This manuscript provides a comprehensive intercomparison between established ozone dry deposition parameterizations. The result is somewhat expected but still highly relevant and valuable for the community, established with robust result. I have only a few minor questions and suggestions:

• The model description is nice and thorough. However, putting them in the main text obstruct the flow of the manuscript. I suggest the authors move the detailed model description to appendix/supplemental material. The authors could also consider using tables to make the model description more organized and readable.

• L 79 – 80: I suggest “land carbon sink” instead of “carbon storage, and more example/elaboration about how ozone affect ecosystem service

• Table 1: What precisely is B? “Parameter related to soil moisture” sounds very vague.

• L 228 – 230: More discussion about how the uncertainty in r_a (choice of MOST universal function, h and z₀) may (or may not) affect the study can be helpful.

• L 284 – 285: Clarify what is “effective LAI”. What is its physical/biological meaning? How is it calculated?

• L 841: What “other compounds” and why are they “challenging” to be measured in high frequency? Some examples, discussions and citations would be helpful.

• L 1728: Could the authors provide how may we address the over-reliance on LAI to determine seasonality? E.g. Would other ecophysiological parameters (e.g. seasonally-varying leaf nitrogen content/leaf-level photosynthetic capacity) help? What factors other than phenology might contribute to the seasonality of v_d, but not yet considered in the parameterizations? Is the seasonality of non-stomatal ozone uptake under-represented?

Reviewer summary

This work contributes to Activity 2 of the AQMEII4 framework. This manuscript uses 18 models and model variants to examine how differences in their parameterization of ozone dry deposition drives model bias with respect to observations (of ozone dry deposition). To isolate inter-model variability due to differences in their ozone dry deposition parameterization, the models are used in a single point configuration and driven by observed meteorology and environmental conditions at each of eight sites. The models’ ability to capture seasonal patterns and interannual variability (where possible) in ozone dry deposition is evaluated at the eight sites. The contribution of variability in the simulated deposition pathways (stomatal, soil etc.) to the models’ bias against observations is also evaluated. Overall, this study finds that, broadly, models’ ozone dry deposition may be too strongly linked to LAI, better constraints on wintertime deposition pathways are required and more detailed observations are required to unpick the drivers of model biases in ozone dry deposition. I have some general and technical comments (see below) that should be addressed prior to publication.

General comments:

The authors’ efforts to provide comprehensive descriptions of the ozone dry deposition schemes used in the 18 models and model variants is very commendable. Similarly, their efforts to compile comprehensive multi-annual observational datasets. Both are valuable resources for the community. The manuscript is also clearly laid out and well written.

Given the multitude of sites, models and dry deposition pathways it is difficult to draw overarching conclusions on the drivers of model bias in ozone dry deposition here. While I agree with the authors recommendations for more detailed observational data, which may help with identifying the biases deposition, the time scales required to generate the type of long-term data sets are obviously quite long. I would therefore be keen to hear more about the author’s plans or ideas to identify drivers of model biases using the data sets developed for this manuscript. For example, would more detailed statistical analysis or model sensitivity studies be useful? Or is it that real-world heterogeneity at the site level prevents over-arching conclusions on sources of model bias for ozone dry deposition?

1. Section 2.1

Would it be possible to highlight the dry deposition scheme components by group? For example, bold or underlined headings for e.g. ‘Stomatal resistances’, ‘Non-stomatal resistances’, ‘Environmental dependencies’ for each of the models could help readers navigate the schemes for their future reference.

1. Figure captions after ‘Figure 3’ need relabelling.

Technical comments:

1. Introduction, L140: “…global chemical transport models and used always as standalone models…”

=> Perhaps remove ‘and’ in the above sentence.

1. Section 2.1.2, L279: “…then the parameter’s value in Table S6.”

=> “…then the parameter’s value is in Table S6.”

1. Section 2.1.2, L287: “…so that nighttime rst values on the single point model more similar to GEOS-Chem.”

=> “…so that nighttime rst values on the single point model are more similar to GEOS-Chem.”

1. Section 2.1.7, L553: “van der Walls”

=> van der Waals

5.Figures 2 (or 3):

Would it be possible to indicate the inter-annual variability in the observations here (Fig. 2 might be better), possibly as vertical bars/whiskers? I’m aware that these plots are illustrating inter-model variability, rather than inter-annual model variability – although the latter looks to be encapsulated by the former in Fig. 2. However, in the context of the site specific discussions, I think it would be useful to illustrate the inter-annual variability in the observations.