such as land use change, strength of CO2 fertilization, nutrient limitation and supply, and response to variability in climate. Process-based land surface models are well suited to address these complex and emerging global change problems but will require extensive development and evaluation. The coupled Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model (CLASS-CTEM) framework has been under continuous development by Environment and Climate Change Canada since 1987. As the open-source model of code development has revolutionized the software industry, scientific software is experiencing a similar evolution. Given the scale of the challenge facing land surface modellers, and the benefits of open-source, or community model, development, we have transitioned CLASS-CTEM from an internally developed model to an open-source community model, which we call the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC) v.1.0. CLASSIC contains many technical features specifically designed to encourage community use including software containerization for serial and parallel simulations, extensive benchmarking software and data (Automated Model Benchmarking; AMBER), self-documenting code, community standard formats for model inputs and outputs, amongst others. Here, we evaluate and benchmark CLASSIC against 31 FLUXNET sites where the model has been tailored to the site-level conditions and driven with observed meteorology. Future versions of CLASSIC will be developed using AMBER and these initial benchmark results to evaluate model performance over time. CLASSIC remains under active development and the code, site-level benchmarking data, software container, and AMBER are freely available for community use.
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coupling the canadian Terrestrial Ecosystem model ctem v 2 0 to environment and climate change canada s greenhouse gas forecast model v 107 glb
Geoscientific Model Development, 2017Co-Authors: Bakr Badawy, Joe R Melton, Saroja Polavarapu, Dylan B A Jones, Feng Deng, Michael Neish, Ray Nassar, Vivek K AroraAbstract:Abstract. The Canadian Land Surface Scheme and the Canadian Terrestrial Ecosystem Model (CLASS-CTEM) together form the land surface component in the family of Canadian Earth system models (CanESMs). Here, CLASS-CTEM is coupled to Environment and Climate Change Canada (ECCC)'s weather and greenhouse gas forecast model (GEM-MACH-GHG) to consistently model atmosphere–land exchange of CO2 . The coupling between the land and the atmospheric transport model ensures consistency between meteorological forcing of CO2 fluxes and CO2 transport. The procedure used to spin up carbon pools for CLASS-CTEM for multi-decadal simulations needed to be significantly altered to deal with the limited availability of consistent meteorological information from a constantly changing operational environment in the GEM-MACH-GHG model. Despite the limitations in the spin-up procedure, the simulated fluxes obtained by driving the CLASS-CTEM model with meteorological forcing from GEM-MACH-GHG were comparable to those obtained from CLASS-CTEM when it is driven with standard meteorological forcing from the Climate Research Unit (CRU) combined with reanalysis fields from the National Centers for Environmental Prediction (NCEP) to form CRU-NCEP dataset. This is due to the similarity of the two meteorological datasets in terms of temperature and radiation. However, notable discrepancies in the seasonal variation and spatial patterns of precipitation estimates, especially in the tropics, were reflected in the estimated carbon fluxes, as they significantly affected the magnitude of the vegetation productivity and, to a lesser extent, the seasonal variations in carbon fluxes. Nevertheless, the simulated fluxes based on the meteorological forcing from the GEM-MACH-GHG model are consistent to some extent with other estimates from bottom-up or top-down approaches. Indeed, when simulated fluxes obtained by driving the CLASS-CTEM model with meteorological data from the GEM-MACH-GHG model are used as prior estimates for an atmospheric CO2 inversion analysis using the adjoint of the GEOS-Chem model, the retrieved CO2 flux estimates are comparable to those obtained from other systems in terms of the global budget and the total flux estimates for the northern extratropical regions, which have good observational coverage. In data-poor regions, as expected, differences in the retrieved fluxes due to the prior fluxes become apparent. Coupling CLASS-CTEM into the Environment Canada Carbon Assimilation System (EC-CAS) is considered an important step toward understanding how meteorological uncertainties affect both CO2 flux estimates and modeled atmospheric transport. Ultimately, such an approach will provide more direct feedback to the CLASS-CTEM developers and thus help to improve the performance of CLASS-CTEM by identifying the model limitations based on atmospheric constraints.
Lina Teckentrup - One of the best experts on this subject based on the ideXlab platform.
