scholarly journals Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools and turnover in temperate forests

2017 ◽  
Author(s):  
Francesc Montané ◽  
Andrew M. Fox ◽  
Avelino F. Arellano ◽  
Natasha MacBean ◽  
M. Ross Alexander ◽  
...  
Keyword(s):  
Primary Production ◽  
Aboveground Biomass ◽  
Land Surface ◽  
Turnover Rate ◽  
Land Surface Model ◽  
Biomass Accumulation ◽  
Deciduous Forests ◽  
Surface Model ◽  
Allocation Scheme

Abstract. How carbon (C) is allocated to different plant tissues (leaves, stem and roots) determines C residence time and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and Leaf Area Index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a Land Surface Model (LSM), the Community Land Model (CLM4.5). We ran CLM for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocation schemes: i) Dynamic C allocation scheme (named "D-CLM") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual Net Primary Production (NPP). ii) An alternative dynamic C allocation scheme (named "D-Litton"), where, similar to (i) C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem and coarse roots iii–iv) Two fixed C allocation schemes, one representative of observations in evergreen (named "F-Evergreen") and the other of observations in deciduous forests (named "F-Deciduous"). D-CLM generally overestimated Gross Primary Production (GPP) and ecosystem respiration, and underestimated Net Ecosystem Exchange (NEE). In D-CLM, initial aboveground biomass in 1980 was largely overestimated (between 10527 and 12897 g Cm-2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g Cm-2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM overestimated LAI in both evergreen and deciduous sites because the leaf C-LAI relationship in the model did not match the observed leaf C-LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic Cstem/Cleaf ratios and strongly reduced the overestimation of initial aboveground biomass, and aboveground NPP for deciduous forests by D-CLM. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. That could be done by addressing some of the current model assumptions about C allocation and the associated parameter uncertainty. Our results highlight the importance of using aboveground biomass data to evaluate and constrain the C allocation scheme in the model, and in particular, the sensitivity to the stem turnover rate. Revising these will be critical to improving long-term C processes in LSMs, and improve their projections of biomass accumulation in forests.

scholarly journals Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools, and turnover in temperate forests

2017 ◽  
Vol 10 (9) ◽  
pp. 3499-3517 ◽  
Author(s):  
Francesc Montané ◽  
Andrew M. Fox ◽  
Avelino F. Arellano ◽  
Natasha MacBean ◽  
M. Ross Alexander ◽  
...  
Keyword(s):  
Primary Production ◽  
Aboveground Biomass ◽  
Land Surface ◽  
Land Surface Model ◽  
Biomass Accumulation ◽  
Deciduous Forests ◽  
Surface Model ◽  
Allocation Scheme ◽  
Tree Ring Data

Abstract. How carbon (C) is allocated to different plant tissues (leaves, stem, and roots) determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM), the Community Land Model (CLM4.5). We ran CLM4.5 for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocation schemes: i. dynamic C allocation scheme (named "D-CLM4.5") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP); ii. an alternative dynamic C allocation scheme (named "D-Litton"), where, similar to (i), C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots; iii.–iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F-Evergreen") and the other of observations in deciduous forests (named "F-Deciduous"). D-CLM4.5 generally overestimated gross primary production (GPP) and ecosystem respiration, and underestimated net ecosystem exchange (NEE). In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g C m−2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g C m−2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C–LAI relationship in the model did not match the observed leaf C–LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic Cstem ∕ Cleaf ratios and strongly reduced the overestimation of initial aboveground biomass and aboveground NPP for deciduous forests by D-CLM4.5. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. These include changing how C is allocated in fixed and dynamic schemes based on data from current forest syntheses and different parameterization of allocation schemes for different forest types. Our results highlight the utility of using measurements of aboveground biomass to evaluate and constrain the C allocation scheme in LSMs, and suggest that stem turnover is overestimated by CLM4.5 for these AmeriFlux sites. Understanding the controls of turnover will be critical to improving long-term C processes in LSMs.

scholarly journals The AquiFR hydrometeorological modelling platform as a tool for improving groundwater resource monitoring over France: evaluation over a 60-year period

2020 ◽  
Vol 24 (2) ◽  
pp. 633-654 ◽  
Author(s):  
Jean-Pierre Vergnes ◽  
Nicolas Roux ◽  
Florence Habets ◽  
Philippe Ackerer ◽  
Nadia Amraoui ◽  
...  
Keyword(s):  
Resource Management ◽  
Land Surface ◽  
Groundwater Resources ◽  
Land Surface Model ◽  
Groundwater Resource ◽  
Surface Model ◽  
Seasonal Forecasts ◽  
Resource Monitoring ◽  
Aquifer Systems

