scholarly journals Carbon balance of South Asia constrained by passenger aircraft CO<sub>2</sub> measurements

2011 ◽  
Vol 11 (9) ◽  
pp. 4163-4175 ◽  
Author(s):  
P. K. Patra ◽  
Y. Niwa ◽  
T. J. Schuck ◽  
C. A. M. Brenninkmeijer ◽  
T. Machida ◽  
...  
Keyword(s):  
South Asia ◽  
Transport Model ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Ecosystem Model ◽  
Terrestrial Ecosystem Model ◽  
Terra Incognita ◽  
Ch4 And N2o ◽  
Carbon Dioxide Co2 ◽  
Passenger Aircraft

Abstract. Quantifying the fluxes of carbon dioxide (CO2) between the atmosphere and terrestrial ecosystems in all their diversity, across the continents, is important and urgent for implementing effective mitigating policies. Whereas much is known for Europe and North America for instance, in comparison, South Asia, with 1.6 billion inhabitants and considerable CO2 fluxes, remained terra incognita in this respect. We use regional measurements of atmospheric CO2 aboard a Lufthansa passenger aircraft between Frankfurt (Germany) and Chennai (India) at cruise altitude, in addition to the existing network sites for 2008, to estimate monthly fluxes for 64-regions using Bayesian inversion and transport model simulations. The applicability of the model's transport parameterization is confirmed using SF6, CH4 and N2O simulations for the CARIBIC datasets. The annual amplitude of carbon flux obtained by including the aircraft data is twice as large as the fluxes simulated by a terrestrial ecosystem model that was applied to prescribe the fluxes used in the inversions. It is shown that South Asia sequestered carbon at a rate of 0.37 ± 0.20 Pg C yr−1 (1 Pg C = 1015 g of carbon in CO2) for the years 2007 and 2008. The seasonality and the strength of the calculated monthly fluxes are successfully validated using independent measurements of vertical CO2 profiles over Delhi and spatial variations at cruising altitude over Asia aboard Japan Airlines passenger aircraft.

scholarly journals Carbon balance of South Asia constrained by passenger aircraft CO<sub>2</sub> measurements

2011 ◽  
Vol 11 (2) ◽  
pp. 5379-5405 ◽  
Author(s):  
P. K. Patra ◽  
Y. Niwa ◽  
T. J. Schuck ◽  
C. A. M. Brenninkmeijer ◽  
T. Machida ◽  
...  
Keyword(s):  
South Asia ◽  
Transport Model ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Ecosystem Model ◽  
Terrestrial Ecosystem Model ◽  
Terra Incognita ◽  
Annual Carbon ◽  
Carbon Dioxide Co2 ◽  
Passenger Aircraft

Abstract. Quantifying the fluxes of carbon dioxide (CO2) between the atmosphere and terrestrial ecosystems in all their diversity, across the continents, is important and urgent for implementing effective mitigating policies. Whereas much is known for Europe and North America for instance, in comparison, South Asia, with 1.6 billion inhabitants and considerable CO2 fluxes, remained terra incognita in this respect. We use regional measurements of atmospheric CO2 aboard a Lufthansa passenger aircraft between Frankfurt (Germany) and Chennai (India) at cruise altitude, in addition to the existing network sites for 2008, to estimate monthly fluxes for 64-regions using Bayesian inversion and transport model simulations. The applicability of the model's transport parameterization is confirmed using SF6, CH4 and N2O simulations for the CARIBIC datasets. The annual carbon flux obtained by including the aircraft data is twice as large as the fluxes simulated by a terrestrial ecosystem model that was applied to prescribe the fluxes used in the inversions. It is shown that South Asia sequestered carbon at a rate of 0.37±0.20 Pg C yr−1 (1Pg C = 1015 g of carbon in CO2) for the years 2007 and 2008. The seasonality and the strength of the calculated monthly fluxes are successfully validated using independent measurements of vertical CO2 profiles over Delhi and spatial variations at cruising altitude over Asia aboard Japan Airlines passenger aircraft.

