Review of “Mid-Holocene ITCZ migration: impacts on Hadley cell dynamics and terrestrial hydroclimate” by Jianpu Bian, Jouni Räisänen, and Heikki Seppä.

This paper presents an analysis of the PMIP4 mid-Holocene (MH) simulations using a set of metrics to quantify changes in the ITCZ and Hadley Cell edge and extent. The paper also includes a broader discussion of the aridity and atmospheric circulation changes in the MH simulations and comparison with available proxy records. The paper is generally clearly written and describes the experiments and results thoroughly. There is a detailed comparison of different methods to define the Hadley Cell edge and strength and the MSE budget. The results will contribute to understanding of MH climate changes in climate model simulations. Overall the paper is a valuable contribution, presenting new and interesting results. I support publication subject to revisions addressing comments outlined below.

General comments:

My main concern is the focus on the annual mean changes. The key changes in the mid-Holocene are associated with seasonal shifts in insolation due to altered timing of perihelion, so that the seasonal mean anomalies will be larger and easier to interpret. Annual changes may involve offsetting summer and winter changes – for example, see Figure 6 of Brierley et al. (2020) mid-Holocene PMIP paper, where many changes in DJF and JJA precipitation are opposite in sign.

I suggest including analysis of the seasonal changes in addition to annual mean. As there is a clear seasonal change in insolation due to orbital changes, the resulting changes in atmospheric circulation and precipitation will be easier to interpret at seasonal time scales, e.g. for the summer monsoons in each hemisphere. It is also possible that MH minus PI Hadley cell changes will differ in Northern Hemisphere (NH) versus Southern Hemisphere (SH) winter given the strong seasonal orbital forcing anomalies.

There is also some apparent confusion regarding the annual mean insolation change due to orbital differences at 6ka relative to pre-industrial. For example, in the abstract it is stated that “orbital forcing increased radiative heating in the Northern Hemisphere” and at line 318, the paper mentions “increased solar radiation in the Northern Hemisphere driven by orbital forcing”. While this is true for the NH spring/summer, the paper presents annual mean results only.

Obliquity changes at 6ka cause annual mean heating at high latitudes versus tropics in both hemispheres, whereas precession of perihelion causes anomalies in seasonal heating in both NH and SH which cancel out for the annual average. It is therefore confusing to present annual mean results but refer to orbital increases in NH insolation and heating.

There may be an annual mean increase in NH temperature in some models – but there is no figure showing this, and it is not evident in the PMIP4 ensemble mean temperature as shown in Brierley et al. (2020) Figure 1: the NH is mainly cooler except for high northern latitudes. Given this, I cannot see how the results show “increased radiative heating in the Northern Hemisphere” for annual averages. Please clarify this.

Specific comments:

Abstract, line 16: Clarify that the wetter NH and drier SH is mainly over land. (Note that this also may vary when considering seasonal changes – see General Comment above).

Line 59: Use of bilinear interpolation – it is normally better to use conservative regridding for fields such as precipitation and mass streamfunction. Please confirm the choice of regridding does not significantly alter the results.

Line 130: As discussed in General Comment above, there would be some benefit to also including seasonal mean results, e.g. for DJF and JJA seasons.  

Line 131: Make clear that you are comparing the CMIP6-PMIP4 PI simulations with observations here. This should also be stated in the caption for Figure 1.

Line 135: According to the legend, Figure 1c shows the multi-model median not the mean – if you are using this to argue that the multi-model mean should be used elsewhere, I suggest modify Figure 1c to show the multi-model mean not median.

Line 159-161: Note that some of the discussion in Reeves et al. (2013) of changes towards wetter/drier conditions is expressed relative to the early Holocene, not to the late Holocene or pre-industrial. It may also be worth including comparison with Petherick et al. (2013) paper about temperate Australian records:

Petherick, L., Bostock, H., Cohen, T. J., Fitzsimmons, K., Tibby, J., Fletcher, M. S., ... & Dosseto, A. (2013). Climatic records over the past 30 ka from temperate Australia–a synthesis from the Oz-INTIMATE workgroup. Quaternary Science Reviews, 74, 58-77.

Figure 1: (c) Caption should cite Adler et al. 2003 for GPCP. (f) Are different dot sizes significant? Explain in caption if so. I also suggest reversing the colour scheme as red is usually dry and blue is usually wet for precipitation anomaly plots.

Table 1: Table caption should be expanded to define all abbreviations used in table and distinguish between Method I and Method II – remind the reader how these differ (using streamfunction values at 500 hPa versus average over 200-900 hPa).

