This study examines the changes to the Indonesian throughflow (ITF) under two solar radiation management (SRM) scenarios – Solar Dimming (SD) and stratospheric aerosol injection (SAI). The SRM outcomes are compared to the SSP2-4.5 and SSP5-8.5 scenarios. The study confirms previous work that shows the ITF decline in the 21^st century is primarily driven by changes to Pacific Upwelling, with the tropical easterly wind changes a secondary component. Furthermore, SD shows a similar decline in the ITF to SSP2-4.5, but the ITF decline in SAI is still similar to SSP5-8.5 (despite the net anthropogenic radiative forcing in SAI being similar to SSP2-45). This is because in SAI, the wind-driven component also declines greatly.

The ITF is likely an important metric to track in SAI simulations. However, the climatical and biogeochem importance of ITF and how these change with respect to GHG forcing or SAI is not well established in this paper. Below, I suggest some broader ideas for the authors to address followed by line-by-line suggestions through Line 300 (for Line 300 to the end, please make similar adjustments as stated previously).

1. In the Introduction, the authors could better clarify the importance of the ITF, what drives the ITF, how these drivers are projected to change under GHG and thus why ITF is projected to decline, what does SD and SAI research show for Pac-Ind variability that is relevant to the current study, and clearly state the main objectives of the paper. Also, the Intro and Methods could better explain the different components of ITF – I don’t know if Buoyancy is an additional component to wind and upwelling, or if buoyancy is another way to calculate the full ITF transport.
2. The significance of trends and changes to the ITF transport are not detailed in the first half of the Results. Furthermore, when Wilcoxon stats are introduced, it is unclear what data is being compared (the monthly model-mean from 202001-209912?) and how the authors are considering the multi-model spread which is quite large compared to the variability in the multi-model mean. Furthermore, for many ocean variables there is usually autocorrelation, please explain how this is addressed in the sample size.
3. For each Results section, the main points are lost. Rather than just listing features of the relevant figures, please note how these features impact the ITF and its components and how these changes are consistent with other studies or if they are unique to this study.
4. In total, the amount of typographical errors, incomplete or run-on sentences, paragraphs without a clear point, are unfortunately distractions to the reader. As a reviewer, it’s hard to address the main points of a paper when the review process becomes just an edit of the text.

As is, I cannot recommend this study for publication. Though, I hope my comments are useful and will aid in your next submission.

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Line 15-20 – the short summary is not clear and lacks relevant details

Line 32 – include historical time period.

Line 36 – What’s the error?  Bc if SSP2-4.5 is 23% down, and G6solar is 19% down and G6sulfur is 28% down, we are talking about a magnitude 4% and 5% from SSP2-4.5 – which may not be a sig difference.

Line 38 – 38% - 65%  not “~”  

Line 45 – remove “of”

Line 49-52 – What are some examples of the ITF role in global climate? Many who read this paper will not be experts of the ITF, or oceanography – I think the introduction needs to more clearly explain the climatical importance of the ITF, its projected changes under SSP, what that means for the climate and biogeochem, etc.

Line 84 – are you referring to GCM simulations with ~1 deg ocean?

Line 91 – what defines “high-resolution”

Line 106 – what is meant by “imperfectly”

Lines 112-114 –What do you mean by “… these particular methods are unlikely to ever be done” --- I presume you mean this exact G6Sulfur SAI strategy is unlikely to be what is chosen if SRM is ever used in the future.  This sentence can be re-worded to more clearly state that ongoing research is examining a multitude SAI strategies (how much, at what latitude, at which altitude, etc) to reduce the equator-to-pole cooling bias.

Line 114 – add “atmospheric” to read: Simulated tropical atmospheric circulation

Line 115 – replace “;” with “.” And start new sentence: Under SD, the seasonal …

Line 115-123 – can you be more specific to the changes to tropical Pacific atmospheric circulation due to SD and SAI (or SRM in general)? And, it’s not clear to me why citations about NA hurricane numbers and CAPE under SRM are relevant to this study.