scholarly journals Technical Note: An efficient method for accelerating the spin-up process for process-based biogeochemistry models

2018 ◽  
Author(s):  
Yang Qu ◽  
Shamil Maksyutov ◽  
Qianlai Zhuang
Keyword(s):  
Global Climate ◽  
Computing Time ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Ecosystem Model ◽  
Original Method ◽  
Technical Note ◽  
Time Saving ◽  
Spatial And Temporal Scales ◽  
Terrestrial Ecosystem Model

Abstract. To better understand the role of terrestrial ecosystems in the global carbon cycle and their feedbacks to the global climate system, process-based biogeochemistry models need to be improved with respect to model parameterization and model structure. To achieve these improvements, the spin-up time for those differential equation-based models needs to be shortened. Here, an algorithm for a fast spin-up was developed and implemented in a biogeochemistry model, the Terrestrial Ecosystem Model (TEM). With the new spin-up algorithm, we showed that the model reached a steady state in less than 10 years of computing time, while the original method requires more than 200 years on average of model run. For the test sites with five different plant function types, the new method saves over 90 % of the original spin-up time in site-level simulations. In North America simulations, average spin-up time saving for all grid cells is 85 % for either daily or monthly version of TEM. The developed spin-up method shall greatly facilitate our future quantification of carbon dynamics at fine spatial and temporal scales.

scholarly journals Reduction of Global Plant Production due to Droughts from 2001 to 2010: An Analysis with a Process-Based Global Terrestrial Ecosystem Model

2015 ◽  
Vol 19 (16) ◽  
pp. 1-21 ◽  
Author(s):  
Chang Liao ◽  
Qianlai Zhuang
Keyword(s):  
Primary Production ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Ecosystem Model ◽  
Plant Production ◽  
Model Parameters ◽  
Drought Impact ◽  
Terrestrial Ecosystem Model

Abstract Droughts dramatically affect plant production of global terrestrial ecosystems. To date, quantification of this impact remains a challenge because of the complex plant physiological and biochemical processes associated with drought. Here, this study incorporates a drought index into an existing process-based terrestrial ecosystem model to estimate the drought impact on global plant production for the period 2001–10. Global Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data products are used to constrain model parameters and verify the model algorithms. The verified model is then applied to evaluate the drought impact. The study indicates that droughts will reduce GPP by 9.8 g C m−2 month−1 during the study period. On average, drought reduces GPP by 10% globally. As a result, the global GPP decreased from 106.4 to 95.9 Pg C yr−1 while the global net primary production (NPP) decreased from 54.9 to 49.9 Pg C yr−1. This study revises the estimation of the global NPP and suggests that the future quantification of the global carbon budget of terrestrial ecosystems should take the drought impact into account.

scholarly journals Regional inversion of CO<sub>2</sub> ecosystem fluxes from atmospheric measurements: reliability of the uncertainty estimates

2013 ◽  
Vol 13 (3) ◽  
pp. 5769-5804
Author(s):  
G. Broquet ◽  
F. Chevallier ◽  
F.-M. Bréon ◽  
M. Alemanno ◽  
F. Apadula ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Transport Model ◽  
Terrestrial Ecosystem ◽  
Co2 Flux ◽  
Ecosystem Model ◽  
Theoretical Uncertainty ◽  
Atmospheric Measurements ◽  
European Continent ◽  
Terrestrial Ecosystem Model ◽  
Uncertainty Estimates