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classic v1 0 the open source community successor to the canadian land surface scheme class and the canadian Terrestrial Ecosystem model ctem part 1 model framework and site level performance
Geoscientific Model Development, 2020Co-Authors: Joe R Melton, Vivek K Arora, Eduard Wisernigcojoc, Matthew Fortier, Ed Chan, Christian Seiler, Lina TeckentrupAbstract:Abstract. Recent reports by the Global Carbon Project highlight large uncertainties around land surface processes such as land use change, strength of CO2 fertilization, nutrient limitation and supply, and response to variability in climate. Process-based land surface models are well suited to address these complex and emerging global change problems but will require extensive development and evaluation. The coupled Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model (CLASS-CTEM) framework has been under continuous development by Environment and Climate Change Canada since 1987. As the open-source model of code development has revolutionized the software industry, scientific software is experiencing a similar evolution. Given the scale of the challenge facing land surface modellers, and the benefits of open-source, or community model, development, we have transitioned CLASS-CTEM from an internally developed model to an open-source community model, which we call the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC) v.1.0. CLASSIC contains many technical features specifically designed to encourage community use including software containerization for serial and parallel simulations, extensive benchmarking software and data (Automated Model Benchmarking; AMBER), self-documenting code, community standard formats for model inputs and outputs, amongst others. Here, we evaluate and benchmark CLASSIC against 31 FLUXNET sites where the model has been tailored to the site-level conditions and driven with observed meteorology. Future versions of CLASSIC will be developed using AMBER and these initial benchmark results to evaluate model performance over time. CLASSIC remains under active development and the code, site-level benchmarking data, software container, and AMBER are freely available for community use.
Shushi Peng - One of the best experts on this subject based on the ideXlab platform.
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Recent Changes in Global Photosynthesis and Terrestrial Ecosystem Respiration Constrained From Multiple Observations
Geophysical Research Letters, 2018Co-Authors: Philippe Ciais, Yilong Wang, Yi Yin, Shushi Peng, Zaichun Zhu, Ana Bastos, Chao Yue, Ashley Ballantyne, Grégoire Broquet, Josep CanadellAbstract:To assess global carbon cycle variability, we decompose the net land carbon sink into the sum of gross primary productivity (GPP), Terrestrial Ecosystem respiration (TER), and fire emissions and apply a Bayesian framework to constrain these fluxes between 1980 and 2014. The constrained GPP and TER fluxes show an increasing trend of only half of the prior trend simulated by models. From the optimization, we infer that TER increased in parallel with GPP from 1980 to 1990, but then stalled during the cooler periods, in 1990-1994 coincident with the Pinatubo eruption, and during the recent warming hiatus period. After each of these TER stalling periods, TER is found to increase faster than GPP, explaining a relative reduction of the net land sink. These results shed light on decadal variations of GPP and TER and suggest that they exhibit different responses to temperature anomalies over the last 35 years.
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Terrestrial Ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region
Journal of Geophysical Research, 2017Co-Authors: Jianyang Xia, David A Mcguire, David M Lawrence, Eleanor J Burke, Guangsheng Chen, Xiaodong Chen, Christine Delire, Charles D Koven, Andrew H Macdougall, Shushi PengAbstract:Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 Terrestrial Ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m
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seasonal responses of Terrestrial Ecosystem water use efficiency to climate change
Global Change Biology, 2016Co-Authors: Mengtian Huang, Philippe Ciais, Shushi Peng, Shilong Piao, Zhenzhong Zeng, Lei Cheng, Jiafu Mao, Benjamin PoulterAbstract:Ecosystem water-use efficiency (EWUE) is an indicator of carbon-water interactions and is defined as the ratio of carbon assimilation (GPP) to evapotranspiration (ET). Previous research suggests an increasing long-term trend in annual EWUE over many regions and is largely attributed to the physiological effects of rising CO2. The seasonal trends in EWUE, however, have not yet been analyzed. In this study, we investigate seasonal EWUE trends and responses to various drivers during 1982-2008. The seasonal cycle for two variants of EWUE, water-use efficiency (WUE, GPP/ET), and transpiration-based WUE (WUEt, the ratio of GPP and transpiration), is analyzed from 0.5 degrees gridded fields from four process-based models and satellite-based products, as well as a network of 63 local flux tower observations. WUE derived from flux tower observations shows moderate seasonal variation for most latitude bands, which is in agreement with satellite-based products. In contrast, the seasonal EWUE trends are not well captured by the same satellite-based products. Trend analysis, based on process-model factorial simulations separating effects of climate, CO2, and nitrogen deposition (NDEP), further suggests that the seasonal EWUE trends are mainly associated with seasonal trends of climate, whereas CO2 and NDEP do not show obvious seasonal difference in EWUE trends. About 66% grid cells show positive annual WUE trends, mainly over mid-and high northern latitudes. In these regions, spring climate change has amplified the effect of CO2 in increasing WUE by more than 0.005 gC m(-2) mm(-1) yr(-1) for 41% pixels. Multiple regression analysis further shows that the increase in springtime WUE in the northern hemisphere is the result of GPP increasing faster than ET because of the higher temperature sensitivity of GPP relative to ET. The partitioning of annual EWUE to seasonal components provides new insight into the relative sensitivities of GPP and ET to climate, CO2, and NDEP.
