See attachment.

The manuscript by Zhuge et al. presents a comprehensive introduction and evaluation of their NJIAS cloud product based on Himawari-8/9 measurements over East Asia and the western North Pacific, and the dataset is expected to serve climate and typhoon studies over the region. The cloud properties are compared with both active and passive satellite results of the kinds, and are evaluated by comparing with Himawari operational and MODIS results. The results are well organized and presented, and the manuscript is well-written overall. I have several suggestions to further strengthen the manuscript.

1. The introduction could be expanded to better motivate the need for this new dataset. How does it build upon and improve existing Himawari-8/9 cloud products? What new capabilities does it offer? More background on current limitations and gaps would help frame the value addition.

2. In Section 2.3 on algorithm updates, more quantitative details could be provided on the impact of the refinements. For example, metrics like changes in POD, FAR, etc. would strengthen this section.

3. The evaluation results are thorough, but the authors could better highlight one or two key advantages and limitations of the NJIAS results compared to MYD06 and JAXA products.

4. The manuscript indicates that the dataset can be used for climate studies, while 7-year observations will be difficult to be used for climate studies. Thus, the corresponding discussions are suggested to be more carefully given.

5. In Section 2.4 on the cloud products, more details should be provided on the algorithms and methodology used to derive the 0.04Deg and TyWNP products from the full disk data. How was the remapping done? What is the impact on data quality compared to full resolution?

6. How is the uncertainties of the dataset, is there any estimation?

7. The intercomparison between NJIAS and JAXA products reveals some interesting differences in Section 3, but the sources of discrepancies are not thoroughly discussed. Speculating on the potential reasons behind the weaker performance of JAXA and areas for algorithm improvement would add value.

8. The conclusions in Section 6 are a bit abrupt and underdeveloped. The authors could expand on the key findings, significance, broader applications and future directions to improve this section. Reiterating the unique contributions of this work would be beneficial.