Line 125-134 – I don’t think this paragraph is necessary.  Perhaps only a sentence is needed to state that the AMOC under SRM has been looked at.  I would rather have another paragraph explaining tropical pacific/Indian ocean changes under SRM and more details about the ocean drivers of ITF.  That said, Lines 446-452 compare the continual downturn of ITF to research that shows that AMOC can recover under SRM – this is a good comparison to make at this stage of the paper.

In general, the intro could use more details about atmo circulation and how that changes under GHG and SRM. More about ITF and what drivers can cause changes to it (bc many geoeng don’t know ocean and ITF).  For example,  “this study will show how SRM can change these drivers of ITF”. Some details are in the methods, but better placed in the introduction.

Line 136 - 137 – replace explore with examine and remove the clause “explore the drivers of these changes”

Line 137-138 suggestion: … 21^st century and consider the transport differences between the GHG-forced scenarios (SSP2-4.5 and SSP5-8.5) and the SRM scenarios (G6solar and G6sulfur).

Line 159 – why aren’t G6 scenarios particularly realistic? And as a follow-up, why should the current study and its results be considered, if the simulations are not realistic?

Line 197-208 – This explanation of the GHG forced changes to deep ocean upwelling and their impact on ITF would be a good addition to the revised introduction.

Line 211-212 – replace “in most studies (“,   with: … in previous studies (e.g., Clarke …

Line 213 – define steric sea level height

Line 214 – “should also drive”, I’m not sure what is meant by this phrase

Line 217 – replace “sharp” with eastern?

Line 218-220 – here ITF transport is defined as the difference btw westward and eastward transport along the northern and southern flanks… just below ITF transport is defined by DBP and EIO density change (above by Sverdrup balance and Pacific upwelling).  Why all of these? What do each tell us about ITF?

Line 236 – is wind driven ITF just the Island Rule transport calculation?

INCLUDE +- 1 SD with respect to ensemble members in all values. For the 2080-2100 minus historical period, we need to know significance! It’s likely that there is lag-1 autocorrelation in these time series too and that needs to be accounted for when defining sample size. And trend values and significance.

Line 242-245 – What are the trend values (for all ITF transport components)? & Calculate the significance of the (linear) trend lines. Because it looks like there is a negative trend in the wind driven component for both SSP2-4.5 and SSP2-8.5, but it may not be significant.

Line 250-252 – These values, as all values in this paper should have a statistic attached to them that details the model spread (easiest would be +- 1 SD wrt model spread); and if comparing between SRM and the SSPs there needs to be a significance test in order to attach some level of confidence to the findings.

Line 252-253 – how can both wind and upwelling contributions to ITF be higher? Their sum is ITF transport, so if one contribution goes up, the other must go down?

Line 261-264 – Should the buoyancy forcing calculation of ITF be more similar to the results from the Amended Island Rule? It’s not clear to me if this is a component of ITF or another way to measure ITF. I’m not sure what is the main point/conclusion of this paragraph

Line 264 – “No obvious trend” – you need to calculate the trend and determine whether it is significant

Line 277-278 – It looks to me like the upwelling contribution to ITF transport is not much different between SAI and SD – again a statistical test will confirm this.

Line 286-287 – it may be that G6sulfur total ITF transport averaged from 2080-2100 is lower than SSP2-8.5, but I doubt it is significant given the variability of the time series.

Line 287-291 – again, the time series shows much variability in the multi-model mean (and certainly in the multi-model spread) that I don’t think there is a significant difference between the buoyancy forced ITF transport in any of the scenarios.

Figure 3 needs error bars. And it would be easier to quickly assess by using the same colors for each scenario as in Fig 2.

Lines 293 – there needs to be a detailed explanation of what is causing the decline in upwelling relative to Historical – as well as why the upwelling becomes downwelling north of ~20N. In general, rather than state what the plot shows, state what the plot means in relation to the main points of the paper.

Figure 4 – insert a panel in the top left that is just the Historical mean wind stress curl so that it is more easy to interpret the changes from this mean state. You could also just make all non-significant values white. Removing the stippling (and adjusting the saturated colorbar) will improve the figure’s aesthetic.

Lines 327-330 – Can you explain how these changes in wind stress curl impact the ITF transport changes? – In general for this paragraph, it’s unclear to me how these various changes to wind stress curl across the basin will impact ITF. I am unable to decipher the main point(s) of this paragraph.

