scholarly journals Addressing Biases in Arctic-Boreal Carbon Cycling in the Community Land Model Version 5

2020 ◽  
Author(s):  
Leah Birch ◽  
Christopher R. Schwalm ◽  
Sue Natali ◽  
Danica Lombardozzi ◽  
Gretchen Keppel-Aleks ◽  
...  
Keyword(s):  
Carbon Cycling ◽  
Eddy Covariance ◽  
Land Surface ◽  
Large Scale ◽  
Carbon Allocation ◽  
Ecosystem Respiration ◽  
Terrestrial Ecosystem ◽  
The Arctic ◽  
Community Land Model ◽  
Warming World

Abstract. The Arctic-boreal zone (ABZ) is experiencing amplified warming, actively changing biogeochemical cycling of vegetation and soils. The land-to-atmosphere fluxes of CO2 in the ABZ have the potential to increase in magnitude and feedback to the climate causing additional large scale warming. The ability to model and predict this vulnerability is critical to preparation for a warming world, but Earth system models have biases that may hinder understanding the rapidly changing ABZ carbon fluxes. Here we investigate circumpolar carbon cycling represented by the Community Land Model 5 (CLM5.0) with a focus on seasonal gross primary productivity (GPP) in plant functional types (PFTs). We benchmark model results using data from satellite remote sensing products and eddy covariance towers. We find consistent biases in CLM5.0 relative to observational constraints: (1) the onset of deciduous plant productivity to be late, (2) the offset of productivity to lag and remain abnormally high for all PFTs in fall, (3) a high bias of grass, shrub, and needleleaf evergreen tree productivity, and (4) an underestimation of productivity of deciduous trees. Based on these biases, we focus model development of alternate phenology, photosynthesis schemes, and carbon allocation parameters at eddy covariance tower sites. Although our improvements are focused on productivity, our final Model Recommendation results in other component CO2 fluxes, e.g. Net Ecosystem Exchange (NEE) and Terrestrial Ecosystem Respiration (TER), that are more consistent with observations. Results suggest that algorithms developed for lower latitudes and more temperate environments can be inaccurate when extrapolated to the ABZ, and that many land surface models may not accurately represent carbon cycling and its recent rapid changes in high latitude ecosystems, especially when analyzed by individual PFTs.

scholarly journals Addressing biases in Arctic–boreal carbon cycling in the Community Land Model Version 5

2021 ◽  
Vol 14 (6) ◽  
pp. 3361-3382
Author(s):  
Leah Birch ◽  
Christopher R. Schwalm ◽  
Sue Natali ◽  
Danica Lombardozzi ◽  
Gretchen Keppel-Aleks ◽  
...  
Keyword(s):  
Carbon Cycling ◽  
Eddy Covariance ◽  
Land Surface ◽  
Large Scale ◽  
Carbon Allocation ◽  
Ecosystem Respiration ◽  
Terrestrial Ecosystem ◽  
The Arctic ◽  
Community Land Model ◽  
Warming World

Abstract. The Arctic–boreal zone (ABZ) is experiencing amplified warming, actively changing biogeochemical cycling of vegetation and soils. The land-to-atmosphere fluxes of CO2 in the ABZ have the potential to increase in magnitude and feedback to the climate causing additional large-scale warming. The ability to model and predict this vulnerability is critical to preparation for a warming world, but Earth system models have biases that may hinder understanding of the rapidly changing ABZ carbon fluxes. Here we investigate circumpolar carbon cycling represented by the Community Land Model 5 (CLM5.0) with a focus on seasonal gross primary productivity (GPP) in plant functional types (PFTs). We benchmark model results using data from satellite remote sensing products and eddy covariance towers. We find consistent biases in CLM5.0 relative to observational constraints: (1) the onset of deciduous plant productivity to be late; (2) the offset of productivity to lag and remain abnormally high for all PFTs in fall; (3) a high bias of grass, shrub, and needleleaf evergreen tree productivity; and (4) an underestimation of productivity of deciduous trees. Based on these biases, we focus on model development of alternate phenology, photosynthesis schemes, and carbon allocation parameters at eddy covariance tower sites. Although our improvements are focused on productivity, our final model recommendation results in other component CO2 fluxes, e.g., net ecosystem exchange (NEE) and terrestrial ecosystem respiration (TER), that are more consistent with observations. Results suggest that algorithms developed for lower latitudes and more temperate environments can be inaccurate when extrapolated to the ABZ, and that many land surface models may not accurately represent carbon cycling and its recent rapid changes in high-latitude ecosystems, especially when analyzed by individual PFTs.

