the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Sep 2024
Pattern scaling of simulated vegetation change in North Africa during glacial cycles
Abstract. Over the last hundreds of millennia natural rhythms in Earth's astronomical motions triggered large-scale climate changes and led periodically to humid conditions in much of North Africa. Known as African humid periods (AHPs), such times sustained river networks, vegetation, wildlife and prehistoric settlements. Mechanisms, extent and timing of the changes still cannot be completely outlined. Although AHPs along glacial cycles are recognizable in long marine sediment records, the related land cover changes are difficult to reconstruct due to scarcity of proxy data over the continent. Moreover, most available information covers only the latest AHP during the Holocene. Here we use a comprehensive Earth system model to look at additional, much earlier, possible cases of AHPs. We simulate the full last glacial cycle, aiming to reproduce the last four AHPs as seen in available proxies. The simulated AHPs seem in broad agreement with geological records, especially in terms of timing and relative strength. We focus on the simulated vegetation coverage in North Africa and we detect a dominant change pattern that seems to scale linearly with known climate forcing variables. We use such scaling to approximate North African vegetation fractions over the last eight glacial cycles. Although the simple linear estimation is based on a single mode of vegetation variability (that explains about 70 % of the variance), it helps to discuss some broad-scale spatial features that had been only considered for the Holocene AHP. Extending the climate simulation several millennia into the future reveals that such pattern scaling breaks when greenhouse gases become a stronger climate change driver.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Climate of the Past.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.- Preprint
(4770 KB) - Metadata XML
- BibTeX
- EndNote
Status: closed
-
RC1: 'Comment on cp-2024-61', Anonymous Referee #1, 07 Nov 2024
The paper from Mateo Duque-Villegas et al. uses MPI-ESM v1.2 for the past 134 ka to simulate northern African hydroclimate and vegetation to reconstruct past AHPs. It aims to construct a pattern scale model to estimate AHPs of the past 800 ka. The model uses forcing variables (insolation, ice volume, and GHG) and is tested against proxy variables such as d18O (vs. 2K T), dP (vs. L*), and vegetation (vs. isotopic depletion and dust). Then, past AHPs are defined as peaks in the pan-Saharan vegetation coverage (%) and analyzed spatially. Here, EOFs capture dominant patterns of vegetation change, which are used to fit a linear model between the forcing variables and the PC1. They state orbitals influence around 66% of the linear model outcome. Next, the pattern scaling is applied and compared against MPI-ESM output, showing a trustworthy approach and extending the temporal extent back to 800 ka. The comparison with the Saporpel record from the Mediterranean does show a good agreement when using some arbitrary thresholding. Last, the pattern scaling approach and their MPI-ESP are used for future SSP scenarios with moderate and intensive GHG emissions for the coming ten kyr. Differences are observed, mainly when the pattern scaling linear model is used for the intense GHG emissions, as this quasi-empirical model has no data example for that.
The paper presents an insightful, well-written approach and uses well-curated figures to show its results. The paper structure is sometimes unusual with literature work and comparisons and discussions within the result section and, therefore, a short discussion section due to the linear progressing type of analysis. I like it, but others can see this differently. The length and the grade of detail are sufficient and allow fluent reading.
The method and the presented results seem logical and reasonable; no significant flaws were detected by my side, even though I am not an expert in GCMs, especially not for this model. Therefore, from my modest perspective, I see the paper as acceptable, but there are some suggestions and comments from my side:
Major comments:
The temporal framework in which the model results are presented is based on glacial cycles and the marine isotope stages, whereas the research target is mainly tropical. There are arguments to see this as problematic, as it can be a north-western perspective that acts as a framework to understand tropical climate, leading to false reasoning about forcing factors. They may also lead to false conclusions when they are used to discussing tropical climates if NH climate implications are applied. In contrast, cycles of the Monsoon Index could simply be counted and labeled, or absolute ages could be used.
