Main comments:

By comparison with the recoded CO concentrations ([CO]) in multi-site ice archives, this study analyzes the model performance of 16 ACCMIP models and 6 AerChemMIP models on simulating historical (1850-2014) [CO] over Greenland and Antarctica, focusing on both absolute values and trends of [CO], and points out that the model is biased in simulating high-latitude CO concentrations. The results are meaningful for improving the long-term simulations of [CO] in a GCM model. However, the analysis of the specific causes of these biases may be insufficient. More quantitative and in-depth analysis is needed to identify sources of the bias.

Specific comments:

Section 3.2, for the ACCMIP models, why were only 3 time slices selected in this study?

Sections 3 and 4, It is suggested that in the text or in an annex, a table be added to give the anthropogenic and biogenic emission inventories and OH radicals used in each model.

Lines 230-231, It is recommended that the differences between the models are analysed in more detail to see why the UKESM1 model can accurately simulate the [CO], the BCC-ESM1 model overestimates [CO] and the other models underestimate it. In addition, there are significant differences in [CO] between AerChemMIP and ACCMIP, what’s the reason for these differences. Overall, the authors provide a lot of analysis of deviations from modelled and observed trends, but there is a lack of explanation of the reasons for the deviations between modelled and observed absolute concentrations.

Lines 335-337, “the mismatch in [CO] trends … may be related to uncertainties in CO emission factors (EF)”, This conclusion is too arbitrary. Although the author describes that the [CO₂] has a sharp increase in growth rates in ~1945 CE, as shown in Fig 3a, for [CO], there is also a sharp increase in ~1945 CE. It is recommended that the authors make some quantitative comparisons rather than just qualitative descriptions.

Section 5.3.3, Many “top-down” inversions (e.g., Müller, and Stavrakou, 2005, doi:10.5194/acp-5-1157-2005; Feng et al., 2020, doi: 10.1029/2019JD031808.) have shown that the present bottom-up inventories underestimate the anthropogenic CO emissions in the Northern Hemisphere. Therefore, I suggest that the author can cite some inversion studies to support that the anthropogenic CO emissions have been underestimated.

Line 30, “outputs from 16 (Atmospheric” => “outputs from 16 ACCMIP (Atmospheric”

Line 75, “[CO]”, full name is needed here.

Line 143, Missing period.

Line 253 and 258, ‘AerChemMip’=>‘AerChemMIP’

Line 269, 2 times larger than what?

Line 301, “XX^th”

Line 325, in Figure 4, fossil fuel emissions are shown as brown lines instead of purple lines, and fire emissions are shown as blue lines instead of brown lines.

Figure 4, Labels of a and b should be added to the top left corner of the two subfigures. In addition, the text of 0-90N and 0-90S in the figures is inconsistent with the description in the figure title of 30-90N and 30-90S. Meanwhile, it is recommended that the timeframe of this graph be consistent with that in Figures 2 and 3.

Line 331, “WWII”, full name is needed here.

Line 332, “EF”, full name is needed here.

The study presents a comparison of modeled atmospheric carbon monoxide (CO) against reconstructions of CO from ice cores and firn air. The authors focus on comparisons for high latitudes in the Northern Hemisphere (NH) and Southern Hemisphere (SH), investigating the multi-model mean for models used in ACCMIP and AerChemMIP. They find improvement of CO representation from ACCMIP to AerChemMIP. CO trends are generally well reproduced by the multimodel mean, with potential reasons for discrepancies discussed.

Overall the manuscript is well written and the analysis rigorous. The evaluation of model results against measurement is important, and timely as a benchmark for future modeling studies. I have several comments to be addressed below.

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Main Comments:

Fig. 2 and Fig. 3 – the different lines in the firn air record for the NH need defining. Originally, I thought the spread was a measure of uncertainty shading, but it looks like multiple lines are plotted from the NH firn data. Please clarify. Also, describe other uncertainty bounds in the caption.

Introduction: the discussion of methane oxidation was a little confusing around line 53 onwards. Consider clarifying by first mentioning secondary CO production accounts for about 50% of CO globally, and then state methane oxidation is the dominant secondary source.

Section 3.2 and Section 4.2 – Please reference if there is a public data repository where you obtained the ACCMIP and AerChemMIP data, or explain how you obtained the data model output.

Section 5.2: There are several additions/clarifications needed for the trend analysis.

• Please clarify whether trends were defined 1980 to 2020 or from 2000?
• What method was used to determine trends? Please add uncertainties to your trend estimates.
• What is being used to define “excellent” agreement?
• Please also state the SH trends in addition to the NH.
• L254-256: The statement “… 4 ppb higher in 2000 CE compared to 1980 CE. ACCMIP models were not able to reproduce decline in Arctic [CO]” seems inconsistent with Fig.2 where the 2000 value seems lower than the 1980 value in the NH.

Section 5.3: The time bound is 1945 on line 266, but 1950 on line 276. I suggest to chose one time bound for ease of understanding.

Fig. 4: I suggest the time range begin at 1850 to be consistent with other figures and the main text arguments.

Section 5.4: Consider whether there is also some potential overestimation in emission sources for the SH between 1900 to 1950 – the model trend seems higher than the measurements during this time period in Figs. 2 and 3.

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Technical Corrections:

Fig 2. and Fig 3. caption: 1850 and 1900 should be 1850, 1980 and 2000.

3.1 Heading – consider changing to “ACCMIP CO budget” to be consistent with section 4.1.

Line 302: Check CCMS is defined

Fig. 4: I suggest to rename “Open Burning” in the legend to “Biomass Burning” to be consistent with the main text.