See attached .pdf file.

The manuscript by Goldberg et al. title “NO2 concentration differences under clear versus cloudy skies and implications for applications of satellite measurements” analyses the differences seen in cloudy versus clear-sky days (using surface in situ, model results and satellite observations) and discusses how these differences may affect satellite observations of nitrogen dioxide columns that are only used under clear sky conditions. The analysis shows that the differences found during clear and cloudy sky conditions need to be taken into consideration when interpreting satellite remote sensing data, as surface data and model results suggest higher surface and column NO2 under cloudy conditions.

I have suggestions to improve this manuscript, which are detailed below. Overall, I think this is a very good fit for publication in Atmospheric Chemistry and Physics after some revisions. It spans multiple disciplines, including satellite remote sensing, air quality, and modelling, making it highly relevant to ACP’s readership. I recommend accepting the manuscript after these revisions are made.

General suggestions

In Section 3.5: For TEMPO a much more rigorous cloud fraction is used which will skew the results. For TROPOMI a cloud fraction of 0.5 is used why use 0.15 for TEMPO? A significant issue is that TEMPO’s cloud fraction is biased high, there are very few cases where the cloud fraction is that low,  a lot of good quality points over clear-sky conditions are filtered when using a cloud fraction cut-off of 0.15. When the coincident cloud fractions from TEMPO and TROPOMI are compared, TEMPO clear-sky is anything below 0.2 (and by clear sky meaning cldF=0 in TROPOMI).  I don’t think it’s fair to compare TROPOMI and TEMPO NO2 that way (as in Fig. 8). Further filters for TEMPO should also include an SZA cut-off (SZA >70 should be filtered) and only snow-free should be used, to have a similar and comparable quality flag as TROPOMI.

It would be helpful to include a map of how many days are filtered for TEMPO (per hour?) similar as in Figure 1, and include TROPOMI for the same time period. This could be included in the main text or the supplement. This should also make it clear what is an appropriate filter is for TEMPO when comparing it to TROPOMI.  

Minor suggestions

l.53: 5.5x7 km2 before August 2019

l.74: is this in North America (and/or US) or globally? 

l.94: 2019 is a critical year to use for this kind of analysis as the TROPOMI resolution switched from 5.5x7 km2 to 5.5x3.5km2. Could this impact any of the results? It would be good to include a couple of sentences addressing this or at least highlighting this, e.g. the clear versus cloudy pixels could change as with a smaller pixel size more pixels are potentially better quality, also the NO2 columns likely increase in urban areas with the smaller pixel size as they are observing a smaller area.

l.128/129: Include more discussion on the impact of the cloud fraction on the AMF (or the VCDs) it contributes significantly to the final AMF. A cloudy and a clear sky AMF is calculated then the cloud fraction is used to weight these AMFs to get the final AMF. The cloudy AMF is typically smaller leading to higher values of the VCD (VCD = SCD/AMF). See e.g. McLinden et al., 2016; Liu et al., 2021;  Nowlan et al., 2025 for more details.

l.157/158: from Mexico City to the Canadian Oil Sands

l.192: there are other reasons other than clouds for low quality (like snow as mentioned), why not just use the cloud fraction to define clear-sky/cloudy-days? The higher values further north or over the mountains as seen using the TROPOMI qa filter could be due to snow rather than clouds.

l.244: The reference in the text to Table 1 is very brief, more details should be included. Here information on chemiluminescence instruments is included, which is quite an important consideration and should be mentioned and discussed more in the text. The no chemilumeneces instruments show a similar slope as the baseline which is encouraging and shows that the increase is not due to increased NOz. It is very encouraging to see that.  What is baseline v2.4 and v2.3.1 there is no explanation of what it means.

How about adding a figure like Figure 5 but for TEMPO and different hours of the day (maybe morning afternoon and evening), either in the main manuscript or in the appendix

Figure S1: why switch to 0.3 as a cut-off when most of the paper used 0.5, Figure 2 (in the main manuscript) also uses 0.5, could all 24 h be included or at least show a few more

References

McLinden, C. A., Fioletov, V., Boersma, K. F., Kharol, S. K., Krotkov, N., Lamsal, L., Makar, P. A., Martin, R. V., Veefkind, J. P., and Yang, K.: Improved satellite retrievals of NO₂ and SO₂ over the Canadian oil sands and comparisons with surface measurements, Atmos. Chem. Phys., 14, 3637–3656, https://doi.org/10.5194/acp-14-3637-2014, 2014.

Liu, S., Valks, P., Pinardi, G., Xu, J., Chan, K. L., Argyrouli, A., Lutz, R., Beirle, S., Khorsandi, E., Baier, F., Huijnen, V., Bais, A., Donner, S., Dörner, S., Gratsea, M., Hendrick, F., Karagkiozidis, D., Lange, K., Piters, A. J. M., Remmers, J., Richter, A., Van Roozendael, M., Wagner, T., Wenig, M., and Loyola, D. G.: An improved TROPOMI tropospheric NO₂ research product over Europe, Atmos. Meas. Tech., 14, 7297–7327, https://doi.org/10.5194/amt-14-7297-2021, 2021.

Nowlan, C. R., Gonzales Abad, G., Liu, X., Wang, H., and Chance, K: TEMPO Nitrogen Dioxide Retrieval Algorithm Theoretical Basis Document, https://asdc.larc.nasa.gov/documents/tempo/ATBD_TEMPO_NO2.pdf