Abstract. The Bayesian framework of CO2 flux inversions permits estimates of the retrieved flux uncertainties. Here, the reliability of these theoretical estimates is studied through a comparison against the misfits between the inverted fluxes and independent measurements of the CO2 Net Ecosystem Exchange (NEE) made by the eddy covariance technique at local (few hectares) scale. Regional inversions at 0.5° resolution are applied for the western European domain where ~ 50 eddy covariance sites are operated. These inversions are conducted for a 6-yr period (2002–2007). They use a mesoscale atmospheric transport model, a prior estimate of the NEE from a terrestrial ecosystem model and rely on the variational assimilation of in situ continuous measurements of CO2 atmospheric mole fractions. The misfits averaged over monthly periods and over the whole domain, are in good agreement with the theoretical uncertainties for prior (respectively inverted) NEE, with positive chi-square tests for the variance at the 2% (respectively 20%) significance levels, despite the scale mismatch and the independence between the prior (respectively inverted) NEE and the flux measurements. The theoretical uncertainty reduction for the monthly NEE at the measurement sites is 53% while the inversion actually decreases the standard deviation of the misfits by as much as 38%. These results build confidence in the NEE estimates at the European/monthly scales and in their theoretical uncertainty from the regional inverse modeling system. However, the uncertainties at the monthly (respectively annual) scale remain larger than the amplitude of the inter-annual variability of monthly (respectively annual) fluxes, so that there is a low confidence in the inter-annual variations. The uncertainties at the monthly scale are significantly smaller than the seasonal variations. The seasonal cycle of the inverted fluxes is thus reliable. In particular, the CO2 sink period over the European continent likely ends later than represented by the ecosystem model.

scholarly journals Regional inversion of CO2 ecosystem fluxes from atmospheric measurements: reliability of the uncertainty estimates

2013 ◽  
Vol 13 (17) ◽  
pp. 9039-9056 ◽  
Author(s):  
G. Broquet ◽  
F. Chevallier ◽  
F.-M. Bréon ◽  
N. Kadygrov ◽  
M. Alemanno ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Transport Model ◽  
Terrestrial Ecosystem ◽  
Co2 Flux ◽  
Ecosystem Model ◽  
Theoretical Uncertainty ◽  
Atmospheric Measurements ◽  
European Continent ◽  
Terrestrial Ecosystem Model ◽  
Uncertainty Estimates

Abstract. The Bayesian framework of CO2 flux inversions permits estimates of the retrieved flux uncertainties. Here, the reliability of these theoretical estimates is studied through a comparison against the misfits between the inverted fluxes and independent measurements of the CO2 Net Ecosystem Exchange (NEE) made by the eddy covariance technique at local (few hectares) scale. Regional inversions at 0.5° resolution are applied for the western European domain where ~ 50 eddy covariance sites are operated. These inversions are conducted for the period 2002–2007. They use a mesoscale atmospheric transport model, a prior estimate of the NEE from a terrestrial ecosystem model and rely on the variational assimilation of in situ continuous measurements of CO2 atmospheric mole fractions. Averaged over monthly periods and over the whole domain, the misfits are in good agreement with the theoretical uncertainties for prior and inverted NEE, and pass the chi-square test for the variance at the 30% and 5% significance levels respectively, despite the scale mismatch and the independence between the prior (respectively inverted) NEE and the flux measurements. The theoretical uncertainty reduction for the monthly NEE at the measurement sites is 53% while the inversion decreases the standard deviation of the misfits by 38%. These results build confidence in the NEE estimates at the European/monthly scales and in their theoretical uncertainty from the regional inverse modelling system. However, the uncertainties at the monthly (respectively annual) scale remain larger than the amplitude of the inter-annual variability of monthly (respectively annual) fluxes, so that this study does not engender confidence in the inter-annual variations. The uncertainties at the monthly scale are significantly smaller than the seasonal variations. The seasonal cycle of the inverted fluxes is thus reliable. In particular, the CO2 sink period over the European continent likely ends later than represented by the prior ecosystem model.

scholarly journals Coupling the Canadian Terrestrial Ecosystem Model (CTEM v. 2.0) to Environment and Climate Change Canada's greenhouse gas forecast model

