Open AccessUsing CO 2 :CO correlations to improve inverse analyses of carbon fluxes
Author(s) -
Palmer Paul I.,
Suntharalingam Parvadha,
Jones Dylan B. A.,
Jacob Daniel J.,
Streets David G.,
Fu Qingyan,
Vay Stephanie A.,
Sachse Glen W.
Publication year - 2006
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2005jd006697
Subject(s) - inversion (geology) , covariance , a priori and a posteriori , inverse , environmental science , atmospheric sciences , mathematics , meteorology , statistics , geology , physics , paleontology , philosophy , geometry , epistemology , structural basin
Observed correlations between atmospheric concentrations of CO 2 and CO represent potentially powerful information for improving CO 2 surface flux estimates through coupled CO 2 ‐CO inverse analyses. We explore the value of these correlations in improving estimates of regional CO 2 fluxes in east Asia by using aircraft observations of CO 2 and CO from the TRACE‐P campaign over the NW Pacific in March 2001. Our inverse model uses regional CO 2 and CO surface fluxes as the state vector, separating biospheric and combustion contributions to CO 2 . CO 2 ‐CO error correlation coefficients are included in the inversion as off‐diagonal entries in the a priori and observation error covariance matrices. We derive error correlations in a priori combustion source estimates of CO 2 and CO by propagating error estimates of fuel consumption rates and emission factors. However, we find that these correlations are weak because CO source uncertainties are mostly determined by emission factors. Observed correlations between atmospheric CO 2 and CO concentrations imply corresponding error correlations in the chemical transport model used as the forward model for the inversion. These error correlations in excess of 0.7, as derived from the TRACE‐P data, enable a coupled CO 2 ‐CO inversion to achieve significant improvement over a CO 2 ‐only inversion for quantifying regional fluxes of CO 2 .