The draft presents its results mainly as a cost-efficient estimation of past AHP patterns based on the simple linear fit. However, the fit itself is of interest, as it shows that orbitals are the main drivers of AHPs, not GHGs or ice sheets. Why is this not presented as an exciting result to be discussed?
Vegetation and vegetation feedback are non-linear and have multimodal distributions. However, EOF assumes unimodality and works better with a Gaussian distribution. How is this considered?Minor Comments:
L5: Capitalize African Humid Period (AHP)?
L25: „1.7 ka to 4.2 ka,“ Where are these definite numbers from? There is a reference needed. Also, a broadened perspective on when, where, and how the AHP ends would be helpful (e.g., abrupt/ gradual, eastern vs. western Africa, or N-S transect, e.g., Shanahan et al., 2015)
L110: Marine sediment reflectance is rapidly introduced here and would need some more explanation for the non-marine audience
L115: More wording could be helpful to explain that the output of the model is compared to proxy results and other model insights
L145: Eastern Africa instead of East Africa, as East Africa refers to the colonial name, whereas eastern Africa is the geographical term
L165: If the last AHP, which has the best ground truth so far, is not correctly reconstructed, how do we assume the model works correctly?
L235: I think this is an exciting output of the study as it shows, with a simple linear model, the contributions of the forcing factors to Africa’s climate heartbeat. For the last sentence, I would pronounce the weakening of the orbital forcing without necessarily increasing NH forcing on tropical African climate.
L325: Indeed, pattern scaling is an empirical method, and there is no precursor to having the model trained on, so it is extrapolating; hence, reaction patterns to this GHG forcing are simply unknown.
L375: An AHP SW-NE tilt exists in the Krapp et al. (2021) dataset, foremost in the MAP. It is weak and underestimated compared to the terrestrial observations, but it exists.
Citation: https://doi.org/10.5194/cp-2024-61-RC1 -
AC1: 'Reply on RC1', Mateo Duque-Villegas, 17 Jan 2025
The comment was uploaded in the form of a supplement: https://cp.copernicus.org/preprints/cp-2024-61/cp-2024-61-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Mateo Duque-Villegas, 17 Jan 2025
-
RC2: 'Comment on cp-2024-61', Shivangi Tiwari, 14 Nov 2024
General comments:
In my view, this study is very interesting and relevant, and quite novel. Barring some grammatical problems, the manuscript is well-written in terms of coherence and flow and the figures are well-made. In my view, it is certainly a study which should be published and would be of interest to the paleoclimate community (especially AHP workers). However, it requires some revisions before publication.
There are two major issues that the authors should address:
- The under-estimation of the Holocene AHP is critical. This is not just because the model may be under-representing AHPs in general, because that would hopefully apply to all simulated AHPs and hence not greatly affect the linear scaling. The issue is that the proposed mechanism (unexpected MOC variability) for this under-estimation appears to apply only to the Holocene AHP. It appears to me that similar MOC variability also occurred before the AHP in MIS5e. Does it lead to a similar under-representation of that AHP? In any case, either one or both of the interglacial AHPs are under-estimated but the other two are not. Can a linear scaling model really be applied in this case?
To clarify: my issue is not with the scaling of the orbital forcing, which is evident in Fig. 1a. Intuitively, this would likely lead to a scaling of the AHP representation. My issue is with the ability of your simulations to show this scaling given the imbalanced representation of the different AHPs. - To me, a study of the future where ice-sheets are kept unchanged is meaningless, especially when ice volume is one of three predictors. I’m afraid the point of Section 3.6 is quite lost on me. From my viewpoint, it would be a perfectly good and “complete” study without attempting to simulate the future climate (imperfectly) as well.
Another relatively minor issue is that I would have liked to see more evidence in favor of their scaling approach for ancient AHPs through more extensive comparison with other proxy records or modelling studies. This is discussed briefly, but to me, elaborating this would be most beneficial in reinforcing the applicability of this technique to ancient AHPs.