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benchmarking the seasonal cycle of co2 fluxes simulated by Terrestrial Ecosystem models
Global Biogeochemical Cycles, 2015Co-Authors: Shushi Peng, Philippe Ciais, Frederic Chevallier, Philippe Peylin, P Cadule, Stephen Sitch, Shilong Piao, Anders Ahlstrom, Chris HuntingfordAbstract:We evaluated the seasonality of CO2 fluxes simulated by nine Terrestrial Ecosystem models of the TRENDY project against (1) the seasonal cycle of gross primary production (GPP) and net Ecosystem exchange (NEE) measured at flux tower sites over different biomes, (2) gridded monthly Model Tree Ensembles-estimated GPP (MTE-GPP) and MTE-NEE obtained by interpolating many flux tower measurements with a machine-learning algorithm, (3) atmospheric CO2 mole fraction measurements at surface sites, and (4) CO2 total columns (XCO2) measurements from the Total Carbon Column Observing Network (TCCON). For comparison with atmospheric CO2 measurements, the LMDZ4 transport model was run with time-varying CO2 fluxes of each model as surface boundary conditions. Seven out of the nine models overestimate the seasonal amplitude of GPP and produce a too early start in spring at most flux sites. Despite their positive bias for GPP, the nine models underestimate NEE at most flux sites and in the Northern Hemisphere compared with MTE-NEE. Comparison with surface atmospheric CO2 measurements confirms that most models underestimate the seasonal amplitude of NEE in the Northern Hemisphere (except CLM4C and SDGVM). Comparison with TCCON data also shows that the seasonal amplitude of XCO2 is underestimated by more than 10% for seven out of the nine models (except for CLM4C and SDGVM) and that the MTE-NEE product is closer to the TCCON data using LMDZ4. From CO2 columns measured routinely at 10 TCCON sites, the constrained amplitude of NEE over the Northern Hemisphere is of 1.6 ± 0.4 gC m−2 d−1, which translates into a net CO2 uptake during the carbon uptake period in the Northern Hemisphere of 7.9 ± 2.0 PgC yr−1.
Shilong Piao - One of the best experts on this subject based on the ideXlab platform.
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accelerated Terrestrial Ecosystem carbon turnover and its drivers
Global Change Biology, 2020Co-Authors: Philippe Ciais, Shilong Piao, Dan Zhu, Xuhui Wang, Ana BastosAbstract:The Terrestrial carbon cycle has been strongly influenced by human-induced CO2 increase, climate change, and land use change since the industrial revolution. These changes alter the carbon balance of Ecosystems through changes in vegetation productivity and Ecosystem carbon turnover time (τeco ). Even though numerous studies have drawn an increasingly clear picture of global vegetation productivity changes, global changes in τeco are still unknown. In this study, we analyzed the changes of τeco between the 1860s and the 2000s and their drivers, based on theory of dynamic carbon cycle in non-steady state and process-based Ecosystem model. Results indicate that τeco has been reduced (i.e., carbon turnover has accelerated) by 13.5% from the 1860s (74 years) to the 2000s (64 years), with reductions of 1 year of carbon residence times in vegetation (rveg ) and of 9 years in soil (rsoil ). Additionally, the acceleration of τeco was examined at biome scale and grid scale. Among different driving processes, land use change and climate change were found to be the major drivers of turnover acceleration. These findings imply that carbon fixed by plant photosynthesis is being lost from Ecosystems to the atmosphere more quickly over time, with important implications for the climate-carbon cycle feedbacks.
