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 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 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 Simultaneous assimilation of satellite and eddy covariance data for improving terrestrial water and carbon simulations at a semi-arid woodland site in Botswana

2013 ◽  
Vol 10 (2) ◽  
pp. 789-802 ◽  
Author(s):  
T. Kato ◽  
W. Knorr ◽  
M. Scholze ◽  
E. Veenendaal ◽  
T. Kaminski ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Data Streams ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Uncertainty Reduction ◽  
Co2 Uptake ◽  
Wide Field ◽  
Hydrological Process ◽  
Terrestrial Ecosystem Model ◽  
Semi Arid

Abstract. Terrestrial productivity in semi-arid woodlands is strongly susceptible to changes in precipitation, and semi-arid woodlands constitute an important element of the global water and carbon cycles. Here, we use the Carbon Cycle Data Assimilation System (CCDAS) to investigate the key parameters controlling ecological and hydrological activities for a semi-arid savanna woodland site in Maun, Botswana. Twenty-four eco-hydrological process parameters of a terrestrial ecosystem model are optimized against two data streams separately and simultaneously: daily averaged latent heat flux (LHF) derived from eddy covariance measurements, and decadal fraction of absorbed photosynthetically active radiation (FAPAR) derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Assimilation of both data streams LHF and FAPAR for the years 2000 and 2001 leads to improved agreement between measured and simulated quantities not only for LHF and FAPAR, but also for photosynthetic CO2 uptake. The mean uncertainty reduction (relative to the prior) over all parameters is 14.9% for the simultaneous assimilation of LHF and FAPAR, 8.5% for assimilating LHF only, and 6.1% for assimilating FAPAR only. The set of parameters with the highest uncertainty reduction is similar between assimilating only FAPAR or only LHF. The highest uncertainty reduction for all three cases is found for a parameter quantifying maximum plant-available soil moisture. This indicates that not only LHF but also satellite-derived FAPAR data can be used to constrain and indirectly observe hydrological quantities.

scholarly journals Simultaneous assimilation of satellite and eddy covariance data for improving terrestrial water and carbon simulations at a semi-arid woodland site in Botswana

2012 ◽  
Vol 9 (3) ◽  
pp. 3615-3643 ◽  
Author(s):  
T. Kato ◽  
M. Scholze ◽  
W. Knorr ◽  
E. Veenendaal ◽  
T. Kaminski ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Data Stream ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Uncertainty Reduction ◽  
Co2 Uptake ◽  
Wide Field ◽  
Hydrological Process ◽  
Terrestrial Ecosystem Model ◽  
Semi Arid

Abstract. Terrestrial productivity in semi-arid woodlands is strongly susceptible to changes in precipitation, and semi-arid woodlands constitute an important element of the global water and carbon cycles. Here, we use the Carbon Cycle Data Assimilation System (CCDAS) to investigate the mechanisms controlling ecological and hydrogical activities for a semi-arid savanna woodland site in Maun, Botswana. Twenty-four eco-hydrological process parameters of a terrestrial ecosystem model are optimized against two data streams either separately or simultaneously: daily averaged latent heat flux (LHF) derived from eddy covariance measurement, and decadal fraction of absorbed photosynthetically active radiation (FAPAR) derived from Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Assimilation of both LHF and FAPAR for the years 2000 and 2001 leads to improved agreement between measured and simulated quantities not only for LHF and FAPAR, but also for photosynthetic CO2 uptake. The closest agreement is found for each observed data stream when only the same data stream is assimilated. The mean uncertainty reduction (relative to the prior) over all parameters is 16.1% for the simultaneous assimilation of LHF and FAPAR, 9.2% for assimilating LHF only, and 7.8% for assimilating FAPAR only. Furthermore, the set of parameters with the highest uncertainty reduction is similar between assimilating only FAPAR or only LHF. The highest uncertainty reduction is found for a parameter describing maximum plant-available soil moisture for all three cases. This indicates that not only LHF but also satellite-derived FAPAR data can be used to constrain and indirectly observe hydrological quantities.

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 The REFLEX project: Comparing different algorithms and implementations for the inversion of a terrestrial ecosystem model against eddy covariance data

2009 ◽  
Vol 149 (10) ◽  
pp. 1597-1615 ◽  
Author(s):  
Andrew Fox ◽  
Mathew Williams ◽  
Andrew D. Richardson ◽  
David Cameron ◽  
Jeffrey H. Gove ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Terrestrial 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 Coupling the Canadian Terrestrial Ecosystem Model (CTEM v. 2.0) to Environment and Climate Change Canada's greenhouse gas forecast model (v.107-glb)

2018 ◽  
Vol 11 (2) ◽  
pp. 631-663 ◽  
Author(s):  
Bakr Badawy ◽  
Saroja Polavarapu ◽  
Dylan B. A. Jones ◽  
Feng Deng ◽  
Michael Neish ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Land Surface ◽  
Atmospheric Transport ◽  
Terrestrial Ecosystem ◽  
Co2 Flux ◽  
Forecast Model ◽  
Ecosystem Model ◽  
Meteorological Forcing ◽  
Terrestrial Ecosystem 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 (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.

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.

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