 |
| Titel |
Re-scaling CO2 natural fluxes over land to correct the global annual growth of CO2 in the MACC CO2 analysis |
| VerfasserIn |
A. Agusti-Panareda, S. Boussetta, G. Balsamo, G. van der Werf, F. Chevallier, R. Engelen, I. Sandu, A. Beljaars, J. Kaiser, A. Andrews, T. J. Conway, K. Masarie, C. Sweeney, P. Tans |
| Konferenz |
EGU General Assembly 2012
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250063475
|
|
|
|
|
|
| Zusammenfassung |
| In the Monitoring of Atmospheric Composition and Climate (MACC) project, analyses of
atmospheric CO2 concentrations are produced by assimilating satellite observations in the
ECMWF Integrated Forecasting System (IFS) Numerical Weather Prediction model. One of
the most important aspects in the assimilation and modelling of CO2 is the representation of
the correct annual growth rate in the atmosphere, which is a small residual of large
source and sink fluxes. In the IFS transport model, the CO2 fluxes are prescribed as
inventories based on off-line statistical and physical models. Currently, the vegetation
fluxes are from the CASA-GFED inventory; although in the future, fluxes from the
CTESSEL model will be implemented on-line. Any small regional error associated
with those fluxes can accumulate and produce large errors in the global annual
budget, if not corrected by the assimilated observations. This leads to biases in the
atmospheric growth of the model, and subsequently, of the analyses. This poster presents a
simple vegetation flux correction method that can be applied off-line prior to the
analysis.
The method aims to correct the CO2 annual growth rate and reduce the errors of the
background concentrations with respect to the NOAA Globalview processed observations of
the marine boundary layer. The correction factors are computed separately over four
latitudinal regions that have coherent seasonal cycles. This is done by converting the regional
mean concentration error into a regional mean flux correction and then regressing the latter
against the regional mean Net Primary Production (NPP) and heterotrophic respiration (Rh)
fluxes. The regression coefficients for each region are then applied to the original NPP and Rh
flux fields. This correction is time independent and it aims to improve the budget as well as
the seasonal cycle and the interhemispheric gradient, without having any impact
on the subseasonal and subregional variability.A final annually dependent global
rescaling is also applied to match the global annual budget of the observed atmospheric
growth.
The results of the flux corrections show that there is a great reduction in the CO2 bias in
the free troposphere. The original annual bias of 1.4 ppm is reduced to 0.3 ppm. There
is also an improvement in the seasonal cycle and interhemispheric gradient with
monthly biases ranging between -0.5 and 1 ppm compared to original monthly
biases of up to 3ppm.The impact in the standard deviation of the error is small as
expected, since the flux variability remains essentially unchanged. In the boundary
layer the results show a mixed impact because of the large influence of tranport
and mixing errors in the boundary layer which can compensate for flux errors.
In summary, this simple method can produce a preliminary flux correction that
greatly reduces the biases in the model and analysis. It can be applied easily in an
operational context within the MACC project. The method can also be used as a
diagnostic tool to evaluate the atmospheric CO2 budget from vegetation models such as
CTESSEL. |
|
|
|
|
|
|