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Original Research Papers

TransCom 3 CO2 inversion intercomparison: 1. Annual mean control results and sensitivity to transport and prior flux information

Authors:

Kevin Robert Gurney ,

Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, US
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Rachel M. Law,

CSIRO Atmospheric Research, PMB 1, Aspendale, Victoria 3195, AU
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A. Scott Denning,

Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, US
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Peter J. Rayner,

CSIRO Atmospheric Research, PMB 1, Aspendale, Victoria 3195, AU
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David Baker,

National Center for Atmospheric Research (NCAR), Boulder, CO 80303, US
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Philippe Bousquet,

Laboratoire des Sciences du Climat et de l’Environment (LSCE), F-91198 Gif-sur-Yvette Cedex, FR
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Lori Bruhwiler,

National Oceanic and Atmospheric Administration (NOAA), Climate Monitoring and Diagnostics Laboratory, 326 Broadway R/CG1, Boulder, CO 80303, US
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Yu-Han Chen,

Department of Earth, Atmospheric, and Planetary Science, Massachusetts Institute of Technology (MIT), Cambridge, MA 0214, US
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Philippe Ciais,

Laboratoire des Sciences du Climat et de l’Environment (LSCE), F-91198 Gif-sur-Yvette Cedex, FR
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Songmiao Fan,

AOS Program, Princeton University, Sayre Hall, Forrestal Campus PO Box CN710 Princeton, NJ 08544-0710, US
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Inez Y. Fung,

Center for Atmospheric Sciences, McCone Hall, University of California, Berkeley, CA 94720-4767, US
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Manuel Gloor,

Max-Planck Institute fur Biogeochemie, D-07701 Jena, DE
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Martin Heimann,

Max-Planck Institute fur Biogeochemie, D-07701 Jena, DE
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Kaz Higuchi,

Meteorological Service of Canada, Environment Canada, Toronto, Ontario M3H 5T4, CA
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Jasmin John,

Center for Atmospheric Sciences, McCone Hall, University of California, Berkeley, CA 94720-4767, US
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Eva Kowalczyk,

CSIRO Atmospheric Research, PMB 1, Aspendale, Victoria 3195, AU
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Takashi Maki,

Quality Assurance Section, Atmospheric Environment Division, Observations Department, Japan Meteorological Agency, 1-3-4 Otemachi, Chiyoda-ku, Tokyo 100-8122, JP
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Shamil Maksyutov,

Institute for Global Change Research, Frontier Research System for Global Change, Yokohama, 236-0001, JP
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Philippe Peylin,

Laboratoire des Sciences du Climat et de l’Environment (LSCE), F-91198 Gif-sur-Yvette Cedex, FR
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Michael Prather,

Earth System Science, University of California, Irvine, CA 92697-3100, US
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Bernard C. Pak,

Earth System Science, University of California, Irvine, CA 92697-3100, US
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Jorge Sarmiento,

AOS Program, Princeton University, Sayre Hall, Forrestal Campus PO Box CN710 Princeton, NJ 08544-0710, US
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Shoichi Taguchi,

National Institute of Advanced Industrial Science and Technology, 16-1 Onogawa Tsukuba, Ibaraki 305-8569, JP
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Taro Takahashi,

Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, US
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Chiu-Wai Yuen

Meteorological Service of Canada, Environment Canada, Toronto, Ontario M3H 5T4, CA
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Abstract

Spatial and temporal variations of atmospheric CO2 concentrations contain information about surface sources and sinks, which can be quantitatively interpreted through tracer transport inversion. Previous CO2 inversion calculations obtained differing results due to different data, methods and transport models used. To isolate the sources of uncertainty, we have conducted a set of annual mean inversion experiments in which 17 different transport models or model variants were used to calculate regional carbon sources and sinks from the same data with a standardized method. Simulated transport is a significant source of uncertainty in these calculations, particularly in the response to prescribed “background” fluxes due to fossil fuel combustion, a balanced terrestrial biosphere, and air—sea gas exchange. Individual model-estimated fluxes are often a direct reflection of their response to these background fluxes. Models that generate strong surface maxima near background exchange locations tend to require larger uptake near those locations. Models with weak surface maxima tend to have less uptake in those same regions but may infer small sources downwind. In some cases, individual model flux estimates cannot be analyzed through simple relationships to background flux responses but are likely due to local transport differences or particular responses at individual CO2 observing locations. The response to the background biosphere exchange generates the greatest variation in the estimated fluxes, particularly over land in the Northern Hemisphere. More observational data in the tropical regions may help in both lowering the uncertain tropical land flux uncertainties and constraining the northern land estimates because of compensation between these two broad regions in the inversion. More optimistically, examination of the model-mean retrieved fluxes indicates a general insensitivity to the prior fluxes and the prior flux uncertainties. Less uptake in the Southern Ocean than implied by oceanographic observations, and an evenly distributed northern land sink, remain in spite of changes in this aspect of the inversion setup.

How to Cite: Gurney, K.R., Law, R.M., Denning, A.S., Rayner, P.J., Baker, D., Bousquet, P., Bruhwiler, L., Chen, Y.-H., Ciais, P., Fan, S., Fung, I.Y., Gloor, M., Heimann, M., Higuchi, K., John, J., Kowalczyk, E., Maki, T., Maksyutov, S., Peylin, P., Prather, M., Pak, B.C., Sarmiento, J., Taguchi, S., Takahashi, T. and Yuen, C.-W., 2003. TransCom 3 CO2 inversion intercomparison: 1. Annual mean control results and sensitivity to transport and prior flux information. Tellus B: Chemical and Physical Meteorology, 55(2), pp.555–579. DOI: http://doi.org/10.3402/tellusb.v55i2.16728
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  Published on 01 Jan 2003
 Accepted on 27 Nov 2002            Submitted on 22 May 2002

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