Abstract. The new AquiFR hydrometeorological modelling platform was developed to provide short-to-long-term forecasts for groundwater resource management in France. This study aims to describe and assess this new tool over a long period of 60 years. This platform gathers in a single numerical tool several hydrogeological models covering much of the French metropolitan area. A total of 11 aquifer systems are simulated through spatially distributed models using either the MARTHE (Modélisation d'Aquifères avec un maillage Rectangulaire, Transport et HydrodynamiquE; Modelling Aquifers with Rectangular cells, Transport and Hydrodynamics) groundwater modelling software programme or the EauDyssée hydrogeological platform. A total of 23 karstic systems are simulated by a lumped reservoir approach using the EROS (Ensemble de Rivières Organisés en Sous-bassins; set of rivers organized in sub-basins) software programme. AquiFR computes the groundwater level, the groundwater–surface-water exchanges and the river flows. A simulation covering a 60-year period from 1958 to 2018 is achieved in order to evaluate the performance of this platform. The 8 km resolution SAFRAN (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie) meteorological analysis provides the atmospheric variables needed by the SURFEX (SURFace EXternalisée) land surface model in order to compute surface runoff and groundwater recharge used by the hydrogeological models. The assessment is based on more than 600 piezometers and more than 300 gauging stations corresponding to simulated rivers and outlets of karstic systems. For the simulated piezometric heads, 42 % and 60 % of the absolute biases are lower than 2 and 4 m respectively. The standardized piezometric level index (SPLI) was computed to assess the ability of AquiFR to identify extreme events such as groundwater floods or droughts in the long-term simulation over a set of piezometers used for groundwater resource management. A total of 56 % of the Nash–Sutcliffe efficiency (NSE; Ef) coefficient calculations between the observed and simulated SPLI time series are greater than 0.5. The quality of the results makes it possible to consider using the platform for real-time monitoring and seasonal forecasts of groundwater resources as well as for climate change impact assessments.

Disentangling the long-term foliar 15N signal using a land surface model

2020 ◽  
Author(s):  
Silvia Caldararu ◽  
Tea Thum ◽  
Richard Nair ◽  
Sönke Zaehle
Keyword(s):  
Nutrient Limitation ◽  
Land Surface ◽  
Nitrogen Availability ◽  
Land Surface Model ◽  
Ecosystem Dynamics ◽  
Surface Model ◽  
Terrestrial Vegetation ◽  
Climate System Model ◽  
Foliar N

<p>Terrestrial vegetation growth is hypothesised to increase under elevated atmospheric CO<sub>2</sub>, a process known as the CO<sub>2</sub> fertilisation effect. However, the magnitude of this effect and its long-term sustainability remains uncertain. One of the main limitations to the CO2  fertilisation effect is nutrient limitation to plant growth, in particular nitrogen (N) in temperate and boreal ecosystems. Recent studies have suggested that decreases in observed foliar N content (N%) and δ<sup>15</sup>N indicate widespread nitrogen limitation with increasing CO<sub>2</sub>  concentrations. However, the factors driving these two variables, and especially the foliar δ<sup>15</sup>N values, are complex and can be caused by a number of processes. On one hand, if the observed trends reflect nutrient limitation, this limitation can be caused by either CO<sub>2</sub> or warming driven growth. On the other hand, it is possible that nutrient limitation does not occur to its full extent due to plant plastic responses to alleviate nutrient limitation, causing a decrease in N%, but changes in the anthropogenic N deposition 15N signal cause the observed δ<sup>15</sup>N trend. In reality, it is likely that all these factors contribute to the observed trends. To understand ecosystem dynamics it is important to disentangle the processes behind these signals which is very difficult based on observational datasets only.</p><p>We use a novel land surface model to explore the causes behind the observed trends in foliar N% and δ<sup>15</sup>N. The QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) model  has the unique capacity to track ecologically relevant isotopic composition, including <sup>15</sup>N in plant and soil pools. The model also includes a realistic representation of plant plastic acclimation processes, specifically a representation of nitrogen allocation to and inside the canopy in response to nitrogen availability, so implicitly to changes in CO<sub>2 </sub> concentrations. We test the different hypotheses above behind the observed changes in N% and δ<sup>15</sup>N separately and quantify the contribution of each of the factors towards the observed trend. We then test the different hypotheses against existing observations of N% and δ<sup>15</sup>N from the ICP Forests database and other published datasets such as the global dataset of Craine et al. 2018.</p><p>Our study showcases the use of an isotope-enabled land surface model in conjunction with long-term observations to strengthen our understanding of the ecosystem processes behind the observed trends.</p>

scholarly journals CNRD v1.0: a high-quality natural runoff dataset for hydrological and climate studies in China