Specific comments:
L18: Perhaps deMenocal et al. (2000) is not the best reference here, because you mention water bodies and expansion of vegetation cover only.
L22: I don’t think our understanding of the extent and timing of the AHP changes depends on climate simulations (and their discrepancies with records), but instead, it is more to do with the proxy data limitations is well taken. You could highlight the point about the discrepancies in a separate sentence.
L25: The references Blanchet et al., 2021 and Ehrmann et al., 2017 are not really wrong, but perhaps misplaced here.
L32: You should either provide a reference for the second part of the sentence which focuses on climate models, or break this sentence into two and present the second part as a general point.
L54: Both the references are related to the Holocene AHP only, hence misplaced in a paragraph that focuses on ancient AHPs. You could cite the same papers but to say that this is a problem with the Holocene AHP simulations which may extend to the ancient AHPs too (depends on the point you want to make, of course).
L109: Keeping ice sheets unchanged at present day levels is a critical limitation, in my opinion.
L138: This is confusing. What is the simulation offset from: the proxy record or the orbital monsoon index? It looks like both to me (at different times). In Fig. 1f, the model precipitation shows more variability and the proxy record is smoother. I see from the figure caption that the proxy record is smoothened, but it would be helpful to mention that here too.
L157: Is this lag not related to the time taken for vegetation to develop and fully expand over the region?
L164: Wouldn’t the effect of the MOC variability apply to MIS 5e too?
L303: I think it is key to quantify how many of the simulated AHPs do agree with sediment core signals, since that would be the most robust evidence in favour of applying this linear scaling to ancient AHPs.
L327: I think this is a crucial limitation of applying your linear scaling model to the future. Simulating the future with invariant ice-sheets is both unrealistic and meaningless. It is additionally problematic if your linear scaling model has an ice volume parameter. For me, the Section 3.6 does not hold any meaningful results and I do not see the point of including it in the manuscript. (Perhaps the significance has eluded me, and the authors could explain it better.)
L335: Independently of the previous comment, I would argue that it is not correct to say that the simulated pattern “does not resemble any of its AHP predecessors”. The absence of the northward vegetation expansion along the west coast is strange, but hardly the only criterion to be employed. (I see a decent zonally-extended expansion and also a meridional pattern in eastern Africa, for example.)
L336: I don’t think either of the papers cited is appropriate for a comparison (or for showing agreement) here. Neither discusses the time after 9 kyr. Pausata et al. (2020) discuss the future in terms of geoengineering projects only. If you would like to keep this statement, please clarify how those studies have results similar to the differences you’re talking about.
L337: I see that this is the same point I was trying to convey earlier. However, I don’t think it really qualifies to be a “result” of this study, but is instead a foreseeable limitation.
L369-370: This line is unclear. How are you comparing vegetation changes with precipitation changes from a model-data comparison? This is the first mention of any comparison with Scussolini et al. (2019). The results from the comparison should be mentioned somewhere in the Results section before.
Technical corrections:
L19: Please capitalize H and P like “African Humid Periods” (since you abbreviate it).
L30: Consider replacing “much more” with “relatively”.
L34: coastline (singular)
L40: restrict (singular)
L52: Saharan shrinking
L55: Replace “enough” with “higher”.
L57: While I see there is a full description in Section 2.1, it would be helpful to mention the name of the model here too.
L59: I do not think you really evaluate “different AHP responses”, since the focus remains on vegetation cover only.
L60: the large-scale climate drivers
L94: This sentence looks like it should be a continuation from the previous one.
L97: decadal
L110: For GHG concentrations (or something else like this)
Fig. 1: The units should be in brackets and not after a ‘/’ which can suggest division. For eg., “orbital monsoon index (Wm-2)”. This applies to all figures in the manuscript.
Fig. 1 right panel: replace title with “Results from simulations (black) and proxies (colour)”.
