General comments
The authors present advancements in tuning the land surface model ORCHIDEE as contained in the IPSL6 Earth system model. Their effort focuses on the bare soil evaporation, the photosynthesis parametrization, and the low-temperature limit on tree mortality. Along the way, they quantify how these changes in the vegetation/land surface modeling modulate the coupled land-climate response under PI and mid-Holocene (MH) climate states with a focus on atmospheric variables and the energy balance. The main objectives in the tuning process have been to increase the extent and amount of boreal forest PFTs and to obtain a partial greening of the Sahara under MH conditions. Both of these tuning objectives were met in the process. Based on their sensitivity experiments, the authors found the photosynthesis parametrization to cause the strongest modulating effects on the radiative response because of its direct link to GPP and, therefore, land surface properties in the mid- to boreal latitudes. In this context, they stress the importance of seasonality, since the two different photosynthesis schemes differ in the start of the growing season they produce.
In response to the initial referee statements, the authors incorporated suggested changes, which were mainly on the presentation and implications of their work. In particular, they updated the Discussions and Conclusions sections and revised several unclear statements. In my opinion, these changes have already improved the presentation of their study. However, besides a number of specific comments, I want to make a general comment which also focuses on accessibility:
With the interdisciplinary readership of ESD in mind, I recommend expanding more on the study’s motivation and context, especially in the abstract and introduction. Currently, the manuscript lacks context/explanation at the beginning of both the abstract and the introduction. As a result, the entry barrier to the manuscript could be very high for readers who are not already familiar with the thinking of land modelers. Beyond that, the manuscript takes it somewhat as a given that the chosen time frames (PI, MH) and parametrizations (bare soil, photosynthesis, tcrit) are of interest. The same goes for introducing the relevance of vegetation feedbacks and the reasoning behind DGVMs as a whole. I reckon re-ordering thoughts popping up here and there in the introduction could reduce these entry barriers and improve its readability at the same time. For example, I would recommend touching on the PI and MH time frames much earlier - right now, this is done in greater detail only at the end of the introduction, but it would be helpful a lot earlier. Another example would be to touch on vegetation feedback with concrete examples early on, e.g., after the first sentence of the introduction, rather than jumping right to the standard literature review.
In addition to that, I suggest the authors expand on how they employ the term “feedback” throughout the manuscript. On the one hand, they modify the strength and character of the vegetation’s response to climate, which alters the vegetation-climate feedback loops, which is clearly formulated. However, on the other hand, they compare the radiative effects between the different model configurations/climate states and term the result of this analysis “feedback” as well (e.g. Figures 6, 11). Although one can “sense” the proximity of these radiative effects to the concept of a feedback factor (think ECS as an example), their understanding is not precisely described. As a result, I am asking myself the question to what degree the difference in radiative effect of say the “surface albedo feedback” diagnosed between the two climate states (Fig 6) is directly comparable to the radiative effect diagnosed between different model versions (Fig 11). Thus, I am missing a brief explanation of what is considered the forcing in the different analyses. Maybe adding a conceptual figure to the introduction or to Section 3.3 would have avoided my confusion.
Finally, I am convinced that providing the final manuscript to a native-language proofreader and utilizing one of the many spell- and grammar-checkers would greatly help improve its readability and accessibility. Currently, it contains a lot of typos and convoluted sentences. I would not expect an extremely polished text, but as a reader, I found it very hard to get the author’s point on a number of occasions, and it should be in the author’s interest to make the paper easily accessible to the reader. I am listing a number of technical comments at the end of my statement, but this list is not exhaustive.
Specific comments
- General remark on figures: Many figures use a color scheme that is not colorblind-safe. I am not expecting the authors to necessarily change this aspect, but I would recommend keeping this in mind for upcoming work. Also, with the current projection of map plots, I found it challenging to recognize details in the high latitudes – This is a bit unfortunate, since a substantial part of the results centers around exactly those areas.
- The authors have updated the title. However, I find the newly added word “highlight” inconclusive. To my understanding, the authors utilize it in the sense of “modulating” or “amplifying” in the text as well (e.g., l 498), and in my opinion, both of these terms would describe their intention more precisely.
