|Review of gmd-2019-146 revision:|
Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2
This is a revision of a previously reviewed manuscript. The authors have done a good job addressing the reviewer comments (which was not a trivial task), but there are still a few things that need clarification before publication. I don’t have any major concerns. Please see the comments below for details.
page 3, lines 19-23:
It isn’t clear what “inconsistent land-cover translation” means here. Inconsistent with LUH? Inconsistent across ESMs/DGVMs?
It seems that the meaning here is leaning toward inconsistency across ESMs/DGVMs, but both inconsistencies are relevant. So I suggest clearly specifying both.
And “globally consistent” is also ambiguous. A rule that is global in spatial extent? Or a rule that is applied consistently by different folks around the globe? Again, it seems like the latter makes more sense here. That it is a global rule is different issue that also generates uncertainty.
Also, “eliminate added uncertainties” is an overly ambitious claim.
Maybe try “Consistent application of a specified rule for translating…could reduce uncertainties from translation inconsistencies in studying…”
page 4, lines 14-16:
Please clarify the relationship to LUH2. These GLM2 runs generate and track the exact same LUH2 data as before, and the additional translational tracking does not affect the LUH2 land use transitions. The translation and tracking of vegetation carbon is an additional capacity.
page 5, lines 17-20
Does this mean that the constant spin-up climate is a 100-year average?
How were the stocks and fluxes calculated during the translation simulations?
Did the spin-up produce a spatial, but temporally static, look-up table for use by the simulations, or was it just for initial conditions?
Or are the simulations also driven by some form of static or time-varying climate that determines carbon fluxes and stocks?
It appears later on page 7 that the spinup contributes to parameters for eq. 7. This should be clarified here.
page 5, line 30
Is the type of vegetation remaining in the land use categories (5-8) tracked? Or is it just the biomass value that characterizes the vegetation?
Is it assumed that land use categories have no biomass (and no change over time in biomass) if the vegetation has been cleared (this is answered on page 10)?
page 6, lines 11-14
Is this correct for gamma? It seems like it should be the opposite: a 1 value for “O” such that the land use type gains vegetation when no clearing occurs. Clearing means that no vegetation would be gained.
page 7, lines 3-4
This needs clarification, as gamma isn’t the same as for the reverse of transitions to land use categories. For example, any transition to land use from primary or secondary would generate a loss of vegetation in primary or secondary land, regardless of clearing, which would mean that gamma is always one for eq. 5; the lost vegetation fraction would either be in a land use category, or it has been cleared.
page 11, line 12
reference table 4
page 11, line 13
I suggest being specific here, as table 4 shows the results. You don’t need the e.g. clause, and you should state that 5 of 8 countries have values within range for rules 1-3 and 4 out of 8 for rule 4 (if i counted correctly)
page 11, line 16
It isn’t clear what you mean here by larger difference and what these differences are. I assume you mean differences between rules 1-3 and rule 4.
page 12, line 22
I am not sure that this metric evaluates the heterogeneity. I suggest something like “…best capture carbon density globally…)
Discussions and Conclusions
page 13, lines 10-11
I suggest rephrasing rangeland part, as currently it isn’t clear what the rule does when establishing rangeland. Rather than switching to leaving vegetation, state that for rangeland the rule clears all vegetation only if source land is forest.