|The authors have made major revisions to the manuscript based on previous comments by 2 reviewers. Overall, the authors have done a good job of addressing the comments of the reviewers. In particular, they have addressed the issue of the initial paper inaccurately describing the work as a dynamical downscaling of CMIP6 products. I believe the manuscript is almost ready to be published, but the authors should spend some time clarifying some elements.|
My comments will address a few aspects of the revised manuscript that the authors should address before publication. These comments focus mostly on new material in the manuscript.
The title is more accurate than the previous one. However, the use of the term “Reassessment” leads to an expectation that comparisons with previous studies would be more prominent, especially in the abstract. These comparisons are made in table 3, but they should also be included in the abstract. Overall, the study does show that the new analysis is likely more accurate than previous assessments, but it is probably not as clear as it could be. See further comments below.
“The biogeochemical boundaries were interpolated from NCAR’s CESM2-WACCM-FV2 solution after a comprehensive evaluation of 17 Global Climate Model (GCMs) products against
available observations and global climatology products”. This statement is too strong for the abstract. The evaluation of the models is robust enough for this paper, but it is not particularly comprehensive in general.
Description of model drivers
The description of the model driving data has improved in the latest manuscript. However, it is still somewhat difficult to follow. I recommend that the authors state clearly in a couple of sentences what their overall philosophy is for selecting the driving/boundary data, instead of only stating what data they have chosen. This will address obvious "Why did the study not use X?" questions from readers?
The authors should probably also state why they did not use a global biogeochemistry reanalysis product instead of a CMIP6 model. This appears justified, as I believe none of the openly available reanalysis have sufficient variables. But the choice of CMIP6 over a reanalysis may seem questionable to some readers, so clarification could help.
I recommend that the authors either remove figure 15 or reconsider the colour scheme. It is currently very difficult to make out where the model is positively or negatively biased. I can see that there is a large bias near the coast, but elsewhere I cannot easily tell if there is a positive or negative bias. This could be fixed by using a diverging colour palette.
This is an importamt and useful figure, in that shows the better performance of this model versus the others assessed. However, the authors should consider making some changes.
I would not expect the coarsely gridded CMIP6 models to be particularly good at resolving pCO2 in this region. It should be easy to outperform them, and so the comparison with CMIP6 should probably go into the supplementary materials.
The important comparison seems to be with the previous regional models. I therefore recommend redoing figures 15 and 16 to only include the regional studies. This is also more in line with the “Reassessment” aspect of the title. It is important the authors make totally clear how their study is improving on previous ones, and figures 15 and 16 weaken that aspect of the study.
As above, the authors should consider restricting this to the regional models. Ideally, table 2 will only include the models shown in table 3. There is also a potential technical issue with the calculations for the CMIP6 models. Many of the coastal points will be outside the CMIP6 model domains. It is therefore unclear how they were handled. Were they extrapolated outside the domain? Given the heavy concentration of coastal points, it is possible the comparison between CMIP6 models and this study is not consistent.