- l 26: mid-Holocene and pre-industrial climate → mid-Holocene and pre-industrial vegetation state? (I am not convinced the green Sahara and boreal forest are part of the climate state in the physical sense.)
- l65: I find this statement a bit too much black and white, since there is more granularity to discuss on how much vegetation dynamics are (not) considered. Maybe the authors can expand a bit on this statement/add a reference.
- l194/195: What kind of inconsistencies and why are they not relevant to this study?
- Section 2.3 title: “Vegetation-climate equilibration” ?
- Figure 3/Section 5.3: Is Bartlein et al. 2011 really the most up-to-date/comprehensive reconstruction that is suitable? Also, it is only pollen-based and does not use multiple proxies. Would newer reconstructions like Erb et al. 2022 (Clim Past, multi-proxy but no pollen cores) be an alternative, or are there other reasons that are not discussed here?
- Section 3.2: I wonder if it has been tested whether this approach is sensitive to the length of the different simulations. Since they have different lengths, they result in a different number of 100-year-long slices, and I could imagine this to have consequences for the statistics.
- l306-308: I actually do not agree with how the figure is interpreted here. From Fig.5 it appears that the LAI in V2 is similar to V4 as well. And it seems to me that the snow cover changes are definitely the largest for V2 and V3.
- l313-315: From Fig.5 it also appears to me that V2 and V3 produce the lowest changes in precipitable water in the tropics, not the largest. In the high latitudes, the opposite applies.
- l400: Figure 10 is not referenced, but I think it is discussed here.
- l410: I am pretty sure this should be Fig 11, not 12, referenced here.
- Figure 12: As far as I can see, it is neither referenced nor explained anywhere.
- The third-to-last paragraph in the Results is hard to read and could be simplified.
- l524: I do not agree with how the finding is described here. The seasonality (difference between the highest and lowest amplitude) is stronger for V2, but it is not for V3, which in turn is very similar to V4. V1 resembles V2 more than it resembles V4.
- l532-535: The authors argue that a seasonally lower GPP drives a higher soil moisture content. However, I cannot infer a seasonally higher moisture content in V4 from Figure 9, although I do see an overall offset. I would rather interpret this in a way that seasonally lower GPP reduces (evapo-)transpiration, leading to higher soil moisture.
- l535-536: I am not convinced whether one can actually call this aspect counterintuitive. To me, it rather appears to be a straightforward consequence of the different photosynthesis schemes.
- Section 5.3: When discussing land use effects, it should be noted that they also induce non-local effects. Therefore, the “NOLU” reference values could (and likely will) be affected by land use as far as I can see. Non-local effects could be briefly mentioned here.
- Section 6: As already pointed out by other referees, the case for DGVMs has been made before – which does not imply that the relevance for including them in ESM simulations should not be mentioned here. However, to perhaps suggest an additional aspect for the conclusions here: To me, this study is a great example for “no model (configuration) suits all needs” – one configuration/model might be better suited to simulate a Sahara greening, while another one might result in lower climate biases in another region of interest (and in addition climate is not just mean climate). And this diversity stems from the fact that the Earth system is highly complex and dynamic. Maybe the authors are interested in taking up this aspect.
Technical corrections
Multiple occasions:
- “Northern Hemisphere” (capital letters)
- “pre-industrial”, “mid-Holocene” (mind the dash)
- “fully coupled/fully-coupled” (adopt one convention)
- “model content” – “model configuration” is probably more precise
- At several occasions “It”/”This” is used for a couple of sentences in a row. At some point, you lose track of what the term actually refers to, which is not helpful.
- l 28: Major aims have been to either … and to …
- l34: for the last glacial inception
- l37: What is the “initial effect of vegetation” – are you referring to the model spin-up? I wouldn’t consider this a very physical motivation for vegetation feedbacks.
- l37: “They” – Who?
- l48: I guess the authors are referring to Holocene simulations? Isn’t interactive vegetation common in a number of models, meanwhile, for present-day and future?
- l49: “still have”
- l50: “model biases … as those discussed by” – As the whole paper is about improving a vegetation model, it would add to the motivation of the study to name a few of the biases specifically
- l54: “Climate-vegetation feedbacks on climate sensitivity… in estimates of climate sensitivity”
- ll56-58: The sentence is confusing. It seems to mention the same aspect twice.
