the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 Apr 2025
NO2 concentration differences under clear versus cloudy skies and implications for applications of satellite measurements
Abstract. Satellite measurements of tropospheric trace gases are often only used when there are few clouds, which screens out 20 – 70 % of the data, depending on geographic region. While the lack of high-quality column measurements during cloudy conditions precludes validation of the satellite data, in situ surface measurements and model simulations can provide insight on the quantitative understanding of NO2 during cloudy conditions. Here, we intercompare surface observations, satellite measurements, and models during 2019 over the contiguous U.S. to quantify how NO2 concentrations are different under clear and cloudy skies. We find that in situ surface NO2 measurements are, on average, +17 % larger on all days compared to restricting to clear sky days and +36 % larger during cloudy days versus clear sky days, with a wide distribution based on geographic region and roadway proximity: largest in the Northeast U.S. and smallest in the Southwest U.S. and near major roadways. WRF-Chem simulated surface NO2 between cloudy and clear conditions is on average much larger than the observed differences: +59 % on cloudy days vs. clear days for the model. This suggests that NO2 in WRF-Chem is more responsive to sunlight and associated photochemistry than in reality. Finally, using in situ NO2 matched to provisional TEMPO data, we find the NO2 differences between cloudy and clear conditions to be larger in the afternoon than morning. This study quantifies some of the biases in satellite measurements introduced by using only clear-sky data, and introduces some corrections to account for these biases.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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Supplement
(1361 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(6010 KB) - Metadata XML
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Supplement
(1361 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2025-1350', Anonymous Referee #1, 16 Apr 2025
- AC1: 'Reply on RC1', Daniel L. Goldberg, 30 Jul 2025
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RC2: 'Comment on egusphere-2025-1350', Anonymous Referee #2, 06 May 2025
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
Citation: https://doi.org/10.5194/egusphere-2025-1350-RC2 - AC2: 'Reply on RC2', Daniel L. Goldberg, 30 Jul 2025
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2025-1350', Anonymous Referee #1, 16 Apr 2025
- AC1: 'Reply on RC1', Daniel L. Goldberg, 30 Jul 2025
-
RC2: 'Comment on egusphere-2025-1350', Anonymous Referee #2, 06 May 2025
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
Citation: https://doi.org/10.5194/egusphere-2025-1350-RC2 - AC2: 'Reply on RC2', Daniel L. Goldberg, 30 Jul 2025
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M. Omar Nawaz
Congmeng Lyu
Annmarie G. Carlton
Shobha Kondragunta
Susan C. Anenberg
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(6010 KB) - Metadata XML
-
Supplement
(1361 KB) - BibTeX
- EndNote
- Final revised paper
See attached .pdf file.