2017 ◽  
Author(s):  
Bakr Badawy ◽  
Saroja Polavarapu ◽  
Dylan B. A. Jones ◽  
Feng Deng ◽  
Michael Neish ◽  
...  
Keyword(s):  
Land Surface ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Terrestrial Ecosystem ◽  
Forecast Model ◽  
Ecosystem Model ◽  
Co2 Fluxes ◽  
Meteorological Forcing ◽  
Terrestrial Ecosystem Model ◽  
Atmospheric Transport Model

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 (CanESM). 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 (CRU-NCEP). 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 within the range of 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, but fall within the uncertainty bounds based on multi-inversion analyses. The coupling of CLASS-CTEM to an atmospheric transport model with carbon assimilation capabilities also provides insights into the limitations of CLASS-CTEM simulated CO2 fluxes through comparisons of simulated atmospheric CO2 with observations at selected flask stations. This capability can be used to continually assess and improve the terrestrial ecosystem modules of the CLASS-CTEM model.

scholarly journals Technical Note: An efficient method for accelerating the spin-up process for process-based biogeochemistry models

2018 ◽  
Vol 15 (13) ◽  
pp. 3967-3973 ◽  
Author(s):  
Yang Qu ◽  
Shamil Maksyutov ◽  
Qianlai Zhuang
Keyword(s):  
Global Climate ◽  
Computing Time ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Ecosystem Model ◽  
Original Method ◽  
Technical Note ◽  
Spatial And Temporal Scales ◽  
Terrestrial Ecosystem Model ◽  
Average Spin

Abstract. To better understand the role of terrestrial ecosystems in the global carbon cycle and their feedbacks to the global climate system, process-based biogeochemistry models need to be improved with respect to model parameterization and model structure. To achieve these improvements, the spin-up time for those differential equation-based models needs to be shortened. Here, an algorithm for a fast spin-up was developed by finding the exact solution of a linearized system representing the cyclo-stationary state of a model and implemented in a biogeochemistry model, the Terrestrial Ecosystem Model (TEM). With the new spin-up algorithm, we showed that the model reached a steady state in less than 10 years of computing time, while the original method requires more than 200 years on average of model run. For the test sites with five different plant functional types, the new method saves over 90 % of the original spin-up time in site-level simulations. In North American simulations, average spin-up time savings for all grid cells is 85 % for either the daily or monthly version of TEM. The developed spin-up method shall be used for future quantification of carbon dynamics at fine spatial and temporal scales.

scholarly journals Quantifying the role of moss in terrestrial ecosystem carbon dynamics in northern high latitudes

2021 ◽  
Vol 18 (23) ◽  
pp. 6245-6269
Author(s):  
Junrong Zha ◽  
Qianlai Zhuang
Keyword(s):  
21St Century ◽  
Land Surface ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Ecosystem Model ◽  
Carbon Dynamics ◽  
The Arctic ◽  
New Model ◽  
Terrestrial Ecosystem Model ◽  
Ecosystem Carbon

Abstract. Mosses are ubiquitous in northern terrestrial ecosystems, and play an important role in regional carbon, water and energy cycling. Current global land surface models that do not consider mosses may bias the quantification of regional carbon dynamics. Here we incorporate mosses as a new plant functional type into the process-based Terrestrial Ecosystem Model (TEM 5.0), to develop a new model (TEM_Moss). The new model explicitly quantifies the interactions between vascular plants and mosses and their competition for energy, water, and nutrients. Compared to the estimates using TEM 5.0, the new model estimates that the regional terrestrial soils currently store 132.7 Pg more C and will store 157.5 and 179.1 Pg more C under the RCP8.5 and RCP2.6 scenarios, respectively, by the end of the 21st century. Ensemble regional simulations forced with different parameters for the 21st century with TEM_Moss predict that the region will accumulate 161.1±142.1 Pg C under the RCP2.6 scenario and 186.7±166.1 Pg C under the RCP8.5 scenario over the century. Our study highlights the necessity of coupling moss into Earth system models to adequately quantify terrestrial carbon–climate feedbacks in the Arctic.

scholarly journals Tiling soil textures for terrestrial ecosystem modelling via clustering analysis: a case study with CLASS-CTEM (version 2.1)

