In this paper, the authors combine the JULES model, which solves the glacier energy balance, with OGGM, which simulates ice flow, and investigate the mass balance over 500 tropical glaciers in the Vilcanota-Urubamba basin in Peru. Specifically, the authors calibrate the surface energy balance model parameters based on 30 glaciers during the period of 2000-2018 and project the mass balance for all glaciers in the region until 2100 with RCP4.5 and RCP8.5. They find that sublimation plays a minor role in glacier evolution at the basal scale, and their mass balance projections are more conservative than previous models. For example, the JULES-OGGM model estimates that 17% of the ice mass will remain by 2100 under RCP4.5, while other models (GloGEM and MAR2012) predict this number to be only 2%.

The manuscript is well written and provides a valuable addition to the current literature of physics-based glacier models, and glacier modeling in general in the region of the tropical Andes. However, I believe that the authors need to provide more information on the climatic input data used in the surface energy balance model. I also suggest that the authors add a sensitivity study for the input data (especially for albedo). Comments and suggestions are given in the list below.

Major comments:

JULES model input parameters: One of the main challenges when using surface energy balance modeling is obtaining the required input data. The authors mention that the data for the other meteorological variables (other than temperature and precipitation) were “generated by resampling (repeating) the 1980-2018 WRF simulations to produce a continuous 2019-2100 time series” (lines 131-133). By not using predictions from CMIP5 for these variables (radiation, relative humidity, wind speed, etc.), the authors are not using future climate information, but rather (randomly?) resampling the current climate for those variables. Hence, I am wondering about large biases in their model input data for the surface balance model. Can the authors please elaborate on their reasoning and discuss biases? Please also provide more information on the resampling procedure. Have the authors performed a sensitivity study on the input data?

Albedo modeling: The authors mention a poor performance in the WRF albedo representations (lines 363-375). In particular, WRF largely overestimates the albedo. Hence, it is not surprising that the JULES-OGGM model shows more conservative mass balance projections for 2100 than other models (e.g., GloGEM, MAR2012, Figure C1). However, the authors implemented many improvements to the glacier modeling procedures in comparison to previous studies (lines 524-528). Hence, I find it hard to estimate whether the more conservative estimates stem from the problematic albedo modeling and resampled model input data, or whether these are actually more realistic estimates for glaciers in this region. Have the authors performed sensitivity tests?

Minor comments:

Abstract: Please mention the grid spacing of your model in the abstract.

Page 8 line 148-151: Do Dussaillant et al. (2019) provide yearly or seasonal data? Please specify.

Page 8 lines 165-170: Can the authors provide details on how the turbulent and latent heat fluxes and the ground heat flux were calculated?

Page 5 lines 121-122: “Grid spacing” and “resolution” refer to two different length scales and should not be used interchangeably (e.g., Grasso, 2000; Stull, 2015). It would be more appropriate to use “grid spacing” here and for similar cases.

Page 6 section 2.4.1: Can the authors please add some details on the start dates for summer and winter periods in the model?

Page 11 lines 225-226: How did the authors come up with 10 grid box nodes with an equal spacing of 167 m elevation for an elevation difference of 2500 m between zmin and zmax? Please explain.

Page 11 lines 236-238: Please provide details on the adjustments that were used for the shortwave radiation.

Page 11 line 240: typo

Page 11 lines 247-248: Have the authors used 10 JULES grid boxes for every glacier or used less grid boxes for glaciers that don’t span the whole range of zmax-zmin?

Page 12 lines 301-303: Are the results (section 3) based on one set of parameters for all glaciers, or was one set of parameters chosen per subregion (R1-R10)? Please specify.

Page 16 lines 356-362: Have these two glaciers been part of the 30 glaciers used for calibration?

Page 17 pages 363-375: WRF albedo modeling: The authors observed that the WRF-modeled albedo rarely falls below 0.8, but the observed albedo falls as low as 0.2 by the end of the dry season. The authors are using the WRF setup from Potter et al. (2023), who are using the Noah-MP land surface model. The default albedo parameterizations for land ice in Noah-MP are set relatively high and might need to be lowered (variable ALBICE in phys/module_sf_noahmp_glacier.F) for a value more consistent with bare ice in the study region. Have the authors explored changes in the WRF land surface model for a more realistic representation of albedo?

Page 21 Figure 9 (e) and (f): Please specify which year you are referring to here (2020?)

Page 23 Figure 10 and page 33 Figure E1: These figures are hard to read. Please increase the text and line sizes.

Page 23 lines 469-470: Can you provide an error estimate of the geodetic validation data used in this study?

Page 24 lines 484-486: Can the authors give a brief overview of the current snow albedo routine in JULES?

Page 24 lines 491-496: Getting the net radiation correct in glacier modeling is a (main) challenge beyond tropical glaciers. Are there any conclusions for glacier calibration that can be drawn which are specific to tropical glaciers?

Page 25 lines 526-527: I believe it is important here to mention which variables have been downscaled (i.e., temperature and precipitation), and that the other variables have been resampled for 2019-2100.

References:

Grasso, LD. (2000). The Differentiation between grid spacing and resolution and their application to numerical modeling. Bulletin of the American Meteorological Society. 81 (3). 579-580. 10.1175/1520-0477(2000)081<0579:CAA>2.3.CO;2.

Stull, R. B. (2015). Practical meteorology: An algebra-based survey of atmospheric science. Department of Earth, Ocean & Atmospheric Sciences, University of British Columbia, Vancouver, BC. https://doi.org/10.14288/1.0300441.

Please find my review and comments in the attached Supplement pdf file.