scholarly journals Year-round simulated methane emissions from a permafrost ecosystem in Northeast Siberia

2017 ◽  
Author(s):  
Karel Castro-Morales ◽  
Thomas Kleinen ◽  
Sonja Kaiser ◽  
Sönke Zaehle ◽  
Fanny Kittler ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Land Surface ◽  
Large Scale ◽  
Molecular Diffusion ◽  
Russian Far East ◽  
Far East ◽  
Methane Emissions ◽  
The Arctic ◽  
Ch4 Emissions ◽  
Permafrost Thaw

Abstract. Methane emissions to the atmosphere from natural wetlands are estimated to be about 25 % of the total global CH4 emissions. In the Arctic, these areas are highly vulnerable to the effects of global warming due to atmospheric warming amplification, leading to soil hydrologic changes involving permafrost thaw, formation of deeper active layers, and rising topsoil temperatures. As a result, projected increase in the degradation of permafrost carbon will likely lead to higher CO2 and CH4 emissions from these areas. Here we evaluate year-round model-simulated CH4 emissions to the atmosphere (for 2014 and 2015) from a region of northeastern Siberia in the Russian Far East. Four CH4 transport pathways are modeled with a revisit-ed version of the process-based JSBACH-methane model: plant-mediated transport, ebullition and molecular diffusion in the presence or absence of snow. This model also simulates the extent of wetlands as the fraction of inundated area in a model grid cell using a TOP-MODEL approach, and these are evaluated against a highly resolved wetland product from remote sensing data. The model CH4 emissions are compared against ground-based CH4 flux measurements using the eddy covariance technique and flux chambers in the same area of study. The magnitude of the summertime modeled CH4 emissions is comparable to those from eddy covariance and flux chamber measurements. However, wintertime modeled CH4 emissions are underestimated by one order of magnitude. The annual CH4 emissions are dominated by plant-mediated transport (61 %), followed by ebullition (~ 35 %). Molecular diffusion of CH4 from the soil into the atmosphere during summer is negligible (0.02 %) compared to the diffusion through the snow during the non-growing season (~ 4 %). We investigate the relationship between temporal changes in the CH4 fluxes, soil temperature, and soil moisture content. Our results highlight the heterogeneity in CH4 emissions at a landscape scale and suggest that further improvements to the representation of large-scale hydrological conditions in the model, especially at regional scales in Arctic ecosystems influenced by permafrost thaw, will allow us to arrive at a more process-oriented land surface scheme and better simulate CH4 emissions under climate change.

scholarly journals Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: algorithms and uncertainty estimation

2006 ◽  
Vol 3 (4) ◽  
pp. 571-583 ◽  
Author(s):  
D. Papale ◽  
M. Reichstein ◽  
M. Aubinet ◽  
E. Canfora ◽  
C. Bernhofer ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Net Ecosystem Exchange ◽  
Terrestrial Ecosystem ◽  
Climatic Conditions ◽  
High Temporal Resolution ◽  
Eddy Covariance Technique ◽  
Forest Sites ◽  
European Database

Abstract. Eddy covariance technique to measure CO2, water and energy fluxes between biosphere and atmosphere is widely spread and used in various regional networks. Currently more than 250 eddy covariance sites are active around the world measuring carbon exchange at high temporal resolution for different biomes and climatic conditions. In this paper a new standardized set of corrections is introduced and the uncertainties associated with these corrections are assessed for eight different forest sites in Europe with a total of 12 yearly datasets. The uncertainties introduced on the two components GPP (Gross Primary Production) and TER (Terrestrial Ecosystem Respiration) are also discussed and a quantitative analysis presented. Through a factorial analysis we find that generally, uncertainties by different corrections are additive without interactions and that the heuristic u*-correction introduces the largest uncertainty. The results show that a standardized data processing is needed for an effective comparison across biomes and for underpinning inter-annual variability. The methodology presented in this paper has also been integrated in the European database of the eddy covariance measurements.