- l61: interconnections
- l63: may be
- l64: “fully-coupled” and then the sentence does not make any sense to me afterwards
- l67-69: The sentence is very long and convoluted
- l71: “the vegetation-climate feedback” – which feedback? This would be an opportunity to be more precise/expand
- l77: “on the model content”
- l83: “We focus on estimating the atmospheric..”
- l90: remainder
- l105: “run using …” → “operates on the atmospheric”
- l119: “two parametrizations”?
- l182: similar orbital configuration
- l186/187: “It somehow provides..” Sounds a bit spongy – could you be more precise?
- l211: imposes a cold start for the land surface
- l214: “recovery” is not so much the right word here, I would suggest “adjustment”?
- Figure 2: There are some data gaps in panel (I), which I would not expect. Also, there is a type in “bare soil” (panel a)
- l252: interpolated to
- l254 and following: “centennial” would be an alternative to “100-year”
- l265: “when accounting for uncertainties (Fig 5)” – Figure 5 does not show any uncertainties
- l266: “as it is expected with vegetation feedback.” Why is this expected?
- l280: “we computed”
- l301: omit “with”
- l329: by replacing … one by one by those obtained ...
- l338: LW_sup
- l362: The first-order feedbacks between … highlighted in the previous section
- l376: “include the change”/”benefit from the change”
-l 384: “With the bareold scheme, …“
- Figure 9: “Evapnu”?; “Transpiration”
- l414: “are the differences in seasonal..”
- l419: “mainly originates from the relative..”
- l431: “does not prevent”
- l438: “outgoing”
- l439: “increasing temperature … the higher atmospheric..”
- l444-445: This sentence does not have any meaning
- l450: “The feedback differences between model versions”
- l460: “To first order, the distribution …”
- l498: “highlights” → “modulates” or “amplifies”?
- Figure 13: “Atmosphere”, “pre-industrial”
- l527-528: This sentence appears superfluous to me.
- Figure 14: wrong panel labels for (c) and (d). Also, I was wondering about the sign convention for the NEE here – do positive values correspond to more or less update?
- l552: “photosynthesis parametrization”
- l558-559: I was curious if the authors could speculate about the nature of these different characteristics.
- l561: What does “direct development” imply?
- l575: I think the reference should be to Fig.8 |
Comments on the manuscript
Dynamic vegetation reveals unavoidable climate feedbacks and their dependence on climate mean state
by Braconnot, Viory, Marti
Pascale Braconnot and coauthors present a study on vegetation-climate feedbacks. They use the new IPSLCM6 with four different parameter sets with respect to the representation of photosynthesis, bare soil evaporation and two parameters defining vegetation competition and distribution. They thoroughly analyze the effect of changing the parameter sets on the simulated global climate and vegetation patterns for preindustrial and for mid-Holocene climate. I am convinced that the specific results of their study strongly depend on the climate system model used and on the specific choice of the parameter sets. Other climate system models and other variation of other parameters would presumably yield other results. And that should explicitly be stated. However, I am also convinced that modeling groups can learn from the paper when addressing the general issue of tuning and exploring the sensitivity of vegetation-climate feedbacks on the choice of vegetation and soil parameters. Thus, I recommend publication of the study with minor corrections, but I strongly suggest skipping the term “unavoidable” in the title and in the text. This term is not explained in the text. It just sounds alarmistic, as if the model would have a choice to “avoid” any negative consequences of model tuning. Quite the contrary, model tuning is done to improve the model performance.
When reading the paper, I see that the new IPSLCM6 yields a much greener mid-Holocene Sahara than the former IPSLCM5 did. That is an exciting result. The authors highlight this achievement in one sentence (line 278/9) and a half-sentence (line 284/285). It would deserve more appreciation in the conclusions. Perhaps, a figure with a zoom on African biomes, using the biomization tool by Dallmeyer et al (2019), for example, which has already been applied to ORCIDEE PFTs, would be useful for a better comparison with other ESM simulations. But I leave this to the authors to decide. I do not like reviewers who suggest completely re-writing a paper or writing a new story. Hence, I only would like to encourage the authors considering an additional study with a perhaps even more interesting focus on the effects resulting from the upgrade from IPSLCM5 to IPSLCM6 versus changing the parameterization of bare soil and vegetation.