2021 ◽  
pp. 1-57
Author(s):  
Jiaojiao Gou ◽  
Chiyuan Miao ◽  
Luis Samaniego ◽  
Mu Xiao ◽  
Jingwen Wu ◽  
...  
Keyword(s):  
Parameter Uncertainty ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Comprehensive Model ◽  
Analysis Framework ◽  
Model Parameter Uncertainty ◽  
Parameter Uncertainty Analysis ◽  
Climate Studies

Capsule summaryA long-term spatiotemporally continuous naturalized runoff record, CNRD v1.0, is reconstructed by using a comprehensive model parameter uncertainty analysis framework within a land-surface model.

scholarly journals Multisource Estimation of Long-Term Terrestrial Water Budget for Major Global River Basins

2012 ◽  
Vol 25 (9) ◽  
pp. 3191-3206 ◽  
Author(s):  
Ming Pan ◽  
Alok K. Sahoo ◽  
Tara J. Troy ◽  
Raghuveer K. Vinukollu ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
Water Balance ◽  
Error Analysis ◽  
Land Surface ◽  
Water Budget ◽  
Large Scale ◽  
Land Surface Model ◽  
Data Sources ◽  
Surface Model ◽  
Terrestrial Water

A systematic method is proposed to optimally combine estimates of the terrestrial water budget from different data sources and to enforce the water balance constraint using data assimilation techniques. The method is applied to create global long-term records of the terrestrial water budget by merging a number of global datasets including in situ observations, remote sensing retrievals, land surface model simulations, and global reanalyses. The estimation process has three steps. First, a conventional analysis on the errors and biases in different data sources is conducted based on existing validation/error studies and other information such as sensor network density, model physics, and calibration procedures. Then, the data merging process combines different estimates so that biases and errors from different data sources can be compensated to the greatest extent and the merged estimates have the best possible confidence. Finally, water balance errors are resolved using the constrained Kalman filter technique. The procedure is applied to 32 globally distributed major basins for 1984–2006. The authors believe that the resulting global water budget estimates can be used as a baseline dataset for large-scale diagnostic studies, for example, integrated assessment of basin water resources, trend analysis and attribution, and climate change studies. The global scale of the analysis presents significant challenges in carrying out the error analysis for each water budget variable. For some variables (e.g., evapotranspiration) the assumptions underpinning the error analysis lack supporting quantitative analysis and, thus, may not hold for specific locations. Nevertheless, the merging and water balance constraining technique can be applied to many problems.

scholarly journals ORCHIDEE-CROP (v0), a new process based Agro-Land Surface Model: model description and evaluation over Europe

2015 ◽  
Vol 8 (6) ◽  
pp. 4653-4696 ◽  
Author(s):  
X. Wu ◽  
N. Vuichard ◽  
P. Ciais ◽  
N. Viovy ◽  
N. de Noblet-Ducoudré ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Latent Heat ◽  
Aboveground Biomass ◽  
Land Surface ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Sensible Heat ◽  
Energy Fluxes ◽  
Crop Phenology

Abstract. The responses of crop functioning to changing climate and atmospheric CO2 concentration ([CO2]) could have large effects on food production, and impact carbon, water and energy fluxes, causing feedbacks to climate. To simulate the responses of temperate crops to changing climate and [CO2], accounting for the specific phenology of crops mediated by management practice, we present here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but it is tested here for maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at 7 winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO2 fluxes (NEE), latent heat and sensible heat fluxes. Additional measurements of leaf area index (LAI), aboveground biomass and yield are used as well. Evaluation results reveal that ORCHIDEE-CROP (v0) reproduces the observed timing of crop development stages and the amplitude of pertaining LAI changes in contrast to ORCHIDEEv196 in which by default crops have the same phenology than grass. A near-halving of the root mean square error of LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m2 m−2 is obtained between ORCHIDEEv196 and ORCHIDEE-CROP (v0) across the 7 study sites. Improved crop phenology and carbon allocation lead to a general good match between modelled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0–54.2 %), crop yield, as well as of the daily carbon and energy fluxes with NRMSE of ~9.0–20.1 and ~9.4–22.3 % for NEE, and sensible and latent heat fluxes, respectively. The model data mistfit for energy fluxes are within uncertainties of the measurements, which themselves show an incomplete energy balance closure within the range 80.6–86.3 %. The remaining discrepancies between modelled and observed LAI and other variables at specific sites are partly attributable to unrealistic representation of management events. In addition, ORCHIDEE-CROP (v0) is shown to have the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, sensible heat fluxes and latent heat fluxes, across the sites in Europe, an important requirement for future spatially explicit simulations. Further improvement of the model with an explicit parameterization of nutrition dynamics and of management, is expected to improve its predictive ability to simulate croplands in an Earth System Model.

scholarly journals Global Reach-level 3-hourly River Flood Reanalysis (1980-2019)

