General comments

In this paper, Moore and colleagues have thoroughly analyzed the signal of the Holocene 8.2 ka event in hydroclimatic proxy records from the tropics. The proxy-based signal is compared to simulation results obtained with the isotope-enabled iCESM global climate model. In the compilation, proxy records from different environments are considered: marine sediment records, lake sediment records and speleothems. As such this work  extends the compilation recently published by Parker and Harrison (2022), who focused on the 8.2 ka signal in speleothem records. Innovative aspects of this manuscript are the extensive analysis of the impact of age uncertainties and the comparison of the proxy-based hydroclimatic anomaly with a state-of-the-art isotope-enabled model simulation of the 8.2 ka event. The paper is well-written, with a clear structure, and includes high-quality figures. The main result is a convincing proxy-based overview of the hydroclimatic response to the 8.2 ka event in the tropics, showing clear regional variability. In my view, the manuscript requires some minor revisions, mostly associated with the detection methods used and the climate model experiment. I provide details below.

Main comments

Introduction, Line 59. “This period occurred during the otherwise stable Holocene epoch (11,700 years ago to present) and was driven by the discharge of around 163,000 km3 of meltwater from proglacial Lakes Ojibway and Agassiz (remnants of the Laurentide Ice Sheet) into the North Atlantic”. The volume and source of the freshwater perturbation are actually still under discussion. For instance, the volume of the proglacial lakes is under discussion (Törnqvist and Hijma, 2012). In addition, Gregoire et al. (2012) argue that a collapse of the “ice saddle” over Hudson Bay could have played an important role in forcing the 8.2 ka event. It is important to make the reader aware of this uncertainty. See also the recent discussion by Aguiar et al. (2021). Besides, it is confusing to refer to Lakes Ojibway and Agassiz as “remnants of the Laurentide Ice Sheet”, so I suggest removing this part of the sentence.

Section 2.3.1. MM method. I propose including a schematic figure explaining how the MM method of detection works in practice, using two examples: one example with multiple events of the same sign and one example with multiple events of different signs. I am thinking of an extended version of Morrill’s Figure 2. It is not clear to me what the actual modification is to the Morrill method. Please specify. If feasible, including such a schematic for the actR method would also be helpful for readers not familiar with this type of changepoint analysis.

Section 2.4. Please make clear that the experimental setup for the iCESM simulation of the 8.2 ka event does only partly follow the PMIP4 design reported by Otto-Bliesner et al. (2017). In the PMIP4 design, the 8.2 ka simulation starts from an experiment with fixed forcing for 9.5 ka instead of 9 ka as is done here. In addition, in the PMIP4 design the freshwater hosing is applied in the Labrador Sea instead of across the entire northern North Atlantic.

Discussion. In some regions, for example the Caribbean and SE Asia, there are records without any detected change located close to records with a clear signal for the 8.2 ka event (see for instance Figure 2). How to interpret the absence of a signal in these records without significant change? It would be insightful to discuss the possible reasons for the absence of a signal.

Section 4.2. Simulated 8.2 ka event. The results of the last 50 years of the “hose” experiment are taken to represent the modelled 8.2 ka event. The mapped difference between “hose” and “ctrl” is used, for instance in Figure A2 and in the model-data comparison.  It would be informative to know how the climate evolved through time in “hose” relative to “ctrl” (for instance related to detectability in the model result, see next point), so I propose including additional figures with modelled time-series of hydroclimate for the key regions shown in Figures 4 to 7. These additional figures could show 100-year time-series of both “ctrl” and “hose”.

Detectability of the simulated 8.2 ka event. The question of detectability of the 8.2 ka event is not only relevant for proxy records, but also for the model results. The difference between “hose” and “ctrl” includes anomalies produced by both internal variability and forced variability (i.e. by hosing). Ideally, one should not perform just one simulation for the 8.2 ka event as is done here, but rather an ensemble experiment in which the members differ only in initial conditions and have identical freshwater forcing (hosing). The ensemble mean allows then to analyze the forced response and to separate it from the internal variability. I refer to Wiersma et al. (2011), who performed this analysis for the temperature response associated with the 8.2 ka event. I realize that it is probably not feasible within the framework of this study to perform several additional ensemble members with iCESM, but in my view the aspect of detectability in the model results should also be discussed in the paper. In addition, I suggest performing a statistical test to determine what results of “hose” are significantly different from the “ctrl” climate, and to include only those significantly different results in the model-data comparison.

Other comments

Line 87. Why is it a critical tool? Please elaborate.

Line 104. How is this sensitivity to hydroclimate determined?

Line 151. Why 10 years? On what is this based?

Line 166. Why 50 or 100 years? Why not taking just 50 years?

