Summary

The submitted article is very well written, is comprehensive in its treatment and has clear graphics. The synoptic compositing is effective in advancing process understanding. What would help advance process understanding would be the study present what role variable meltwater retention played in the extreme days and seasons, provided that the retention model has a realistic response to melt intensity and snowfall from the previous year, the latter factor (snowpack) to represent snow retention capacity.

**high level critique** in no particular order of importance...

Consider to analyze the rainfall for the 2015 and 2016 events from CARRA data?

ERA5-Land reanalysis dataset, what about coarse resolution, how its downscaled is important and how representative of local gradients is a big question

147, temperature lapse rate obtained from the daily ERA5 pressure level data, how do the numbers compare with Fausto et al 2009 'A new present-day temperature parameterization for Greenland'?

263 "78% of the runoff on both days" very interesting, perhaps unique finding, if I understand that rainfall was the majority of runoff. If so, try to highlight the result in abstract and conclusions

314 "rainfall exhibited a 2.2-fold increase from 1951–1960 to 2010–2020" try to highlight the result in abstract and conclusions

fig 6 suggest instead of °C/decade, try "change" or "trend" as the trend slope from regression multiplied by the number of years. Then possibly in abstract and conclusions can state temperature increased by _°C over the period...same with precipitation parameter trends

329 "top three daily runoff events being caused primarily by rainfall", discuss retention on those dates, how depleted? saturated snow?

334 "unclear relationship", what about retention findings from model?

**low level comments**

"io" means "instead of"

abstract

Main Text

"local glaciers" io "peripheral glaciers", peripheral is a recent language mistake we can fix by using a more accurate term

"relatively small area of Greenland (4%)," depends on level of connectivity, see doi:10.5194/tc-6-1483-2012 and use a range of % and cite the article

37 "from local glaciers" io "from glaciers"

40-50 is also possible to find reports of infrastructure bridge damage near Nuuk, for example in Kobbefjord after rainfall in 2022 https://x.com/NuukNERO/status/1573959848991014913

66 cite also Ahlstrøm 2017 Sci Reports

83 add day/month the aws installed

90 perhaps add Williamson PNAS or other supporting work outside of Japanese publications

188 "agreement" io "good agreement"

190 what is RMSE after bias correction, would be smaller than 0.07?

197 "runoff was measured in the summer periods during 2017–2019 at 1.4–2.0 km from the glacier terminus (Mankoff et al., 2020;" how is the Mankoff data used? I think that is not a measurement but a model?

214 "slightly" add % difference

218 "good agreement" add % difference

265 see also Fausto GRL and Frontiers from 2016 for possible citation in addition to (Nghiem et al., 2012).

Fig 5 red stars do not seem needed as the maximum is illustrated already

Fig 5 runoff "fraction" seems better than depth

301 "glacier mass budget surplus" io "positive glacier mass balance"

303 "climatic mass balance" is more conventional than "glacier mass balance", see Glossary of Glaciology, IAHS Cogley

355 "rain event at Summit station on the Greenland ice sheet in the summer of 2021" was more like "light rain" or "mist" which ocurred after snowfall, see Summit Figure S5a in Box study Supplement and relevant discussion

450 good point "atmospheric circulation patterns are not captured by the Earth system models used in CMIP5 and CMIP6"

The article is very well written and understandable. Its scientific conclusions are sound and the work is well motivated by the lack of discharge data going back into the past. Some more details in the methodology could help the understanding of the reader (details below). The discussion from the point of view of synoptic and climatic controls is enlightening, but some of the suggested causal linkages are more implied than clearly demonstrated (details below).

Scientific comments:

450 - The authors claim that the pressure patters in fig. 9 ‘trigger’ the high runoff events, which may well be true, but as far as the work that is shown goes, the linkage is only demonstrated in one direction, namely that the pressure pattern is present when a runoff event occurs. It is not demonstrated that every time the pressure pattern occurs, a runoff event follows. It’s not imperative in the context of the study to do that, but the choice of the word ‘trigger’ is maybe overstating the depth of the analysis somewhat.

With respect to the association between GBI and higher surface temperatures, the manuscript talks exclusively about the role of warm air advection, mostly in connection with cited previous work. I wonder  whether decreased cloudiness and higher shortwave radiation also may play a role occasionally, or what the relative importance of the two mechanisms is (e.g. 445, 475).

Since the composites in fig. 7 contain only very few events, it would be quite nice if the text commented very briefly also on how representative they are for the individual events. In particular, the claim about the atmospheric rivers driving the runoff events, is it true for every single one of the 3 events?

Technical comments:

A list of variables measured by the AWS would be nice.

In the methodology, I would appreciated a bit more clarity on whether the non-glaciated part of the catchment is included in the modelling, in particular since rainfall is found to be important in the high-runoff scenarios. If the area is too small to make an appreciable difference, this can just be stated.

A little more detail on the tuning of the rainfall estimates from ERA to the glacier surface elevation changes could also help the understanding - e.g. is the whole year taken into consideration (suggested by fig. S4a)? Then how is the snow density calculated / taken into account?

In the model description (3.1), I would find it clearer to say ‘daily averages’ instead of just ‘daily values’ (if indeed it is daily averages that are being used). A short comment on whether the strong nonlinearity in the Stefan-Boltzmann Law is problematic or not at that level of temporal discretisation might be helpful.

The sequence of equations 7-9: Why not directly just use T_z? Also, does the calibration of ERA5 temperature happen after the lapse rate adjustment to the elevation of SIGMA-B?

110 - “The conductive heat flux, 𝐺, (W m−2) was calculated from the temperature profile of the subsurface snow/ice#: evokes the impression that the subsurface temperature profile is an input (and where would that information come from?), when in reality it is just part of the model.

55, 300, 420 - When discussing the role of snowfall, it becomes clear only later in the text that in the context of its importance for ablation it is its effect on albedo in the summer that is referred to (the reader may first think of winter accumulation). This could be made a bit clearer (e.g. in 300).

445 - “increase in annual runoff since 2000 coincided with the years with the top-ranked summer GBI”: is a little unclear, if I interpret fig 9 correctly, the time after 2000 is both when the top-ranked GBI years occur and when the years with highest runoff occur, but it is not necessarily a year-by-year coincidence, i.e. not every year with top-ranked GBI has top-ranked runoff.

Fig 9: The nature of the fields displayed is not completely clear to me. The anomalies are with respect to averages over what time spans? And the ‘regression anomalies’ - I presume this is the regression coefficient of Z500 with respect to GBI?