What can we learn from European continuous atmospheric CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; measurements to quantify regional fluxes – Part 2: Sensitivity of flux accuracy to inverse setup

Carouge, C.; Rayner, P.J.W.; Peylin, P.; Bousquet, P.; Chevallier, F.; Ciais, Philippe

doi:10.5194/acp-10-3119-2010

Cited by 42 publications

(27 citation statements)

References 24 publications

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“…Similar to previous studies (Carouge et al, 2010;Schuh et al, 2009;Gerbig et al, 2006;Ahmadov et al, 2009), we find that significant aggregation of results is needed to come to robust numbers. The aggregation scale is on the order of 100 × 100 km as in previous work.…”

Section: Discussionsupporting

confidence: 66%

A comparison of different inverse carbon flux estimation approaches for application on a regional domain

Tolk¹,

Dolman²,

Meesters³

et al. 2011

Atmos. Chem. Phys.

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Abstract.We have implemented six different inverse carbon flux estimation methods in a regional carbon dioxide (CO 2 ) flux modeling system for the Netherlands. The system consists of the Regional Atmospheric Mesoscale Modeling System (RAMS) coupled to a simple carbon flux scheme which is run in a coupled fashion on relatively high resolution (10 km). Using an Ensemble Kalman filter approach we try to estimate spatiotemporal carbon exchange patterns from atmospheric CO 2 mole fractions over the Netherlands for a two week period in spring 2008. The focus of this work is the different strategies that can be employed to turn first-guess fluxes into optimal ones, which is known as a fundamental design choice that can affect the outcome of an inversion significantly.Different state-of-the-art approaches with respect to the estimation of net ecosystem exchange (NEE) are compared quantitatively: (1) where NEE is scaled by one linear multiplication factor per land-use type, (2) where the same is done for photosynthesis (GPP) and respiration (R) separately with varying assumptions for the correlation structure, (3) where we solve for those same multiplication factors but now for each grid box, and (4) where we optimize physical parameters of the underlying biosphere model for each land-use type. The pattern to be retrieved in this pseudo-data experiment is different in nearly all aspects from the first-guess fluxes, including the structure of the underlying flux model, reflecting the difference between the modeled fluxes and the fluxes in the real world. This makes our study a stringent test of the performance of these methods, which are currently widely used in carbon cycle inverse studies.Correspondence to: L. F. Tolk (lieselotte.tolk@acaciawater.com)Our results show that all methods struggle to retrieve the spatiotemporal NEE distribution, and none of them succeeds in finding accurate domain averaged NEE with correct spatial and temporal behavior. The main cause is the difference between the structures of the first-guess and true CO 2 flux models used. Most methods display overconfidence in their estimate as a result. A commonly used daytime-only sampling scheme in the transport model leads to compensating biases in separate GPP and R scaling factors that are readily visible in the nighttime mixing ratio predictions of these systems.Overall, we recommend that the estimate of NEE scaling factors should not be used in this regional setup, while estimating bias factors for GPP and R for every grid box works relatively well. The biosphere parameter inversion performs good compared to the other inversions at simultaneously producing space and time patterns of fluxes and CO 2 mixing ratios, but non-linearity may significantly reduce the information content in the inversion if true parameter values are far from the prior estimate. Our results suggest that a carefully designed biosphere model parameter inversion or a pixel inversion of the respiration and GPP multiplication factors are from the tested inversions the most prom...

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Section: Discussionsupporting

confidence: 66%

A comparison of different inverse carbon flux estimation approaches for application on a regional domain

Tolk¹,

Dolman²,

Meesters³

et al. 2011

Atmos. Chem. Phys.

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“…However, the present uncertainty in the estimates of the sinks is too large to provide independent constraints on global emissions, and uncertainty concerning atmospheric transport compounds this problem at finer regional-scale spatial resolution [9]. At the same time, uncertainty in CO 2 emissions is too large to enable early detection of unexpected feedbacks in the CO 2 sinks, if these were to occur.…”

Section: Introductionmentioning

confidence: 99%

Economic value of improved quantification in global sources and sinks of carbon dioxide

Durant

Quéré

Hope

et al. 2011

Phil. Trans. R. Soc. A.

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On average, about 45 per cent of global annual anthropogenic carbon dioxide (CO 2 ) emissions remain in the atmosphere, while the remainder are taken up by carbon reservoirs on land and in the oceans-the CO 2 'sinks'. As sink size and dynamics are highly variable in space and time, cross-verification of reported anthropogenic CO 2 emissions with atmospheric CO 2 measurements is challenging. Highly variable CO 2 sinks also limit the capability to detect anomolous changes in natural carbon reservoirs. This paper argues that significant uncertainty reduction in annual estimates of the global carbon balance could be achieved rapidly through coordinated up-scaling of existing methods, and that this uncertainty reduction would provide incentive for accurate reporting of CO 2 emissions at the country level. We estimate that if 5 per cent of global CO 2 emissions go unreported and undetected, the associated marginal economic impacts could reach approximately US$20 billion each year by 2050. The net present day value of these impacts aggregated until 2200, and discounted back to the present would have a mean value exceeding US$10 trillion. The costs of potential impacts of unreported emissions far outweigh the costs of enhancement of measurement infrastructure to reduce uncertainty in the global carbon balance.

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“…These methods have been successfully used in terrestrial systems including the City of Cape Town 11,12 , and regional and global CO 2 emissions inventories 29,30 . This method relies on high accuracy measurements of atmospheric CO 2 (or other) concentrations to constrain a priori estimates of CO 2 fluxes derived from activity and emission factor estimates.…”

Section: Marine Observationsmentioning

confidence: 99%

South African carbon observations: CO2 measurements for land, atmosphere and ocean

Feig¹,

Joubert²,

Mudau³

et al. 2017

S. Afr. J. Sci.

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What can we learn from European continuous atmospheric CO<sub>2</sub> measurements to quantify regional fluxes – Part 2: Sensitivity of flux accuracy to inverse setup

Cited by 42 publications

References 24 publications

A comparison of different inverse carbon flux estimation approaches for application on a regional domain

A comparison of different inverse carbon flux estimation approaches for application on a regional domain

Economic value of improved quantification in global sources and sinks of carbon dioxide

South African carbon observations: CO2 measurements for land, atmosphere and ocean

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