the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Vertical profiles of global tropospheric nitrogen dioxide (NO2) obtained by cloud-slicing TROPOMI
Abstract. Routine observations of the vertical distribution of tropospheric nitrogen oxides (NOx ≡ NO + NO2) are severely lacking, despite the large influence of NOx on climate, air quality, and atmospheric oxidants. Here we derive vertical profiles of global seasonal mean tropospheric NO2 by applying the cloud-slicing method to TROPOspheric Monitoring Instrument (TROPOMI) columns of NO2 retrieved above optically thick clouds. The resultant NO2 are at a horizontal resolution of 1° × 1° for multiple years (June 2018 to May 2022) covering 5 layers in the upper (180–320 hPa and 320–450 hPa) and mid (450–600 hPa and 600–800 hPa) troposphere, and the marine boundary layer (800 hPa to the Earth’s surface). Terrestrial boundary layer NO2 are obtained as the difference between TROPOMI tropospheric columns and the integrated column of cloud-sliced NO2 in all layers above the boundary layer. Cloud-slicing NO2 is typically 20–60 pptv throughout the free troposphere and spatial coverage ranges from > 60 % in the mid-troposphere to < 20 % in the upper troposphere and boundary layer. Our product is similar (within 10–15 pptv) to NO2 data from NASA DC-8 aircraft campaigns (INTEX-A, ARCTAS, SEAC4RS, ATom) when both datasets are abundant and sampling coverage is commensurate, but such instances are rare. We use the cloud-sliced NO2 to critique current knowledge of the vertical distribution of global NO2, as simulated with the GEOS-Chem chemical transport model updated to include peroxypropionyl nitrate (PPN) and aerosol nitrate photolysis that liberate NO2 in the lower and mid-troposphere for aerosol nitrate photolysis and upper troposphere for PPN. Multiyear GEOS-Chem and cloud-sliced means are compared to mitigate the influence of interannual variability. We find that for cloud-sliced NO2 the interannual variability is ~10 pptv over remote areas and ~25 pptv over areas influenced by lightning and surface sources. The model consistently underestimates NO2 across the remote marine troposphere by ~15 pptv. In the northern midlatitudes, GEOS-Chem overestimates mid-tropospheric NO2 by 20–50 pptv, as NOx production per lightning flash is parameterised to be almost double the rest of the world. There is a critical need for in-situ NO2 measurements in the tropical terrestrial troposphere to evaluate cloud-sliced NO2 there. The model and cloud-sliced NO2 discrepancies identified here need to be investigated further to ensure confident use of models to understand and interpret factors affecting the global distribution of tropospheric NOx, ozone and other oxidants.
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RC1: 'Comment on egusphere-2024-1541', Anonymous Referee #1, 01 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1541/egusphere-2024-1541-RC1-supplement.pdf
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RC2: 'Comment on egusphere-2024-1541', Anonymous Referee #2, 16 Aug 2024
Review of “Vertical profiles of global tropospheric nitrogen dioxide (NO2) obtained by cloud-slicing TROPOMI” by Horner et al.
8/16/24
Summary:
This paper describes an extension of previous efforts in total column NO2 cloud slicing in order to obtain vertical profiles of NO2 amount. Building on the work of Marais et al. [2021], who derived NO2 mixing ratios in the upper troposphere from a single year of TROPOMI data, the authors refine the earlier technique in several ways and extend the analysis to the surface, based on 4 years of TROPOMI using a self-consistent retrieval throughout the period. The new cloud-sliced climatology is compared with both aircraft in situ data and GEOS-Chem model output. The analysis presented is very thorough and thoughtfully presented.
Comments (minor):
- In section 2.1, the cloud-slicing technique is nicely explained in the text. The addition of an equation(s), would make it easier to understand how the authors go from a total column amount to mixing ratios in individual layers of the troposphere.
- Also in section 2.1, a better of explanation of what “informed by thresholds used by Choi et al.” (line 131) means is needed.
- Please explain what “NO2 mixing ratios within each layer are relatively well mixed” (lines 149–150) means. Do you mean NO2 is well mixed or the mixing ratio is constant within the layer?