scholarly journals Carbon Exchange and Accumulation in an Orinoco High Plains Native Savanna Ecosystem as Measured by Eddy Covariance

2021 ◽  
Vol 9 ◽  
Author(s):  
Luis A. Morales-Rincon ◽  
Andrea J. Hernandez ◽  
Nubia S. Rodriguez-Hernandez ◽  
Rodrigo Jimenez
Keyword(s):  
Eddy Covariance ◽  
Land Surface ◽  
Net Primary Production ◽  
Carbon Sink ◽  
Ecosystem Respiration ◽  
High Plains ◽  
First Year ◽  
Drought Duration ◽  
C Cycle ◽  
The Impact

Savanna ecosystems cover ∼20% of the total land surface and account for ∼30% of the terrestrial global net primary production. They are also highly sensitive to climate change, since their carbon (C) sink capacity may decline under rising temperatures and irregular rainfall. These responses, which will define the future climate role of the savanna ecosystems, are currently not well understood. The Colombian Orinoco River basin (“Llanos”) natural savannas are being rapidly converted to agriculture. The impact of this transformation on C fluxes and accumulation is not clear. It is thus urgent to understand the Llanos natural savanna ecosystem services, including their C cycle and underlying mechanisms. Here we report and analyze 2 years of measurements of carbon dioxide fluxes from a naturally-restored (secondary) Llanos High Plains savanna ecosystem, using eddy covariance. Meteorological conditions, particularly rainfall, were quite variable during the measurement period. During the first year of measurements, the savanna was a weak carbon source (35 gC m−2), while during the second year, the system was a comparatively strong carbon sink (−273 gC m−2), despite receiving less rainfall than during the first year. As expected, the savanna net ecosystem exchange (NEE) was highly dependent on global solar radiation, soil water content, and ecosystem respiration. We found that after ∼10 days of nominal drought, i.e., with less than ∼5 mm/day of precipitation, the NEE became highly dependent on drought duration. The ecosystem reached a critical condition of low photosynthetic activity after ∼60 days of nominal drought. Based on these findings, we developed and applied a simple standard meteorology-based model that properly reproduced the observations. Our results indicate that a shift to a climate with similar total precipitation but split into extreme dry and wet seasons might eventually suppress the savanna C uptake capacity.

scholarly journals Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations

2009 ◽  
Vol 10 (6) ◽  
pp. 1534-1547 ◽  
Author(s):  
Sujay V. Kumar ◽  
Rolf H. Reichle ◽  
Randal D. Koster ◽  
Wade T. Crow ◽  
Christa D. Peters-Lidard
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Large Scale ◽  
Surface Soil ◽  
Root Zone ◽  
Regional Climate ◽  
Surface Model ◽  
Surface Soil Moisture ◽  
Community Land Model ◽  
Assimilation System

Abstract Root-zone soil moisture controls the land–atmosphere exchange of water and energy, and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root-zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments, synthetic surface soil moisture observations are assimilated into four different models [Catchment, Mosaic, Noah, and Community Land Model (CLM)] using the ensemble Kalman filter. The authors demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates that the potential of surface soil moisture assimilation to improve root-zone information is higher when the surface–root zone coupling is stronger. The experiments also suggest that (faced with unknown true subsurface physics) overestimating surface–root zone coupling in the assimilation system provides more robust skill improvements in the root zone compared with underestimating the coupling. When CLM is excluded from the analysis, the skill improvements from using models with different vertical coupling strengths are comparable for different subsurface truths. Last, the skill improvements through assimilation were found to be sensitive to the regional climate and soil types.