L144: I think you should rephrase it better than “dilutes isotopic signal”. From what I’ve learnt, using terms like “dilutes” or “weakens” is discouraged while discussing isotopic signals.
L145: This sentence needs to be rephrased to be grammatically correct (missing subject?).
L148: Replace “proxies” with “proxy records”.
L178: I suggest you rephrase as “and overall, is much drier (about 1 mm d-1) over North Africa...”
L182: Perhaps this could be rephrased to something like “The intensity of an AHP is also reflected in the spatial extent of vegetation cover changes.”
L187: This was a little confusing to me. What exactly is the caveat that you mention? If this refers to what is discussed in lines 190-197, then the lines 187-197 should be in one paragraph.
L198: There is only one AHP during the Holocene (“milder ones” doesn’t make sense).
L210: peak amplitudes of what? Also, this paragraph has too many brackets. Some of the bracketed text would flow as part of the sentence too.
L213: I would rephrase this sentence as “The matrix is centered about its mean by removing the trend in changes from PI and decomposed...”.
L213: What does p refer to here?
L278: Please rephrase “gases data”.
L305: Check citation style.
L308: Do you mean Fig. 6e?
L311: Is D’Agostino et al., 2019 the intended reference here? It doesn’t extend to the upcoming millennia.
L340: The phrase “the simulation may be unique” is too open-ended and pointless. You could rephrase it as “To the best of our knowledge, the simulation is unique...”.
L351: Humidity is not shown or discussed anywhere.
L354-356: Please improve the structure of the sentence.
L415: I would not introduce a new phrase (“desert bias”) in the Conclusions section.
L417-419: Please rephrase these sentences for grammatical correctness.
L422: I would remove the last two sentences altogether.
Citation: https://doi.org/10.5194/cp-2024-61-RC2 -
AC2: 'Reply on RC2', Mateo Duque-Villegas, 17 Jan 2025
The comment was uploaded in the form of a supplement: https://cp.copernicus.org/preprints/cp-2024-61/cp-2024-61-AC2-supplement.pdf
- The under-estimation of the Holocene AHP is critical. This is not just because the model may be under-representing AHPs in general, because that would hopefully apply to all simulated AHPs and hence not greatly affect the linear scaling. The issue is that the proposed mechanism (unexpected MOC variability) for this under-estimation appears to apply only to the Holocene AHP. It appears to me that similar MOC variability also occurred before the AHP in MIS5e. Does it lead to a similar under-representation of that AHP? In any case, either one or both of the interglacial AHPs are under-estimated but the other two are not. Can a linear scaling model really be applied in this case?
Status: closed
-
RC1: 'Comment on cp-2024-61', Anonymous Referee #1, 07 Nov 2024
The paper from Mateo Duque-Villegas et al. uses MPI-ESM v1.2 for the past 134 ka to simulate northern African hydroclimate and vegetation to reconstruct past AHPs. It aims to construct a pattern scale model to estimate AHPs of the past 800 ka. The model uses forcing variables (insolation, ice volume, and GHG) and is tested against proxy variables such as d18O (vs. 2K T), dP (vs. L*), and vegetation (vs. isotopic depletion and dust). Then, past AHPs are defined as peaks in the pan-Saharan vegetation coverage (%) and analyzed spatially. Here, EOFs capture dominant patterns of vegetation change, which are used to fit a linear model between the forcing variables and the PC1. They state orbitals influence around 66% of the linear model outcome. Next, the pattern scaling is applied and compared against MPI-ESM output, showing a trustworthy approach and extending the temporal extent back to 800 ka. The comparison with the Saporpel record from the Mediterranean does show a good agreement when using some arbitrary thresholding. Last, the pattern scaling approach and their MPI-ESP are used for future SSP scenarios with moderate and intensive GHG emissions for the coming ten kyr. Differences are observed, mainly when the pattern scaling linear model is used for the intense GHG emissions, as this quasi-empirical model has no data example for that.
