A two-step scheme for high-resolution regional atmospheric trace gas inversions based on independent models

Rödenbeck, Christian; Gerbig, Christoph; Trusilova, Kristina; Heimann, Martin

doi:10.5194/acp-9-5331-2009

Cited by 78 publications

(105 citation statements)

References 18 publications

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“…sensitivities of atmospheric concentrations to surface emissions) of the individual aircraft profiles should be taken into account in the future. Furthermore, it would be useful to calculate, for all global models individually, the background mole fractions using the scheme of Rödenbeck et al (2009). This would allow the modelled CH 4 enhancements to be derived more accurately.…”

Section: Evaluation Of Inverse Modelsmentioning

confidence: 99%

“…Global inverse models are widely used to estimate emissions of CH 4 at global/continental scale, using mainly high-accuracy surface measurements at remote stations (e.g. Bergamaschi et al, 2013;Bousquet et al, 2006;Mikaloff Fletcher et al, 2004a, b;Saunois et al, 2016). In addition, satellite retrievals of GHGs have also been used in a number of studies.…”

Section: Introductionmentioning

confidence: 99%

“…While the global net balance (global sources minus global sinks) of CH 4 is well defined by the atmospheric measurements of in situ CH 4 mole fractions at global background stations, the attribution of the observed spatial and temporal variability to specific sources and regions remains very challenging (Houweling et al, 2017;Kirschke et al, 2013;Saunois et al, 2016). Global inverse models are widely used to estimate emissions of CH 4 at global/continental scale, using mainly high-accuracy surface measurements at remote stations (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Inverse modelling of European CH<sub>4</sub> emissions during 2006–2012 using different inverse models and reassessed atmospheric observations

et al. 2018

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Abstract. We present inverse modelling (top down) estimates of European methane (CH 4 The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH 4 emissions with maxima in summer, while anthropogenic CH 4 emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain.Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH 4 compared to the background, integrated over the entire boundary layer and over the lower troposphere. The estimated average regional biases range between −40 and 20 % at the aircraft profile sites in France, Hungary and Poland.

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Section: Evaluation Of Inverse Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Inverse modelling of European CH<sub>4</sub> emissions during 2006–2012 using different inverse models and reassessed atmospheric observations

et al. 2018

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“…Kim et al (2011 derived 12 climatological average monthly (spatially uniform) coefficients for wetland emissions to optimize atmospheric CH 4 concentrations over the WSL relative to observed CH 4 concentrations obtained by aircraft sampling at two locations in the WSL. Winderlich (2012) used the Kaplan (2002) wetland inventory for prior wetland emissions, within the global inversion system TM3-STILT (Rödenbeck et al, 2009;Trusilova et al, 2010) The other inversions we considered were global: the "Reference" and "Kaplan" versions of the inversion, denoted by "Bousquet2011R" and "Bousquet2011K", respectively, and the estimate of Bloom et al (2010), denoted by "Bloom2010". Matthews and Fung (1987) emissions inventory was the prior for wetland emissions in the Bousquet2011R inversion, while the Kaplan (2002) emissions were the prior for the Bousquet2011K inversion.…”

Section: -2009mentioning

confidence: 99%

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

et al. 2015

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Abstract. Wetlands are the world's largest natural source of methane, a powerful greenhouse gas. The strong sensitivity of methane emissions to environmental factors such as soil temperature and moisture has led to concerns about potential positive feedbacks to climate change. This risk is particularly relevant at high latitudes, which have experienced pronounced warming and where thawing permafrost could potentially liberate large amounts of labile carbon over the next 100 years. However, global models disagree as to the magnitude and spatial distribution of emissions, due to uncertainties in wetland area and emissions per unit area and a scarcity of in situ observations. Recent intensive field campaigns across the West Siberian Lowland (WSL) make this an ideal region over which to assess the perPublished by Copernicus Publications on behalf of the European Geosciences Union. T. J. Bohn et al.: Intercomparison of wetland methane emissions modelsformance of large-scale process-based wetland models in a high-latitude environment. Here we present the results of a follow-up to the Wetland and Wetland CH 4 Intercomparison of Models Project (WETCHIMP), focused on the West Siberian Lowland (WETCHIMP-WSL). We assessed 21 models and 5 inversions over this domain in terms of total CH 4 emissions, simulated wetland areas, and CH 4 fluxes per unit wetland area and compared these results to an intensive in situ CH 4 flux data set, several wetland maps, and two satellite surface water products. We found that (a) despite the large scatter of individual estimates, 12-year mean estimates of annual total emissions over the WSL from forward models (5.34 ± 0.54 Tg CH 4 yr −1 ), inversions (6.06 ± 1.22 Tg CH 4 yr −1 ), and in situ observations (3.91 ± 1.29 Tg CH 4 yr −1 ) largely agreed; (b) forward models using surface water products alone to estimate wetland areas suffered from severe biases in CH 4 emissions; (c) the interannual time series of models that lacked either soil thermal physics appropriate to the high latitudes or realistic emissions from unsaturated peatlands tended to be dominated by a single environmental driver (inundation or air temperature), unlike those of inversions and more sophisticated forward models; (d) differences in biogeochemical schemes across models had relatively smaller influence over performance; and (e) multiyear or multidecade observational records are crucial for evaluating models' responses to long-term climate change.

