LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Klimpt, Johannes; Friese, Elmar; Elbern, Hendrik (2016)
Languages: English
Types: Article
Subjects:
This idealized regional atmospheric inversion study assesses the potential of the 4-dimensional variational (4D-Var) method to estimate CO2 fluxes and the atmospheric CO2 concentration state jointly. In order to distinguish and quantify the surface-atmosphere CO2 fluxes, combining anthropogenic CO2 emissions, photosynthesis, and respiration, we include uncertainties of initial values, which arise from highly uncertain surface fluxes and night-time transport. Therefor a new calculation of the background error standard deviation for the CO2 fluxes was developed. To suppress spurious wiggles occurring from advection, an absolute monotone advection scheme with low numeric diffusion and its adjoint has been implemented. The inversion by the EURopean Air pollution Dispersion-Inverse Model (EURAD-IM) with 5 km resolution in Central Europe is validated by synthetic half hourly measurements from eleven concentration towers. A significant improvement of the analysis is shown if initial values and CO2 fluxes are optimised jointly, compared to optimising CO2 fluxes alone, without estimating uncertainty of atmospheric concentration. We find that joint estimation of carbon fluxes and initial states requires a careful balance of the background error covariance matrices but enables a more detailed analysis of atmospheric CO2 and the surface-atmosphere fluxes.

Share - Bookmark

Cite this article

Collected from