The paper presents an insightful, well-written approach and uses well-curated figures to show its results. The paper structure is sometimes unusual with literature work and comparisons and discussions within the result section and, therefore, a short discussion section due to the linear progressing type of analysis. I like it, but others can see this differently. The length and the grade of detail are sufficient and allow fluent reading.
The method and the presented results seem logical and reasonable; no significant flaws were detected by my side, even though I am not an expert in GCMs, especially not for this model. Therefore, from my modest perspective, I see the paper as acceptable, but there are some suggestions and comments from my side:
Major comments:
The temporal framework in which the model results are presented is based on glacial cycles and the marine isotope stages, whereas the research target is mainly tropical. There are arguments to see this as problematic, as it can be a north-western perspective that acts as a framework to understand tropical climate, leading to false reasoning about forcing factors. They may also lead to false conclusions when they are used to discussing tropical climates if NH climate implications are applied. In contrast, cycles of the Monsoon Index could simply be counted and labeled, or absolute ages could be used.
The draft presents its results mainly as a cost-efficient estimation of past AHP patterns based on the simple linear fit. However, the fit itself is of interest, as it shows that orbitals are the main drivers of AHPs, not GHGs or ice sheets. Why is this not presented as an exciting result to be discussed?
Vegetation and vegetation feedback are non-linear and have multimodal distributions. However, EOF assumes unimodality and works better with a Gaussian distribution. How is this considered?Minor Comments:
L5: Capitalize African Humid Period (AHP)?
L25: „1.7 ka to 4.2 ka,“ Where are these definite numbers from? There is a reference needed. Also, a broadened perspective on when, where, and how the AHP ends would be helpful (e.g., abrupt/ gradual, eastern vs. western Africa, or N-S transect, e.g., Shanahan et al., 2015)
L110: Marine sediment reflectance is rapidly introduced here and would need some more explanation for the non-marine audience
L115: More wording could be helpful to explain that the output of the model is compared to proxy results and other model insights
L145: Eastern Africa instead of East Africa, as East Africa refers to the colonial name, whereas eastern Africa is the geographical term
L165: If the last AHP, which has the best ground truth so far, is not correctly reconstructed, how do we assume the model works correctly?
L235: I think this is an exciting output of the study as it shows, with a simple linear model, the contributions of the forcing factors to Africa’s climate heartbeat. For the last sentence, I would pronounce the weakening of the orbital forcing without necessarily increasing NH forcing on tropical African climate.
L325: Indeed, pattern scaling is an empirical method, and there is no precursor to having the model trained on, so it is extrapolating; hence, reaction patterns to this GHG forcing are simply unknown.
L375: An AHP SW-NE tilt exists in the Krapp et al. (2021) dataset, foremost in the MAP. It is weak and underestimated compared to the terrestrial observations, but it exists.
Citation: https://doi.org/10.5194/cp-2024-61-RC1 -
AC1: 'Reply on RC1', Mateo Duque-Villegas, 17 Jan 2025
The comment was uploaded in the form of a supplement: https://cp.copernicus.org/preprints/cp-2024-61/cp-2024-61-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Mateo Duque-Villegas, 17 Jan 2025
-
RC2: 'Comment on cp-2024-61', Shivangi Tiwari, 14 Nov 2024
General comments:
In my view, this study is very interesting and relevant, and quite novel. Barring some grammatical problems, the manuscript is well-written in terms of coherence and flow and the figures are well-made. In my view, it is certainly a study which should be published and would be of interest to the paleoclimate community (especially AHP workers). However, it requires some revisions before publication.
There are two major issues that the authors should address:
- The under-estimation of the Holocene AHP is critical. This is not just because the model may be under-representing AHPs in general, because that would hopefully apply to all simulated AHPs and hence not greatly affect the linear scaling. The issue is that the proposed mechanism (unexpected MOC variability) for this under-estimation appears to apply only to the Holocene AHP. It appears to me that similar MOC variability also occurred before the AHP in MIS5e. Does it lead to a similar under-representation of that AHP? In any case, either one or both of the interglacial AHPs are under-estimated but the other two are not. Can a linear scaling model really be applied in this case?
