An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker

Peters, Wouter; Jacobson, A. R.; Sweeney, Colm; Andrews, A. E.; Conway, T. J.; Masarie, K. A.; Miller, J. B.; Bruhwiler, L.; Pétron, Gabrielle; Hirsch, A.; Worthy, D.; Werf, Guido R. van der; Randerson, James T.; Wennberg, P. O.; Krol, Maarten; Tans, Pieter P.

doi:10.1073/pnas.0708986104

Cited by 996 publications

(1,166 citation statements)

References 32 publications

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“…The model combines surface air samples collected around the globe and from tall towers and small aircraft in North America with an atmospheric transport model coupled with a Kalman filter to produce estimates of atmospheric CO 2 mole fractions on a global grid (Peters et al, 2007). The model X CO 2 data are regularly gridded at 1 • × 1 • daily resolution, making it particularly convenient for use in spatial parameter estimation.…”

Section: Application To Acos-gosat and Tccon Datamentioning

confidence: 99%

A method for colocating satellite XCO2 data to ground-based data and its application to ACOS-GOSAT and TCCON

et al. 2014

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Abstract. Satellite measurements are often compared with higher-precision ground-based measurements as part of validation efforts. The satellite soundings are rarely perfectly coincident in space and time with the ground-based measurements, so a colocation methodology is needed to aggregate "nearby" soundings into what the instrument would have seen at the location and time of interest. We are particularly interested in validation efforts for satellite-retrieved total column carbon dioxide (X CO 2 ), where X CO 2 data from Greenhouse Gas Observing Satellite (GOSAT) retrievals (ACOS, NIES, RemoteC, PPDF, etc.) or SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIA-MACHY) are often colocated and compared to ground-based column X CO 2 measurement from Total Carbon Column Observing Network (TCCON).Current colocation methodologies for comparing satellite measurements of total column dry-air mole fractions of CO 2 (X CO 2 ) with ground-based measurements typically involve locating and averaging the satellite measurements within a latitudinal, longitudinal, and temporal window. We examine a geostatistical colocation methodology that takes a weighted average of satellite observations depending on the "distance" of each observation from a ground-based location of interest. The "distance" function that we use is a modified Euclidian distance with respect to latitude, longitude, time, and midtropospheric temperature at 700 hPa. We apply this methodology to X CO 2 retrieved from GOSAT spectra by the ACOS team, cross-validate the results to TCCON X CO 2 ground-based data, and present some comparisons between our methodology and standard existing colocation methods showing that, in general, geostatistical colocation produces smaller mean-squared error.

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Section: Application To Acos-gosat and Tccon Datamentioning

confidence: 99%

A method for colocating satellite XCO2 data to ground-based data and its application to ACOS-GOSAT and TCCON

et al. 2014

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“…This facilitates intercomparisons with data assimilation products like CarbonTracker [9], and also with aircraft measurements, which often occur over tall tower sites.…”

Section: Networkmentioning

confidence: 99%

The Total Carbon Column Observing Network

Wunch

Toon

Blavier

et al. 2011

Phil. Trans. R. Soc. A.

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A global network of ground-based Fourier transform spectrometers has been founded to remotely measure column abundances of CO 2 , CO, CH 4 , N 2 O and other molecules that absorb in the near-infrared. These measurements are directly comparable with the near-infrared total column measurements from space-based instruments. With stringent requirements on the instrumentation, acquisition procedures, data processing and calibration, the Total Carbon Column Observing Network (TCCON) achieves an accuracy and precision in total column measurements that is unprecedented for remotesensing observations (better than 0.25% for CO 2 ). This has enabled carbon-cycle science investigations using the TCCON dataset, and allows the TCCON to provide a link between satellite measurements and the extensive ground-based in situ network.

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“…Different retrievals of methane based on TANSO-FTS/GOSAT products are made available to the community Schepers et al, 2012;Parker et al, 2011) based on two retrieval approaches: proxy and full physics. The proxy method retrieves the ratio of methane column (XCH 4 ) and carbon dioxide column (XCO 2 ), from which XCH 4 is derived after multiplication with transport model-derived XCO 2 Peters et al, 2007;Frankenberg et al, 2006). It intends mostly to remove biases due to light scattering on clouds and aerosols and is highly efficient owing to the small spectral distance between CO 2 and CH 4 sunlight absorption bands (1.65 µm for CH 4 and 1.60 µm for CO 2 ).…”

Section: Satellite Data Of Column-averaged Chmentioning

confidence: 99%

The global methane budget 2000–2012

Saunois

Bousquet

Poulter

et al. 2016

Earth Syst. Sci. Data

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Abstract. The global methane (CH 4 ) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH 4 over the past decade. Emissions and concentrations of CH 4 are continuing to increase, making CH 4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH 4 sources that overlap geographically, and from the destruction of CH 4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (∼ biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). . Top-down inversions consistently infer lower emissions in China (∼ 58 Tg CH 4 yr −1 , range 51-72, −14 %) and higher emissions in Africa (86 Tg CH 4 yr −1 , range 73-108, +19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models.The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30-40 % on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions.

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An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker

Cited by 996 publications

References 32 publications

A method for colocating satellite <i>X</i><sub>CO<sub>2</sub></sub> data to ground-based data and its application to ACOS-GOSAT and TCCON

A method for colocating satellite <i>X</i><sub>CO<sub>2</sub></sub> data to ground-based data and its application to ACOS-GOSAT and TCCON

The Total Carbon Column Observing Network

The global methane budget 2000–2012

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An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker

Cited by 996 publications

References 32 publications

A method for colocating satellite &lt;i&gt;X&lt;/i&gt;&lt;sub&gt;CO&lt;sub&gt;2&lt;/sub&gt;&lt;/sub&gt; data to ground-based data and its application to ACOS-GOSAT and TCCON

A method for colocating satellite &lt;i&gt;X&lt;/i&gt;&lt;sub&gt;CO&lt;sub&gt;2&lt;/sub&gt;&lt;/sub&gt; data to ground-based data and its application to ACOS-GOSAT and TCCON

The Total Carbon Column Observing Network

The global methane budget 2000–2012

Contact Info

Product

Resources

About

A method for colocating satellite <i>X</i><sub>CO<sub>2</sub></sub> data to ground-based data and its application to ACOS-GOSAT and TCCON

A method for colocating satellite <i>X</i><sub>CO<sub>2</sub></sub> data to ground-based data and its application to ACOS-GOSAT and TCCON