2021 ◽  
pp. 1-49
Author(s):  
Yuan Yang ◽  
Ming Pan ◽  
Peirong Lin ◽  
Hylke E. Beck ◽  
Zhenzhong Zeng ◽  
...  
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Flood Events ◽  
Spatial And Temporal Scales ◽  
Level 3 ◽  
Global Coverage ◽  
River Modeling ◽  
Global Reach

AbstractBetter understanding and quantification of river floods for very local and flashy events calls for modeling capability at fine spatial and temporal scales. However, long-term discharge records with a global coverage suitable for extreme events analysis are still lacking. Here, grounded on recent breakthroughs in global runoff hydrology, river modeling, high resolution hydrography, and climate reanalysis, we developed a 3-hourly river discharge record globally for 2.94 million river reaches during the 40-year period of 1980-2019. The underlying modeling chain consists of the VIC land surface model (0.05°, 3-hourly) that is well calibrated and bias corrected and the RAPID routing model (2.94 million river and catchment vectors), with precipitation input from MSWEP and other meteorological fields downscaled from ERA5. Flood events (above 2-year return) and their characteristics (number, spatial distribution, and seasonality) were extracted and studied. Validations against 3-hourly flow records from 6,000+ gauges in CONUS and daily records from 14,000+ gauges globally show good modeling performance across all flow ranges, good skills in reconstructing flood events (high extremes), and the benefit of (and need for) sub-daily modeling. This data record, referred as Global Reach-level Flood Reanalysis (GRFR), is publicly available at https://www.reachhydro.org/home/records/grfr.

scholarly journals A new version of the CABLE land surface model (Subversion revision r4601) incorporating land use and land cover change, woody vegetation demography, and a novel optimisation-based approach to plant coordination of photosynthesis

2018 ◽  
Vol 11 (7) ◽  
pp. 2995-3026 ◽  
Author(s):  
Vanessa Haverd ◽  
Benjamin Smith ◽  
Lars Nieradzik ◽  
Peter R. Briggs ◽  
William Woodgate ◽  
...  
Keyword(s):  
Land Use ◽  
Electron Transport ◽  
Land Surface ◽  
Secondary Forest ◽  
Land Surface Model ◽  
Biomass Accumulation ◽  
Surface Model ◽  
Interannual Variations ◽  
New Developments ◽  
Global Land

Abstract. The Community Atmosphere–Biosphere Land Exchange model (CABLE) is a land surface model (LSM) that can be applied stand-alone and provides the land surface–atmosphere exchange within the Australian Community Climate and Earth System Simulator (ACCESS). We describe new developments that extend the applicability of CABLE for regional and global carbon–climate simulations, accounting for vegetation responses to biophysical and anthropogenic forcings. A land use and land cover change module driven by gross land use transitions and wood harvest area was implemented, tailored to the needs of the Coupled Model Intercomparison Project 6 (CMIP6). Novel aspects include the treatment of secondary woody vegetation, which benefits from a tight coupling between the land use module and the Population Orders Physiology (POP) module for woody demography and disturbance-mediated landscape heterogeneity. Land use transitions and harvest associated with secondary forest tiles modify the annually resolved patch age distribution within secondary vegetated tiles, in turn affecting biomass accumulation and turnover rates and hence the magnitude of the secondary forest sink. Additionally, we implemented a novel approach to constrain modelled GPP consistent with the coordination hypothesis and predicted by evolutionary theory, which suggests that electron-transport- and Rubisco-limited rates adjust seasonally and across biomes to be co-limiting. We show that the default prior assumption – common to CABLE and other LSMs – of a fixed ratio of electron transport to carboxylation capacity at standard temperature (Jmax, 0∕Vcmax, 0) is at odds with this hypothesis; we implement an alternative algorithm for dynamic optimisation of this ratio such that coordination is achieved as an outcome of fitness maximisation. The results have significant implications for the magnitude of the simulated CO2 fertilisation effect on photosynthesis in comparison to alternative estimates and observational proxies. These new developments enhance CABLE's capability for use within an Earth system model and in stand-alone applications to attribute trends and variability in the terrestrial carbon cycle to regions, processes and drivers. Model evaluation shows that the new model version satisfies several key observational constraints: (i) trend and interannual variations in the global land carbon sink, including sensitivities of interannual variations to global precipitation and temperature anomalies; (ii) centennial trends in global GPP; (iii) coordination of Rubisco-limited and electron-transport-limited photosynthesis; (iv) spatial distributions of global ET, GPP, biomass and soil carbon; and (v) age-dependent rates of biomass accumulation in boreal, temperate and tropical secondary forests. CABLE simulations agree with recent independent assessments of the global land–atmosphere flux partition that use a combination of atmospheric inversions and bottom-up constraints. In particular, there is agreement that the strong CO2-driven sink in the tropics is largely cancelled by net deforestation and forest degradation emissions, leaving the Northern Hemisphere (NH) extratropics as the dominant contributor to the net land sink.

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