To clarify: my issue is not with the scaling of the orbital forcing, which is evident in Fig. 1a. Intuitively, this would likely lead to a scaling of the AHP representation. My issue is with the ability of your simulations to show this scaling given the imbalanced representation of the different AHPs. - To me, a study of the future where ice-sheets are kept unchanged is meaningless, especially when ice volume is one of three predictors. I’m afraid the point of Section 3.6 is quite lost on me. From my viewpoint, it would be a perfectly good and “complete” study without attempting to simulate the future climate (imperfectly) as well.
Another relatively minor issue is that I would have liked to see more evidence in favor of their scaling approach for ancient AHPs through more extensive comparison with other proxy records or modelling studies. This is discussed briefly, but to me, elaborating this would be most beneficial in reinforcing the applicability of this technique to ancient AHPs.
Specific comments:
L18: Perhaps deMenocal et al. (2000) is not the best reference here, because you mention water bodies and expansion of vegetation cover only.
L22: I don’t think our understanding of the extent and timing of the AHP changes depends on climate simulations (and their discrepancies with records), but instead, it is more to do with the proxy data limitations is well taken. You could highlight the point about the discrepancies in a separate sentence.
L25: The references Blanchet et al., 2021 and Ehrmann et al., 2017 are not really wrong, but perhaps misplaced here.
L32: You should either provide a reference for the second part of the sentence which focuses on climate models, or break this sentence into two and present the second part as a general point.
L54: Both the references are related to the Holocene AHP only, hence misplaced in a paragraph that focuses on ancient AHPs. You could cite the same papers but to say that this is a problem with the Holocene AHP simulations which may extend to the ancient AHPs too (depends on the point you want to make, of course).
L109: Keeping ice sheets unchanged at present day levels is a critical limitation, in my opinion.
L138: This is confusing. What is the simulation offset from: the proxy record or the orbital monsoon index? It looks like both to me (at different times). In Fig. 1f, the model precipitation shows more variability and the proxy record is smoother. I see from the figure caption that the proxy record is smoothened, but it would be helpful to mention that here too.
L157: Is this lag not related to the time taken for vegetation to develop and fully expand over the region?
L164: Wouldn’t the effect of the MOC variability apply to MIS 5e too?
L303: I think it is key to quantify how many of the simulated AHPs do agree with sediment core signals, since that would be the most robust evidence in favour of applying this linear scaling to ancient AHPs.
L327: I think this is a crucial limitation of applying your linear scaling model to the future. Simulating the future with invariant ice-sheets is both unrealistic and meaningless. It is additionally problematic if your linear scaling model has an ice volume parameter. For me, the Section 3.6 does not hold any meaningful results and I do not see the point of including it in the manuscript. (Perhaps the significance has eluded me, and the authors could explain it better.)
L335: Independently of the previous comment, I would argue that it is not correct to say that the simulated pattern “does not resemble any of its AHP predecessors”. The absence of the northward vegetation expansion along the west coast is strange, but hardly the only criterion to be employed. (I see a decent zonally-extended expansion and also a meridional pattern in eastern Africa, for example.)
L336: I don’t think either of the papers cited is appropriate for a comparison (or for showing agreement) here. Neither discusses the time after 9 kyr. Pausata et al. (2020) discuss the future in terms of geoengineering projects only. If you would like to keep this statement, please clarify how those studies have results similar to the differences you’re talking about.
L337: I see that this is the same point I was trying to convey earlier. However, I don’t think it really qualifies to be a “result” of this study, but is instead a foreseeable limitation.
L369-370: This line is unclear. How are you comparing vegetation changes with precipitation changes from a model-data comparison? This is the first mention of any comparison with Scussolini et al. (2019). The results from the comparison should be mentioned somewhere in the Results section before.