The calibration-free complementary relationship (CR) approach aids large-scale ET estimation

2020 ◽  
Author(s):  
Ning Ma ◽  
Jozsef Szilagyi ◽  
Yinsheng Zhang
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Eddy Covariance ◽  
Land Surface ◽  
Large Scale ◽  
Relative Bias ◽  
Dew Point ◽  
Surface Model ◽  
Complementary Relationship ◽  
Calibration Free

<p>Having recognized the limitations in spatial representativeness and/or temporal coverage of (i) current ground evapotranspiration (ET<sub>a</sub>) observations, and; (ii) land surface model (LSM) and remote sensing (RS) based ET<sub>a</sub> estimates due to uncertainties in soil and vegetation parameters, a calibration-free nonlinear complementary relationship (CR) model is employed with inputs of air and dew-point temperature, wind speed, and net radiation to estimate monthly ET<sub>a</sub> over conterminous United States during 1979–2015. Similar estimates of three land surface models (Noah, VIC, Mosaic), two reanalysis products (NCEP-II, ERA-Interim), two remote-sensing-based (GLEAM, PML) algorithms, and the spatially upscaled eddy-covariance ET<sub>a</sub> measurements of FLUXNET-MTE plus this new result from CR were validated against water-balance-derived results. We found that the CR outperforms all other methods in the multiyear mean annual HUC2-averaged ET<sub>a</sub> estimates with RMSE = 51 mm yr<sup>−1</sup>, R = 0.98, relative bias of −1 %, and NSE = 0.94, respectively. Inclusion of the GRACE data into the annual water balances for the considerably shorter 2003–2015 period does not have much effect on model performance. Besides, the CR outperforms all other models for the linear trends in annual ET rates over the HUC2 basins. Over the significantly smaller HUC6 basins where the water-balance validation is more uncertain, the CR still outperforms all other models except FLUXNET-MTE, which has the advantage of possible local ET<sub>a</sub> measurements, a benefit that clearly diminishes at the HUC2 scale.</p><p>   Because the employed CR method is calibration-free and requires only very few meteorological inputs, yet it yields superior ET performance at the regional scale, we further employed this method to develop a new 34-year (1982-2015) ET<sub>a</sub> product for China. The new Chinese ET<sub>a</sub> product was first validated against 13 eddy-covariance measurements in China, producing NSE values in the range of 0.72–0.95. On the basin scale, the modeled ET<sub>a</sub> values yielded a relative bias of 6%, and an NSE value of 0.80 in comparison with water-balance-derived evapotranspiration rates across ten major river basins in China, indicating the CR-simulated ET<sub>a</sub> rates reliable over China. Further evaluations suggest that the CR-based ET<sub>a</sub> product is more accurate than seven other mainstream ET<sub>a</sub> products. During last three decades, our new ET<sub>a</sub> product showed that annual ET<sub>a</sub> increased significantly over most parts of western and northeastern China, but decreased significantly in many regions of the North China Plain as well as in the eastern and southern coastal regions of China. This new CR-derived ET<sub>a</sub> product would benefit the community for long-term large-scale hydroclimatological studies.</p>

scholarly journals Evaluating the potential of large-scale simulations to predict carbon fluxes of terrestrial ecosystems over a European Eddy Covariance network

2014 ◽  
Vol 11 (10) ◽  
pp. 2661-2678 ◽  
Author(s):  
M. Balzarolo ◽  
S. Boussetta ◽  
G. Balsamo ◽  
A. Beljaars ◽  
F. Maignan ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Land Surface ◽  
Large Scale ◽  
Meteorological Data ◽  
Model Development ◽  
Vapour Pressure Deficit ◽  
Terrestrial Ecosystems ◽  
Carbon Fluxes ◽  
Simulation Performance ◽  
Large Scale Simulations

