The title “Rapidly changing lake-terminating glaciers in high mountain Asia: a dataset from 1990 to 2022” by Luo et al. described an important, high-quality dataset, vs a new continental-scale inventory of lake-terminating glaciers(LTGs) and their proglacial lakes in High Mountain Asia (HMA) from 1990 to 2022, which fills a recognized gap in HMA cryospheric inventories. The LTG dataset is first region-wide, openly available proglacial lake data through time, which are already on Zenoda with a DOI and CC-0 License. This methodology of dataset is rigorous, semi-automated and reproducible GEE workflow with manual verification using higher-resolution data(Planet labs) and cross-validation with existing datasets. By using long-term Landsat imageries (TM/OLI, 30m resolution) (1990±2 years, 2022±1 year), the study captured 32 years of change of LTG and glacier-lake.

Once the above transparency and validation items are addressed (most require only supplementary material or minor text), the paper will fully meet ESSD’s standards and should be published with minor revision.

General comments

1. Steiner et al. have shared the global LGT. And, this work also produce the LGT in HMA in different time. I would suggest share those LGT. And please Emphasize in the abstract that the vector data are provided as shapefiles / GeoPackage with full attribute tables compliant with the RGI 7.0 vocabulary; this is not obvious to casual readers.
2. It is useful to share the GEE javascript/pythod code as a supplementary file or link to a public Github.

Specific comments

1. The minimum lake threshold was used 0.0036km2(4-pixel), which is justified and consistent with earlier regional work. However, I also noted that the uncertainty of proglacial lakes less than 0.01km2 is larger than 40% in Figure 6. Consequently, I wonder what's the point of taking such a small threshold? I would suggest Keep the threshold at 0.01 km2
2. A 2025 global LTG inventory (Steiner et al., 2025) identified 1912 LTGs in HMA (vs. 1740 in this study), with only 47.4% overlap. The study attributes this to temporal differences (2000±2 vs. 2022) but does not explore potential methodological discrepancies (e.g., Steiner et al.’s use of ASTER data and expert cross-validation), limiting cross-dataset consistency.
3. Table format. “Table 4:” is different with Table 1,2,3. Figure format “Figure1,2,3,4，”，“Figure 5:”, Please check those format
4. Discussion session is weak. The title of this Manuscript is rapidly changes of LTG, So, it is better to link LTG changes to climate drivers (such as how climate effect on regional variations in LTG loss) or others. Furthermore, LTG are link to hazards, so it is usefull to discuss/ass their risk. It would enhance the dataset’s value for disaster risk management.