- Better rationales for the thresholds used in the analysis are needed. For example, comparisons between cloud-sliced and GEOS-Chem grids are made only when at least 10 cloud-sliced data points are within the cloud-sliced grid (lines 248–249). Why 10 and not 5 or 15?
- Figures 1 and 2: Recommend adding “n=” to the insets in each panel, indicating the number grids used. It will make the figures easier to interpret without reading the text.
- It is hard to derive much quantitative information about the cloud-sliced vs. aircraft NO2 from Figure 4. The maps are valuable in defining the geographic regions analyzed subsequently, and the larger circles show where the aircraft data are nicely. No change is requested—just a comment.
- “The greater variability in the DC-8 data in each layer (larger interquartile ranges), is because DC-8 are single year measurements, whereas cloud-sliced NO2 are multiyear means” (lines 353–354): I do not understand why the longer time period would necessarily reduce the IQR. In fact, I might have expected the opposite, as multi-year variability might increase the range of values sampled. Could this instead be due to a difference in the representativeness of the measurement, seeing as the TROPOMI footprints are larger than the DC-8 sampling and thus average out smaller-scale features? In any case, more explanation is needed of this quoted statement.
Citation: https://doi.org/10.5194/egusphere-2024-1541-RC2 - AC1: 'Comment on egusphere-2024-1541', Rebekah Horner, 20 Sep 2024
Status: closed
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RC1: 'Comment on egusphere-2024-1541', Anonymous Referee #1, 01 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1541/egusphere-2024-1541-RC1-supplement.pdf
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RC2: 'Comment on egusphere-2024-1541', Anonymous Referee #2, 16 Aug 2024
Review of “Vertical profiles of global tropospheric nitrogen dioxide (NO2) obtained by cloud-slicing TROPOMI” by Horner et al.
8/16/24
Summary:
This paper describes an extension of previous efforts in total column NO2 cloud slicing in order to obtain vertical profiles of NO2 amount. Building on the work of Marais et al. [2021], who derived NO2 mixing ratios in the upper troposphere from a single year of TROPOMI data, the authors refine the earlier technique in several ways and extend the analysis to the surface, based on 4 years of TROPOMI using a self-consistent retrieval throughout the period. The new cloud-sliced climatology is compared with both aircraft in situ data and GEOS-Chem model output. The analysis presented is very thorough and thoughtfully presented.
Comments (minor):
- In section 2.1, the cloud-slicing technique is nicely explained in the text. The addition of an equation(s), would make it easier to understand how the authors go from a total column amount to mixing ratios in individual layers of the troposphere.
- Also in section 2.1, a better of explanation of what “informed by thresholds used by Choi et al.” (line 131) means is needed.
- Please explain what “NO2 mixing ratios within each layer are relatively well mixed” (lines 149–150) means. Do you mean NO2 is well mixed or the mixing ratio is constant within the layer?
- Better rationales for the thresholds used in the analysis are needed. For example, comparisons between cloud-sliced and GEOS-Chem grids are made only when at least 10 cloud-sliced data points are within the cloud-sliced grid (lines 248–249). Why 10 and not 5 or 15?
- Figures 1 and 2: Recommend adding “n=” to the insets in each panel, indicating the number grids used. It will make the figures easier to interpret without reading the text.
- It is hard to derive much quantitative information about the cloud-sliced vs. aircraft NO2 from Figure 4. The maps are valuable in defining the geographic regions analyzed subsequently, and the larger circles show where the aircraft data are nicely. No change is requested—just a comment.
- “The greater variability in the DC-8 data in each layer (larger interquartile ranges), is because DC-8 are single year measurements, whereas cloud-sliced NO2 are multiyear means” (lines 353–354): I do not understand why the longer time period would necessarily reduce the IQR. In fact, I might have expected the opposite, as multi-year variability might increase the range of values sampled. Could this instead be due to a difference in the representativeness of the measurement, seeing as the TROPOMI footprints are larger than the DC-8 sampling and thus average out smaller-scale features? In any case, more explanation is needed of this quoted statement.
Citation: https://doi.org/10.5194/egusphere-2024-1541-RC2 - AC1: 'Comment on egusphere-2024-1541', Rebekah Horner, 20 Sep 2024
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