Part 1. Optimising surfaces fluxes with atmospheric CO2: strength & weaknesses

Up to recently atmospheric CO2 data have been used to optimise surface CO2 fluxes after the inversion of the atmospheric transport (see main presentation for the principle). Several groups have used different transport mode, different prior flux information, l and different inversion schemes. Main differences are

  • The spatial esolution of the surfaces fluxes that are optimized: from each model grid pixel to large scale regions (22 in some cases)
  • The temporal resolution of the fluxes: from monthly to weekly
  • The algorythm to minimize the cost function: either based on a matrix formulation or on a variational approach (see main presentation)
  • The transport model resolution: from 1 degree grid to 4 degree grid resolution
  • The type of re-analysed wind fields: from different meteorological institute (ECMWF, NCEP, ...)
  • The prior fluxes that will be further optimized: using different biosphere model for the land, different ocean estimates, and different fossil fuel emissions
  • The prior flux errors and errors covariances

11 inversions are compared below. Their main characteristic are provided in Table 1:

Table. Participating inversion systems and key attributes

Acronym Refence # of regions Time period Obs1 # of obs locations2 IAV wind3 IAV priors4
LSCEa Piao et al, 2009 Grid-cell (96x72) 1996-2004 MM 67 Yes No
MACC-II Chevallier et al, 2010 Grid-cell (96x72) 1988-2011 Raw 134 Yes Yes
CCAM Rayner et al, 2008 146 1992-2008 MM 73 CO2
No No
MATCH Rayner et al, 2008 116 1992-2008 MM 73 CO2
No No
CT2011_oi Peters et al, 2007 156 2001-2010 Raw 96 Yes Yes
CTE2013 Peters et al, 2010 168 2001-2010 Raw 117 Yes Yes
JENA (s96, v3.5) Rödenbeck, 2005 Grid-cell (72x48) 1996-2011 Raw 50 Yes No
RIGC (TDI-64) Patra et al, 2005a 64 1989-2008 MM 74 Yes No
JMA Maki et al, 2010 22 1985-2009 MM 146 Yes No
TrC Gurney et al, 2008 22 1990-2008 MM 103 No No
NICAM Niwa et al, 2012 40 1988-2007 MM 71 Yes No

1: Observations used as monthly means (MM) or at sampling time (Raw)
2: Number of measurement locations included in the inversion (some inversions use multiple records from a single location)
3: Inversion accounts for interannually varying transport (Yes) or not (No)
4: Inversion accounts for interannually varying prior fluxes (Yes) or not (No)

Typical results obtained with these inversions are:

Figure 1. Mean natural fluxes for the period 2001-2004 of the individual participating inversion posterior fluxes. Shown here are total (first column), natural "fossil corrected" land (second column) and natural ocean (third column) carbon exchange aggregated over the Globe (top row), the North (2nd row), the Tropics (3rd row) and the South (bottom row), with the three regions divided by approximately 25°N and 25°S (but modified over land areas to keep regional estimates (e.g. northern Africa) in one region; see figure S7 in Supplementary Material). Numbers in parentheses represent the mean flux and the standard deviation across all inversions.

Figure 2. Annual mean anomalies of the individual participating inversion posterior flux estimates. Shown here are the fossil corrected natural land (first column) and natural ocean (second column) carbon exchange for the same regions as Figure 4: the Globe, north (> 25N), tropics (25S-25N) and south (< 25S).

Visit the following web sites to make your own comparison with these inversions:


  1. What are the robust features across the different inversions?
  2. What are the main causes of flux differences across the different inversions? Try to rank them according to your understanding of the whole inversion process.