Lines 346-354 & Table 2 – What is the acronym TRN? For the Wilcoxon signed-rank test, how do you account for model spread at each month? For example, I’m having difficultly being convinced that the 0.23 change from G6-solar to SSP5-8.5 is significant given that large mult-model variance compared to the signal. Could you elaborate on this stat test and how the model spread is accounted for?

Lines 368-384 – Please clarify the main point(s) of this paragraph and relate the significance of upwelling changes to ITF transport.

Figure 5 – Just mask out in white the non-significant areas and increase the colorbar range so the stat sig areas are not saturated.

Lines 394-420 & Figure 6 – Similar comments to above.

Summary and Discussion – These paragraphs are easier to understand. To improve the clarity of the whole paper, these main points should be established as the goals of the paper in the Introduction and then addressed throughout the Results. As the paper stands now, it is difficult to determine the main points and how the results address these points.

Line 467-469 – I missed the analysis where wind driven transport is compared between models? Given the multi-model range from Fig 2, it seems like the models would have some disagreement with respect to wind driven transport.

Review of "The Indonesian Throughflow Circulation Under Solar Geoengineering" by Chen et al

In this manuscript, the authors analyse the changes in the ITF in two sets of GEOMIP6 simulations, with solar dimming and with stratospheric aerosol injection. They find that the major changes are due to upwelling in the Pacific Ocean, and not so much due to changes in wind stress. 

This is in principle an interesting result, but I wonder whether it warrants a full manuscript by itself. The results are relatively 'thin', and there is very limited connection to how the changes in ITF impact other parts of the tropical ocean systems. I therefore encourage the Editor to carefully consider whether there is enough 'scientific meat' to the research question of ITF changes under geoengineering scenarios.

If the Editor does find the Research Question sufficiently relevant, then I have a few major concerns that I think should be addressed before the manuscript is ready for publication

1. The authors state that the ITF flow is too complex to be measured directly, but that is only (to some extent) true in observations. In model simulations, it is fairly trivial to simply integrate zonal and meridional transports, even more so in the coarser-resolution simulations of GEOMIP than in high-res simulations. I therefore really don't understand why the authors need to invoke buoyancy- and wind-stress based proxies of transport, if they could also measure transport directly

2. While relations with ENSO and other climate variability modes is discussed in the last section, there is no analysis of it. I'm surprised, as the effect of Geoengineering on ENSO is one of the many outstanding concerns. The argument that ENSO-analysis can't be done because the models are unforced is not very strong; there have been plenty of CMIP ENSO analyses. 

3. There is very little mention of the fidelity/skill of the GeoMIP simulations in this region. Only the mean transport is compared, but what about other EOVs like SST etc?

4. On line 238, the authors compare the wind-driven ITF of Fig 2a to the INSTANT observations of Sprintall et al; but these direct observations also include the buoyancy component so should be compared to Fig 2c; in which case the agreement is much poorer. 

5. The explanation of the results in terms of climate physics is relatively limited. Most of the arguments in e.g. lines 313-334 are fairly handwaving and/or descriptive and could be substantiated by more careful and quantitative analysis. 

Minor comments:

-line 19L state that this is the ITF water transport

- line 19: in which way 'similar'?

- line 57: the word 'compensating' is very confusing here. Agulhas leakage and ITF don't compensate each other

- line 58: is 'flush' the best word here?

- line 65: the use of 'flux' and 'transport' in one sentence raises the question whether these concepts are the same or not

- line 80: The flow in the ITF is grossly simplified here. I strongly encourage the authors to be a bit more specific about the different pathways; and/or to show a model domain?

- line 84: which simulations are meant here?

- line 99: how is this transport observed?

- line 112: why are these particular methods unlikely to be ever done?

- Lin 159: why are the G6 scenarios not particularly realistic?

- line 185: is 'dormant' the right word?

- line 224: It's unclear whether these variables are calculated as a function of time, or using time-mean fields

- line 227: is this lever of 1200 m also an appropriate choice here?

- line 229: is this the difference in spatially averaged densities?

- line 268: what is meant with a 'scheme' here?

- line 448/449: refer to where this is shown in the analysis