Technical corrections:
L19: Please capitalize H and P like “African Humid Periods” (since you abbreviate it).
L30: Consider replacing “much more” with “relatively”.
L34: coastline (singular)
L40: restrict (singular)
L52: Saharan shrinking
L55: Replace “enough” with “higher”.
L57: While I see there is a full description in Section 2.1, it would be helpful to mention the name of the model here too.
L59: I do not think you really evaluate “different AHP responses”, since the focus remains on vegetation cover only.
L60: the large-scale climate drivers
L94: This sentence looks like it should be a continuation from the previous one.
L97: decadal
L110: For GHG concentrations (or something else like this)
Fig. 1: The units should be in brackets and not after a ‘/’ which can suggest division. For eg., “orbital monsoon index (Wm-2)”. This applies to all figures in the manuscript.
Fig. 1 right panel: replace title with “Results from simulations (black) and proxies (colour)”.
L144: I think you should rephrase it better than “dilutes isotopic signal”. From what I’ve learnt, using terms like “dilutes” or “weakens” is discouraged while discussing isotopic signals.
L145: This sentence needs to be rephrased to be grammatically correct (missing subject?).
L148: Replace “proxies” with “proxy records”.
L178: I suggest you rephrase as “and overall, is much drier (about 1 mm d-1) over North Africa...”
L182: Perhaps this could be rephrased to something like “The intensity of an AHP is also reflected in the spatial extent of vegetation cover changes.”
L187: This was a little confusing to me. What exactly is the caveat that you mention? If this refers to what is discussed in lines 190-197, then the lines 187-197 should be in one paragraph.
L198: There is only one AHP during the Holocene (“milder ones” doesn’t make sense).
L210: peak amplitudes of what? Also, this paragraph has too many brackets. Some of the bracketed text would flow as part of the sentence too.
L213: I would rephrase this sentence as “The matrix is centered about its mean by removing the trend in changes from PI and decomposed...”.
L213: What does p refer to here?
L278: Please rephrase “gases data”.
L305: Check citation style.
L308: Do you mean Fig. 6e?
L311: Is D’Agostino et al., 2019 the intended reference here? It doesn’t extend to the upcoming millennia.
L340: The phrase “the simulation may be unique” is too open-ended and pointless. You could rephrase it as “To the best of our knowledge, the simulation is unique...”.
L351: Humidity is not shown or discussed anywhere.
L354-356: Please improve the structure of the sentence.
L415: I would not introduce a new phrase (“desert bias”) in the Conclusions section.
L417-419: Please rephrase these sentences for grammatical correctness.
L422: I would remove the last two sentences altogether.
Citation: https://doi.org/10.5194/cp-2024-61-RC2 -
AC2: 'Reply on RC2', Mateo Duque-Villegas, 17 Jan 2025
The comment was uploaded in the form of a supplement: https://cp.copernicus.org/preprints/cp-2024-61/cp-2024-61-AC2-supplement.pdf
- The under-estimation of the Holocene AHP is critical. This is not just because the model may be under-representing AHPs in general, because that would hopefully apply to all simulated AHPs and hence not greatly affect the linear scaling. The issue is that the proposed mechanism (unexpected MOC variability) for this under-estimation appears to apply only to the Holocene AHP. It appears to me that similar MOC variability also occurred before the AHP in MIS5e. Does it lead to a similar under-representation of that AHP? In any case, either one or both of the interglacial AHPs are under-estimated but the other two are not. Can a linear scaling model really be applied in this case?
Data sets
Post-processed data and scripts for "Pattern scaling of simulated vegetation change in North Africa during glacial cycles" Mateo Duque-Villegas https://doi.org/10.17617/3.HQTV1J
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 263 | 76 | 151 | 490 | 23 | 17 |
- HTML: 263
- PDF: 76
- XML: 151
- Total: 490
- BibTeX: 23
- EndNote: 17
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1