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“…Hence, the spatial locations of coupling are not limited to a certain regional domain. Also, a global coupled model setup makes it possible to implement a single-stage inversion and data assimilation schemes, as opposed to the two-stage approach proposed for nested model setups (Peylin et al, 2005;Rödenbeck et al, 2009). Combining Eulerian and Lagrangian models offer the opportunity of constructing a cost-efficient, high-resolution surface flux data assimilation system.…”

Section: Introductionmentioning

confidence: 99%

Simulation of variability in atmospheric carbon dioxide using a global coupled Eulerian – Lagrangian transport model

et al. 2011

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Abstract. This study assesses the advantages of using a coupled atmospheric-tracer transport model, comprising a global Eulerian model and a global Lagrangian particle dispersion model, to improve the reproducibility of tracer-gas variations affected by the near-field surface emissions and transport around observation sites. The ability to resolve variability in atmospheric composition on an hourly time-scale and a spatial scale of several kilometers would be beneficial for analyzing data from continuous ground-based monitoring and from upcoming space-based observations. The coupled model yields an increase in the horizontal resolution of transport and fluxes, and has been tested in regional-scale studies of atmospheric chemistry. By applying the Lagrangian component to the global domain, we extend this approach to the global scale, thereby enabling computationally efficient global inverse modeling and data assimilation. To validate the coupled model, we compare model-simulated CO 2 concentrations with continuous observations at three sites: two operated by the National Oceanic and Atmospheric Administration, USA, and one operated by the National Institute for Environmental Studies, Japan. As the goal of this study is limited to introducing the new modeling approach, we selected a transport simulation at these three sites to demonstrate how the model may perform at various geographical areas. The coupled model provides improved agreement between modeled and observed CO 2 concentrations in comparison to the Eulerian model. In an area where variability in CO 2 concentration is dominated by a fossil fuel signal, the correlation coefficient between modeled and observed concentrations increases by between 0.05 to 0.1 from the original values of 0.5-0.6 achieved with the Eulerian model.

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A two-step scheme for high-resolution regional atmospheric trace gas inversions based on independent models

Cited by 78 publications

References 18 publications

Inverse modelling of European CH<sub>4</sub> emissions during 2006–2012 using different inverse models and reassessed atmospheric observations

Inverse modelling of European CH<sub>4</sub> emissions during 2006–2012 using different inverse models and reassessed atmospheric observations

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

Simulation of variability in atmospheric carbon dioxide using a global coupled Eulerian – Lagrangian transport model

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A two-step scheme for high-resolution regional atmospheric trace gas inversions based on independent models

Cited by 78 publications

References 18 publications

Inverse modelling of European CH&lt;sub&gt;4&lt;/sub&gt; emissions during 2006–2012 using different inverse models and reassessed atmospheric observations

Inverse modelling of European CH&lt;sub&gt;4&lt;/sub&gt; emissions during 2006–2012 using different inverse models and reassessed atmospheric observations

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

Simulation of variability in atmospheric carbon dioxide using a global coupled Eulerian – Lagrangian transport model

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Inverse modelling of European CH<sub>4</sub> emissions during 2006–2012 using different inverse models and reassessed atmospheric observations

Inverse modelling of European CH<sub>4</sub> emissions during 2006–2012 using different inverse models and reassessed atmospheric observations