Please find the review attached 

This study by Korosov et al. aims to present a new climate data record of Arctic sea ice age, LM-SIAge, developing a Lagrangian advection method on a triangular grid to minimize numerical diffusion compared to a grid-based method. On a daily basis, covering a wide range of years with a new approach, this dataset would be positioned as an important contribution to the scientific community, and potential users can effectively use this dataset for Arctic weather and climate monitoring, model validation, as well as data assimilation. The manuscript is well written and organized, and the research topic is well-fitting within the journal's scope. I recommend a revision to address the specific comments below before the manuscript is accepted for publication

1.    One thing that I was concerned about was a validation and uncertainty analysis of the constructed dataset. The authors used buoy position data to validate the age product. It is an acceptable approach. However, the used buoy trajectories cover only between 2002 and 2024. The product for the earlier period of 1991 – 2011 was not validated in this manuscript. The uncertainty inherent in this product depends on the quality of the passive microwave-based SICs. The uncertainty of SICs can vary with seasons. The seasonal uncertainties of the age product due to the SIC uncertainties should be addressed. In addition, the uncertainty section is difficult to read and understand. I recommend reformulating this section.

2.    In methodology, the authors chose certain parameters, e.g., mesh element size thresholds, angle, and element area, which seem to be used without any justification. It would be better if the authors provide how sensitive the results are changed due to these parameters or references to support these values.  

3.    Are there any possibilities of ridging or deformation processes with different age categories affecting the proposed algorithm?

4.    It is very fair to provide Figure 15 for the NSIDC product as well.

5.    In supplementary videos, I found that somewhat permanent multiyear ice exists in the coastline of the Kara Sea and Islands between the Kara and Laptev Seas. Is this correct?

This manuscript, “A Climate Data Record of Sea Ice Age Using Lagrangian Advection of a Triangular Mesh” by Korosov et al., is well written and scientifically sound. It presents a novel and carefully implemented approach to estimate sea-ice age with improved accuracy. Sea-ice age is a key variable for understanding Arctic sea-ice dynamics and thermodynamics, and the development of an improved methodology for its derivation will be welcomed by many researchers in the cryospheric community.



The authors introduce a Lagrangian-tracking framework based on triangular meshes to reduce tracking errors in sea-ice age estimation. The approach is clearly described and appears to be robust and efficient. The results demonstrate that this method substantially improves the spatial and temporal consistency of sea-ice age products.



Although direct validation of sea-ice age is inherently challenging due to the scarcity of observational references, the authors have utilized available datasets effectively. The validation efforts are appropriate and sufficient within the limitations of current observations.



Overall, the manuscript represents a valuable contribution to the field. I recommend publication after minor revisions.



Specific Comments

Section 3.1 – Representation of Age Evolution

The computation of sea-ice age change appears to assume that all ice categories evolve similarly in time. In reality, when sea-ice concentration decreases, younger ice tends to melt more rapidly than older ice. It would be helpful if the authors could clarify whether this differential melting behavior is accounted for in their formulation, or discuss its potential implications for the resulting age distribution.

Clarity of Method Description (Figures 5 and 6)

Since the triangular-mesh approach and its associated remeshing procedure may be unfamiliar to many readers, the description of these processes could be improved for clarity. Figures 5 and 6 are central to understanding the proposed algorithm, but both could be made more legible and intuitive.

In Figure 5, particularly in the left and right examples, it is difficult to visually identify what has changed before and after the remeshing process. The green lines representing the remeshed state are also hard to distinguish.

In Figure 6, the blue and black lines in the left panel are not easily distinguishable. Enhancing the color contrast or line thickness would improve readability.