|The manuscript has improved a lot. The authors have made efforts to be more concise and include more references in the manuscript. Though, the manuscript still falls a bit short of references.. Below are some minor/technical points from the track change:|
p 2, line 35: The justification is too vague and not quantitative enough. It would be more relevant to specify the time scale and the horizontal resolution for which the assumption is valid based on specific case studies.
p 3, line 74: Add ..with processes not included..."
p 3, line 73: "This enables to include the information" Write instead "This enables the inclusion of information..".
p 3, line 74: You can specify that others groups have already coupled a land surface model to a transport model to assimilate both atmospheric observations (e.g., CO2 mixing ratio) and terrestrial observations.See the MPI-CCDAS with Schurmann et al. (2016), the ORCHIDEE-CCDAS with Peylin et al. (2016) and the BETHY-CCDAS (Rayner et al. (2005); Schloze et al. (2007); Ziehn et al. (2012) ; Kaminski (2013).
You could mention the technics used in these systems.
p 3, line 84: The BETHY Land Surface Model disposes also of an adjoint that is used to optimize the land surface parameters. See Ziehn et al. (2012).
p28, line 705: When mentioning the CPU time consumed by an experiment with ICLASS, it would be relevant to compare with a Land Surface Model (e.g., SIB4) coupled to a transport model. How much faster is ICLASS compared to a full LSM coupled to a transport model?
Ziehn, T., Scholze, M., and Knorr, W. (2012), On the capability of Monte Carlo and adjoint inversion techniques to derive posterior parameter uncertainties in terrestrial ecosystem models, Global Biogeochem. Cycles, 26, GB3025, doi:10.1029/2011GB004185.
Schürmann, G. J., Kaminski, T., Köstler, C., Carvalhais, N., Voßbeck, M., Kattge, J., Giering, R., Rödenbeck, C., Heimann, M., and Zaehle, S.: Constraining a land-surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System V1.0, Geosci. Model Dev., 9, 2999–3026, https://doi.org/10.5194/gmd-9-2999-2016, 2016.
Rayner, P. J., Scholze, M., Knorr, W., Kaminski, T., Giering, R.,
and Widmann, H.: Two decades of terrestrial carbon fluxes from
a carbon cycle data assimilation system (CCDAS), Global Biogeochem. Cy., 19, GB2026, doi:10.1029/2007JD008642, 2005.
Kaminski, T., Knorr, W., Scholze, M., Gobron, N., Pinty, B., Giering, R., and Mathieu, P.-P.: Consistent assimilation of MERIS
FAPAR and atmospheric CO2 into a terrestrial vegetation model
and interactive mission benefit analysis, Biogeosciences, 9,
3173–3184, doi:10.5194/bg-9-3173-2012, 2012.