2017 ◽  
Author(s):  
Joe R. Melton ◽  
Reinel Sospedra-Alfonso ◽  
Kelly E. McCusker
Keyword(s):  
Soil Texture ◽  
Land Surface ◽  
Clustering Analysis ◽  
Clustering Algorithms ◽  
Terrestrial Ecosystem ◽  
Grid Cell ◽  
Moisture Stress ◽  
Ecosystem Model ◽  
Global Scale ◽  
Terrestrial Ecosystem Model

Abstract. We investigate the application of clustering algorithms to represent sub-grid scale variability in soil texture for use in a global-scale terrestrial ecosystem model. Our model, the coupled Canadian Land Surface Scheme – Canadian Terrestrial Ecosystem Model (CLASS-CTEM), is typically implemented at a coarse spatial resolution (ca. 2.8° × 2.8°) due to its use as the land surface component of the Canadian Earth System Model (CanESM). CLASS-CTEM can, however, be run with tiling of the land surface as a means to represent sub-grid heterogeneity. We first determined that the model was sensitive to tiling of the soil textures via an idealized test case before attempting to cluster soil textures globally. To cluster a high-resolution soil texture dataset onto our coarse model grid, we use two linked algorithms (OPTICS (Ankerst et al., 1999; Daszykowski et al., 2002) and Sander et al. (2003)) to provide tiles of representative soil textures for use as CLASS-CTEM inputs. The clustering process results in, on average, about three tiles per CLASS-CTEM grid cell with most cells having four or less tiles. Results from CLASS-CTEM simulations conducted with the tiled inputs (Cluster) versus those using a simple grid-mean soil texture (Gridmean) show CLASS-CTEM, at least on a global scale, is relatively insensitive to the tiled soil textures, however differences can be large in arid or peatland regions. The Cluster simulation has generally lower soil moisture and lower overall vegetation productivity than the Gridmean simulation except in arid regions where plant productivity increases. In these dry regions, the influence of the tiling is stronger due to the general state of vegetation moisture stress which allows a single tile, whose soil texture retains more plant available water, to yield much higher productivity. Although the use of clustering analysis appears promising as a means to represent sub-grid heterogeneity, soil textures appear to be reasonably represented for global scale simulations using a simple grid-mean value.

scholarly journals Changes in carbon fluxes and pools induced by cropland expansion in South and Southeast Asia in the 20th century

2011 ◽  
Vol 8 (6) ◽  
pp. 11979-12012 ◽  
Author(s):  
B. Tao ◽  
H. Tian ◽  
G. Chen ◽  
W. Ren ◽  
C. Lu ◽  
...  
Keyword(s):  
Southeast Asia ◽  
South Asia ◽  
20Th Century ◽  
Forest Biomass ◽  
Terrestrial Ecosystems ◽  
Carbon Fluxes ◽  
Ecosystem Model ◽  
Natural Forests ◽  
Legacy Effect ◽  
South And Southeast Asia

Abstract. A process-based ecosystem model, the Dynamic Land Ecosystem Model (DLEM), was applied to evaluate the effects of cropland expansion on terrestrial carbon fluxes and pools in South and Southeast Asia in the 20th century. The results indicated that cropland expansion in both regions has resulted in a release of 18.26 Pg C into the atmosphere in the study period. Of this amount, approximately 23 % (4.19 Pg C) was released from South Asia and 77 % (14.07 Pg C) from Southeast Asia. More land area was converted to cropland but less carbon was emitted in South Asia than in Southeast Asia, where forest biomass and soil carbon are significantly higher. Carbon losses in vegetation, soil organic matter, and litter carbon pools accounted for 15.09, 2.01, and 1.60 Pg C, respectively. Significant decreases in vegetation carbon occurred across most regions of Southeast Asia due to continuous cropland expansion and depletion of natural forests. Our study also indicated that it is important to take into account the land use legacy effect when evaluating the contemporary carbon balance in terrestrial ecosystems.

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