Abstract. This paper reports a comparison between large-scale simulations of three different land surface models (LSMs), ORCHIDEE, ISBA-A-gs and CTESSEL, forced with the same meteorological data, and compared with the carbon fluxes measured at 32 eddy covariance (EC) flux tower sites in Europe. The results show that the three simulations have the best performance for forest sites and the poorest performance for cropland and grassland sites. In addition, the three simulations have difficulties capturing the seasonality of Mediterranean and sub-tropical biomes, characterized by dry summers. This reduced simulation performance is also reflected in deficiencies in diagnosed light-use efficiency (LUE) and vapour pressure deficit (VPD) dependencies compared to observations. Shortcomings in the forcing data may also play a role. These results indicate that more research is needed on the LUE and VPD functions for Mediterranean and sub-tropical biomes. Finally, this study highlights the importance of correctly representing phenology (i.e. leaf area evolution) and management (i.e. rotation–irrigation for cropland, and grazing–harvesting for grassland) to simulate the carbon dynamics of European ecosystems and the importance of ecosystem-level observations in model development and validation.

scholarly journals Constraining a global ecosystem model with multi-site eddy-covariance data

2012 ◽  
Vol 9 (10) ◽  
pp. 3757-3776 ◽  
Author(s):  
S. Kuppel ◽  
P. Peylin ◽  
F. Chevallier ◽  
C. Bacour ◽  
F. Maignan ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Vegetation Index ◽  
Ecosystem Respiration ◽  
Terrestrial Ecosystem ◽  
Co2 Flux ◽  
Parameter Analysis ◽  
Single Site ◽  
Biogeochemical Model ◽  
Model Parameters ◽  
Area Index

Abstract. Assimilation of in situ and satellite data in mechanistic terrestrial ecosystem models helps to constrain critical model parameters and reduce uncertainties in the simulated energy, water and carbon fluxes. So far the assimilation of eddy covariance measurements from flux-tower sites has been conducted mostly for individual sites ("single-site" optimization). Here we develop a variational data assimilation system to optimize 21 parameters of the ORCHIDEE biogeochemical model, using net CO2 flux (NEE) and latent heat flux (LE) measurements from 12 temperate deciduous broadleaf forest sites. We assess the potential of the model to simulate, with a single set of inverted parameters, the carbon and water fluxes at these 12 sites. We compare the fluxes obtained from this "multi-site" (MS) optimization to those of the prior model, and of the "single-site" (SS) optimizations. The model-data fit analysis shows that the MS approach decreases the daily root-mean-square difference (RMS) to observed data by 22%, which is close to the SS optimizations (25% on average). We also show that the MS approach distinctively improves the simulation of the ecosystem respiration (Reco), and to a lesser extent the gross primary productivity (GPP), although we only assimilated net CO2 flux. A process-oriented parameter analysis indicates that the MS inversion system finds a unique combination of parameters which is not the simple average of the different SS sets of parameters. Finally, in an attempt to validate the optimized model against independent data, we observe that global-scale simulations with MS optimized parameters show an enhanced phase agreement between modeled leaf area index (LAI) and satellite-based observations of normalized difference vegetation index (NDVI).

scholarly journals Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe

2013 ◽  
Vol 6 (6) ◽  
pp. 2165-2181 ◽  
Author(s):  
J. F. Chang ◽  
N. Viovy ◽  
N. Vuichard ◽  
P. Ciais ◽  
T. Wang ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Large Scale ◽  
Management Practices ◽  
Ecosystem Respiration ◽  
Net Ecosystem Exchange ◽  
Grassland Management ◽  
Forage Yield ◽  
Model Description ◽  
Co2 Fluxes ◽  
Area Index

Abstract. This study describes how management of grasslands is included in the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland–atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (grassland management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites, equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can realistically capture the cut-induced seasonal variation in biometric variables (LAI: leaf area index; AGB: aboveground biomass) and in CO2 fluxes (GPP: gross primary productivity; TER: total ecosystem respiration; and NEE: net ecosystem exchange). However, improvements at grazing sites are only marginal in ORCHIDEE-GM due to the difficulty in accounting for continuous grazing disturbance and its induced complex animal–vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. For annual CO2 fluxes, the NEE bias and RMSE (root mean square error) in ORCHIDEE-GM are reduced by 53% and 20%, respectively, compared to ORCHIDEE. ORCHIDEE-GM is capable of modeling the net carbon balance (NBP) of managed temperate grasslands (37 ± 30 gC m−2 yr−1 (P < 0.01) over the 11 sites) because the management module contains provisions to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

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