The sensitivity study is clearly written. Perhaps a more formal analysis using the Alpert-Stein factor separation would yield a better understanding of feedbacks and synergies between feedback. But, again, I do not insist on doing a new analysis which would require 24 simulations. It would be sufficient to mention that the present study does not differentiate between the pure contributions triggered by a new parameterization and the possible synergies emerging from combining new parameterizations.
Finally, I suggest skipping trivial common places like the very last paragraph (lines 630 – 634). It is completely true that dynamical vegetation is an important factor which should be considered in ESMs. But this study is not the first one to point to the importance of dynamic vegetation. We (including the authors) have convincingly addressed this topic by numerous studies over the last roughly 30 years.
Minor comments:
Line 116 and following: It would be useful to learn something about the interaction with the C-cycle. Into which carbon pools of the plants and the soil is the carbon gain by photosynthesis fed? Or does this issue do not play any role here?
Line 242, Fig. 3: The abbreviations in the title lines (dtas, dpr) are not defined in the caption. Why not put a \Delta T_s or \Delta P_r in the title lines and in the caption?
Line 257, Fig. 4: The new parameterizations increase the simulated annual mean precipitation in WA, but still, the simulated precip amounts to only a factor of 0.4 of the reconstructed precip. How is the aggregation of data points and comparison with grid box results done? Using any area-mean? (Would be sensible to only consider grid boxes for which reconstructions are available.)
Line 283 ff: “It results from vegetation feedbacks amplified by synergy with ocean feedbacks …” surely, it does. But without differentiation between feedback and synergy, it remains a trivial statement and could be skipped – in contrast to the second half of the sentence which likely is the real reason and would deserve more attention.
Line 287, Fig. 5: The labels on the colorbars are partly hidden behind the colorbars. Please shift. The global maps, specifically for the differences in lai, are too small to see any details outside the tropics. Please enlarge the figures to the size of the other global maps in the other figures.
Line 304: It would be helpful to note that alpha_p is the surface albedo. Commonly, one would symbolize the planetary albedo with the subscript ‘p’.
Eq.(3) and other places in the text: Sometimes the subscripts appear as subscripts, sometimes as an extension of the variable, for example as in SWsi vs. SW_{si} or LWsup vs. LW_{sup}. Please harmonize.
Line 318: gases instead of gazes
Line 348: What are pft 7 and 8? It would help reading, if the names of the PFTs are mentioned here or in a table.
Line 454 and other places: Sahara Sahel or Sahel Sahara sounds a bit cumbersome, because the Sahara and the Sahel (region) are pretty different regions.
Line 457: …, so that the magnitude …
Line 509: “The suite of mid-Holocene … allow us to dig into the complexity of the Earth’s climate system.” That is a rather generic and bold statement as this study just touches a small subset and very specific aspects of the global climate system.
Line 510: “We insist on the fact …” I do not understand, why you have to ‘insist’ on the fact, instead of highlighting the fact.
Line 519 ff: I do not quite understand the meaning of this sentence. Perhaps it is just the wording ‘associate to’ … The word ‘fulfil’ should be ‘fulfill’.
Line 527: “We show that dynamical vegetation reveals how ….” I am not sure how dynamical vegetation can reveal anything. The analysis of the climate-vegetation interaction can certainly do, but, again, only with respect to the processes considered, not with respect of the entire complexity of all biospheric processes.
Line 537: Which “step changes between the model version … is (shouldn’t is ‘are’) different from …?
Line 542: Which “model content” … lead(s) to different vegetation cover …?
Line 562 ff. Indeed, the statement that “simulated vegetation is an integrator …” is “trivial”. Perhaps a more modest statement would be sensible. This study is not the very first one to highlight the importance of vegetation dynamics.
Line 565/567. I agree that one cannot infer vegetation feedbacks from studies in which vegetation patterns are kept fixed. In this sense, the titles of early studies (e.g. Kutzbach et al. Nature 1996) are misleading. These studies analyzed impacts rather than feedbacks.
Line 596: This would require (instead of requires)
Line 600: … because land use (not land used) is not