Received: 25 May 2016 – Accepted for review: 18 Aug 2016 – Discussion started: 19 Aug 2016
Abstract. 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.
This preprint has been withdrawn.
How to cite. Klimpt, J., Friese, E., and Elbern, H.: Joint CO2 state and flux estimation with the 4D-Var system EURAD-IM, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2016-132, 2016.
Atmospheric inversions optimize surface-atmosphere CO2 fluxes using CO2 concentration observations and atmospheric transport models. This study optimizes additionally the atmospheric initial concentration of CO2 jointly with the fluxes. Artificial generated observations are used to estimate limits and benefits of the used inversion method.
Uncertainty of analyzed CO2 fluxes can be reduced with the joint optimization of fluxes and the atmospheric CO2 concentration.
Atmospheric inversions optimize surface-atmosphere CO2 fluxes using CO2 concentration...