This study presents the application of the COSIPY model to simulate firn temperature evolution in a cold accumulation zone at Colle Gnifetti. The model is 1D but spatially distributed to map the firn temperature evolution over the whole study area. The model solves the surface energy balance in a skin layer to estimate surface temperature and melting. These variables are used to force a 1D firn model that solves for snow densification, water percolation and refreezing, and heat diffusion. The results show overall good agreement with the extensive firn temperature measurements carried out for many years at Colle Gnifetti and confirm the previously identified strong spatial variability of firn temperature, which is primarily controlled by surface melt. The study quantifies the current firn warming trend and provides a useful estimate of future firn warming at high altitude. The authors highlight some model limitations, particularly the influence of the initial temperature profile after spin-up or the choice of percolation scheme.   

The manuscript is clear, well written with nice figures, and investigates an important topic as firn warming controls the strong ongoing change in the glacier thermal regime at high elevations. However, I am surprised that the authors try to publish a very similar study as Mattea et al. (2021) without any significant differences. The figures, the paper structure, the data and the model are more or less the same. Some small modifications and parameter tuning have been done that lead to slightly different results, but I do not think it is worth a new publication just for that. I actually found the discussion of Mattea et al. (2021) more interesting. 

Nevertheless, I think the manuscript can still be published in The Cryosphere if the authors make an effort to distinguish their study from Mattea et al. (2021). I have made some suggestions in this sense in the general comments below, which I encourage the authors to do. 

Best regards, 

Adrien Gilbert 

General comments

• The study would be more interesting if the sensitivity of the results to the different parameters were clearly analyzed and reported. In particular, I miss the influence of the modification you made compared to Mattea et al. (2021). How sensitive is the result to penetrating radiation? To surface roughness? To thermal conductivity ? To percolation depth? This exercise has already been partially done in the appendix of Mattea et al. (2021) by single parameter modification (2 values). This could be done in more detail in this study by better exploring the parameter space and the associated modeled temperature change.
  
  

• You mention a high-resolution thermistor chain at SP that allows to identify a significant 4m-deep temperature increase in 21 days. It would be interesting to see how the model compares to this record in detail to potentially identify the origin of the model bias. This is especially interesting because summer 2022 has the most intense high altitude melt ever recorded ...  

• The authors highlight, as in Mattea et al. (2021), the strong influence of the imposed percolation depth and suggest that a more physical approach would be better but nothing has been done. Implementing an alternative, more physical approach (even simple), for water percolation would be an improvement/modification that would better justify a new paper. You could also use your high-resolution thermistor chain at SP to validate the percolation scheme.
  
  

•  The model tends to have a cold bias compared to the observation. It would be interesting to identify the origin of this bias. A detailed comparison of model and data at a selected site could help. I think it is possible to show if the bias comes from heat conduction, vertical advection, missing energy input within the snowpack (radiation penetration?), or from too cold surface temperature from the SEB model? Or something else?   

 Specific comments 

 You will find a list of corrections and specific comments embedded in the annotated PDF in attachment.