Line 167-168: The methods used to define the ITCZ location need to be briefly described in the Methods section, not just in the Supplement.

Figure 2: What are the red and blue line colours in (a) and (b) panels? Define in caption.

For panel c, either include full names (inner edge, southern edge etc.) or define the abbreviations in the figure caption: “southern edge of Hadley Cell (Edge_S)” etc.

Figure 3: Please either label the models on the x-axis of figures or ensure the order of models in the legend matches the order in the plots. Otherwise, any colour-blind reader will not be able to interpret this figure.

Line 196: Previous studies of global warming – clarify whether these are model or observational studies and whether focused on historical period or future projections or both.

Figure 4 a-f: It is difficult to distinguish the lines based on the colour alone. I suggest using different dot and dash patterns as well as different colours.

Section 4, paragraphs 2 and 3: In this section, you should also compare your results with D’Agostino et al. (2019) and (2020) studies on NH and SH monsoon changes in PMIP mid-Holocene simulations. These studies make use of MSE budget analysis so they are highly relevant. You may also want to mention these studies in the introduction in the section discussing the MH monsoon changes (lines 35-40).

D'Agostino, R., Bader, J., Bordoni, S., Ferreira, D., & Jungclaus, J. (2019). Northern Hemisphere monsoon response to mid‐Holocene orbital forcing and greenhouse gas‐induced global warming. Geophysical Research Letters, 46(3), 1591-1601.

D’Agostino, R., Brown, J. R., Moise, A., Nguyen, H., Dias, P. L. S., & Jungclaus, J. (2020). Contrasting southern hemisphere monsoon response: MidHolocene orbital forcing versus future greenhouse gas–induced global warming. Journal of Climate, 33(22), 9595-9613.

References:

Line 472: Publisher details missing from Nicholson book reference.

terrestrial hydroclimate”

By Bian et al.

Overview:

This study investigates the effects of the northward migration of the Intertropical Convergence Zone (ITCZ) on the Hadley cell and global hydrological patterns during the mid-Holocene, around 6,000 years ago. This period, known as the "Green Sahara," experienced significant climatic changes, with increased precipitation in typically arid regions. The study utilizes simulations from the PMIP4-CMIP6 archive to analyze shifts in the ITCZ and changes in Hadley cell characteristics, revealing a contraction and weakening of the northern Hadley cell and an expansion and strengthening of the southern cell. These dynamics contributed to wetter conditions in the Northern Hemisphere and drier conditions in the Southern Hemisphere. This study underscores the complex interactions among orbital forcing, ITCZ migration, Hadley cell dynamics, and terrestrial aridity during the mid-Holocene. While climate models provide valuable insights, recognizing their limitations and the uncertainties in simulations and reconstructions is crucial. Continued research and model development are necessary to enhance our understanding of past climate changes and their implications for future climate scenarios. In general, I find the paper is well written and could be published after revision.

My main concerns:

1. What are the new findings of the study? The change of Hadley cell, ITCZ, and precipitation patterns in the Mid-Holocene were well reported in previous studies, and especially the Mid-Holocene ITCZ migration and precipitation patterns have been reported in the authors’ previous published paper of Bian et al. (2024). Maybe the moisture static energy budget could be interesting to understand the dynamics of changes in Hadley cells. The author should clearly state what is new in the introduction.

Bian, J., Räisänen, J. Mid-holocene changes in the global ITCZ: meridional structure and land–sea rainfall differences. Clim Dyn 62, 10683–10701 (2024). https://doi.org/10.1007/s00382-024-07470-1

1. Why is the ITCZ migration leading to the change of Hadley Cells? It could also be the Hadley cell leads the ITCZ migration. Where I can see the evidence of ITCZ migration leading to the changes in Hadley Cells?
2. The asymmetry responses of Hadley Cells in the Northern Hemisphere and Southern Hemisphere are interesting. It would be great if the authors could show a more dynamic understanding of the asymmetry responses, especially more focus on the moisture static energy budget in the revision.
3. In most of the analysis, this study uses multiple model ensemble mean, I am wondering whether there are any models and realizations that could better capture the reconstructed precipitation patterns, or how different the simulated precipitation patterns change among different models. For example, does a model with a larger Hadley Cell northward shifting and intensifying show more precipitation increases in the Northern Hemisphere extropical monsoon regions? I think some more discussions on the model uncertainties might further help to understand the dynamic links between the large-scale circulation change and precipitation patterns.