Abstract. Terrestrial ecosystem models are employed to calculate the sources and sinks of carbon dioxide between land and atmosphere. These models may be heavily parameterised. Where reliable estimates are unavailable for a parameter, it remains highly uncertain; uncertainty of parameters can substantially contribute to overall model output uncertainty. This paper builds on the work of the terrestrial Carbon Cycle Data Assimilation System (CCDAS), which, here, assimilates atmospheric CO2 concentrations to optimise 19 parameters of the underlying terrestrial ecosystem model (Biosphere Energy Transfer and Hydrology scheme, BETHY). Previous experiments have shown that the identified minimum may contain non-physical parameter values. One way to combat this problem is to use constrained optimisation and so avoid the optimiser searching non-physical regions. Another technique is to use penalty terms in the cost function, which are added when the optimisation searches outside of a specified region. The use of parameter transformations is a further method of avoiding this problem, where the optimisation is carried out in a transformed parameter space, thus ensuring that the optimal parameters at the minimum are in the physical domain. We compare these different methods of achieving meaningful parameter values, finding that the parameter transformation method shows consistent results and that the other two provide no useful results.

Limiting the parameter space within the Carbon Cycle Data Assimilation System (CCDAS)

This work presents a flux inversion system for assessing the potential of new satellite imagery measurements of atmospheric CO2 to monitor anthropogenic emissions at scales ranging from local intense point sources to regional and 10 national scales. While the modeling framework keeps the complexity of previous studies focused on individual and large cities, this system encompasses a wide range of sources to extend the scope of the analysis. This atmospheric inversion system uses a zoomed configuration of the regional transport model CHIMERE which covers most of Western Europe with a 2-km resolution grid over nNorthern France, wWestern Germany and Benelux. For each day of March and May 2016, over the 6 hours before a given satellite overpass, the inversion controls separately the hourly budgets of anthropogenic emissions 15 in this area from ~300 cities, power plants and regions. The inversion also controls hourly regional budgets of the natural fluxes. This enables the analysis of results at the local to regional scales for a wide range of sources in terms of emission budgets and spatial extent while accounting for the uncertainties associated with to natural fluxes and the overlapping of plumes from different sources. The potential of satellite data to monitor CO2 fluxes is quantified by with posterior uncertainties or uncertainty reductions (URs) from prior inventory-based statistical knowledge. 20 A first analysis focuses on the hourly to 6-hour budgets of the emissions of the Paris urban area, and on the sensitivity of the results to different characteristics of the images of vertically integrated CO2 (XCO2) corresponding to the spaceborne instrument: the pixel spatial resolution, the precision of the XCO2 retrievals per pixel, and the swath width. This sensitivity analysis provides a correspondence between these parameters and thresholds on the targeted precisions on of emission estimates. However, the results indicate a large sensitivity to the wind speed and to the prior flux uncertainties. The analysis 25 is then extended to the large ensemble of point sources, cities and regions in the study domain, with a focus on the inversion system ability to monitor separately neighbor sources whose atmospheric signatures overlap and are also mixed with those produced by natural fluxes. Results highlight the strong dependence of uncertainty reductions to the emission budgets, to the wind speed and on whether the focus is on point or area sources. With the system hypothesis that the atmospheric transport is perfectly known, the results indicate that the atmospheric signal overlap is not a critical issue. For the emissions within the 630 hours before a satellite overpass, URs of more than 50% can only be achieved for power plants and cities whose annual

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Response to Anonymous Referee #1

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Response to Anonymous Referee #1