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seasonal responses of Terrestrial Ecosystem water use efficiency to climate change
Global Change Biology, 2016Co-Authors: Mengtian Huang, Philippe Ciais, Shushi Peng, Shilong Piao, Zhenzhong Zeng, Lei Cheng, Jiafu Mao, Benjamin PoulterAbstract:Ecosystem water-use efficiency (EWUE) is an indicator of carbon-water interactions and is defined as the ratio of carbon assimilation (GPP) to evapotranspiration (ET). Previous research suggests an increasing long-term trend in annual EWUE over many regions and is largely attributed to the physiological effects of rising CO2. The seasonal trends in EWUE, however, have not yet been analyzed. In this study, we investigate seasonal EWUE trends and responses to various drivers during 1982-2008. The seasonal cycle for two variants of EWUE, water-use efficiency (WUE, GPP/ET), and transpiration-based WUE (WUEt, the ratio of GPP and transpiration), is analyzed from 0.5 degrees gridded fields from four process-based models and satellite-based products, as well as a network of 63 local flux tower observations. WUE derived from flux tower observations shows moderate seasonal variation for most latitude bands, which is in agreement with satellite-based products. In contrast, the seasonal EWUE trends are not well captured by the same satellite-based products. Trend analysis, based on process-model factorial simulations separating effects of climate, CO2, and nitrogen deposition (NDEP), further suggests that the seasonal EWUE trends are mainly associated with seasonal trends of climate, whereas CO2 and NDEP do not show obvious seasonal difference in EWUE trends. About 66% grid cells show positive annual WUE trends, mainly over mid-and high northern latitudes. In these regions, spring climate change has amplified the effect of CO2 in increasing WUE by more than 0.005 gC m(-2) mm(-1) yr(-1) for 41% pixels. Multiple regression analysis further shows that the increase in springtime WUE in the northern hemisphere is the result of GPP increasing faster than ET because of the higher temperature sensitivity of GPP relative to ET. The partitioning of annual EWUE to seasonal components provides new insight into the relative sensitivities of GPP and ET to climate, CO2, and NDEP.
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change in Terrestrial Ecosystem water use efficiency over the last three decades
Global Change Biology, 2015Co-Authors: Mengtian Huang, Philippe Ciais, Shilong Piao, Lei Cheng, Jiafu Mao, Benjamin Poulter, Yan Sun, Xiaoying Shi, Zhenzhong ZengAbstract:National Natural Science Foundation of China (41125004); Chinese Ministry of Environmental Protection Grant (201209031); the 111 Project (B14001);US Department of Energy (DOE), Office of Science, Biological, + Environmental Research; DOE DE-AC05-00OR22725
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benchmarking the seasonal cycle of co2 fluxes simulated by Terrestrial Ecosystem models
Global Biogeochemical Cycles, 2015Co-Authors: Shushi Peng, Philippe Ciais, Frederic Chevallier, Philippe Peylin, P Cadule, Stephen Sitch, Shilong Piao, Anders Ahlstrom, Chris HuntingfordAbstract:We evaluated the seasonality of CO2 fluxes simulated by nine Terrestrial Ecosystem models of the TRENDY project against (1) the seasonal cycle of gross primary production (GPP) and net Ecosystem exchange (NEE) measured at flux tower sites over different biomes, (2) gridded monthly Model Tree Ensembles-estimated GPP (MTE-GPP) and MTE-NEE obtained by interpolating many flux tower measurements with a machine-learning algorithm, (3) atmospheric CO2 mole fraction measurements at surface sites, and (4) CO2 total columns (XCO2) measurements from the Total Carbon Column Observing Network (TCCON). For comparison with atmospheric CO2 measurements, the LMDZ4 transport model was run with time-varying CO2 fluxes of each model as surface boundary conditions. Seven out of the nine models overestimate the seasonal amplitude of GPP and produce a too early start in spring at most flux sites. Despite their positive bias for GPP, the nine models underestimate NEE at most flux sites and in the Northern Hemisphere compared with MTE-NEE. Comparison with surface atmospheric CO2 measurements confirms that most models underestimate the seasonal amplitude of NEE in the Northern Hemisphere (except CLM4C and SDGVM). Comparison with TCCON data also shows that the seasonal amplitude of XCO2 is underestimated by more than 10% for seven out of the nine models (except for CLM4C and SDGVM) and that the MTE-NEE product is closer to the TCCON data using LMDZ4. From CO2 columns measured routinely at 10 TCCON sites, the constrained amplitude of NEE over the Northern Hemisphere is of 1.6 ± 0.4 gC m−2 d−1, which translates into a net CO2 uptake during the carbon uptake period in the Northern Hemisphere of 7.9 ± 2.0 PgC yr−1.
