TransCom 3 CO$_2$ inversion intercomparison: 1. Annual mean control results and sensitivity to transport and prior flux information

* Corresponding author
5 SATINV - Modélisation INVerse pour les mesures atmosphériques et SATellitaires
LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] : DRF/LSCE
8 ICOS-ATC - ICOS-ATC
LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] : DRF/LSCE
9 AOS Program - Atmospheric and Oceanic Sciences Program [Princeton]
GFDL - NOAA Geophysical Fluid Dynamics Laboratory, Princeton University
16 MOSAIC - Modélisation des Surfaces et Interfaces Continentales
LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] : DRF/LSCE
Abstract : Spatial and temporal variations of atmospheric CO$_2$ concentrations contain information about surface sources and sinks, which can be quantitatively interpreted through tracer transport inversion. Previous CO$_2$ 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 CO$_2$ 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.
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K. Gurney, R. Law, A. Denning, P. Rayner, D. Baker, et al.. TransCom 3 CO$_2$ inversion intercomparison: 1. Annual mean control results and sensitivity to transport and prior flux information. Tellus B - Chemical and Physical Meteorology, Taylor & Francis, 2003, 55 (2), pp.555-579. ⟨10.3402/tellusb.v55i2.16728⟩. ⟨bioemco-00175987⟩

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