Line 183. In the actR method, the time window for detection (7.9 to 8.3 ka) is different from the window used in the MM method (7.9 to 8.5 ka). Why this difference and what is the consequence? In addition, is there also a minimum duration for detection in the actR method?

Line 212. Are the forcings for the “ctrl” simulation identical to the 400-year-long 9ka simulation? If not, what are the differences? And is the climate stable in “ctrl” or is there is there still a trend in the surface conditions, signifying adjustment to the different forcings?

4.3 Data-Model comparisons. It is noteworthy that the regional structure of the 8.2 ka event found in this study resembles the hydroclimatic anomaly in a simulation of the Younger Dryas cold event in which freshwater forcing applied in the North Atlantic also plays an important role (Renssen et al. 2018). The hydroclimatic response for the Younger Dryas shows wetter conditions in the Caribbean, SE South America, Southern Africa and Madagascar, but drier conditions in S Central America, the Arabian Peninsula and SE Asia, broadly consistent with the proxy-based signal of the 8.2 ka event provided in the present paper in Figure 2.

Line 238. “… a lack of agreement of the sign or presence of an event”. Do you mean a lack of agreement between the two detection methods? Please clarify.

Figures 2-7. The grey symbols are very hard to see, so I suggest improving their visibility.

Figures 3-7. What do the grey isolines represent? Please explain.

Figures 4-7. In several cases, there are no proxy records of a specific type in a region (for example marine records in East Asia, Figures 4c and f). It is not very meaningful to show the simulation results in these cases, as there is no data-model comparison possible. So, I propose to only show the maps of key regions if there are proxy records available for the data-model comparison.

Figure 5. Legend is missing.

Figure A2a and b. According to the figure caption, the contours in these figures indicate the “range of temperatures in the “ctrl” simulation over the full 100 years”. It is not clear what temperatures these isotherms represent, so I do not see how these contours are useful, and I suggest removing them from the figure.

Additional references

Gregoire, L. J., et al. (2012) Deglacial rapid sea level rises caused by ice-sheet saddle collapses. Nature 487:597 219-222. https://doi.org/10.1038/nature11257.

Renssen, H., et al. (2018) The global hydroclimate response during the Younger Dryas event. Quaternary Science Reviews 193, 84-97. https://doi.org/10.1016/j.quascirev.2018.05.033

Törnqvist, T.E., Hijma, M.P. (2012) Links between early Holocene ice-sheet decay, sea-level rise and abrupt climate change. Nature Geoscience 5, 601-606. https://doi.org/10.1038/NGEO1536`.

Wiersma, A.P., et al. (2011) Fingerprinting the 8.2 ka event climate response in a coupled climate model. Journal of Quaternary Science 26, 118-127, https://doi.org/10.1002/jqs.1439.

The study by Moore et al. compilated global hydroclimate proxies for the 8.2ka event in the tropics and subtropics and compared them with the hosing simulation by the state-of-the-art isotope enabled CESM.

Major novelties:

1. They developed an updated compilation of high-resolution, continuous, well-dated proxy datasets. This is important to the broad paleoclimate community.
2. They introduced the use of the Abrupt Change Toolkit in R (actR) for event detection, which better accounts for age model uncertainties in proxy records. As a result, they quantified the starting, ending, and duration of the 8.2ka event.
3. They revealed a more complex, regionally specific hydroclimate response pattern rather than a simple hemispheric dipole in the 8.2ka event.

However, the paper lacks depth in discussing the source of model-data differences, regional hydroclimate mechanisms, and the responses and of d18Op, making it feel dry due to excessive qualitative descriptions of proxy and modeling results. In my opinion, it could be published in climate of the past, but a list of concerns should be addressed.

Major concerns:

1. Condense the proxy and model results description while enhancing analysis of model-data differences. Focus on presenting actR results primarily, with MM results moved to supplementary materials for greater conciseness. This paper's unique contribution lies in the detailed regional data-model comparison, but thoughtful discussions lack. For instance, the d18Op responses in East Asia during the 8.2ka event exhibit an east-west dipole pattern, contrasting with the uniform enriched isotopic signal seen in the Heinrich events. Despite similar hosing experiments, it is intriguing to explore why such discrepancies exist between these events.
2. The data-model comparisons are necessarily quantitative rather than qualitative, particularly for speleothem d18Op records. Otherwise, why use the isotope-enabled model? It would be beneficial to understand if changes in d18Op are caused by the water isotope or precipitation seasonality.

Minor:

Line 6:  "event detention methods" should be "event detection methods"

Line11: "decadal to multi-centennial timescales" should be: "decadal-to-multi-centennial timescales"

Line 33: “strong strong” should be “strong”

Line 253: add “A total of 61”

Fig. 3. The shading should be difference between control and hosing, right? The caption is confusing.

Fig 5. No color bar