the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Sep 2024
Evaluating tropospheric nitrogen dioxide in UKCA using OMI satellite retrievals over South and East Asia
Abstract. We compare tropospheric column nitrogen dioxide (NO2) in the United Kingdom Chemistry and Aerosol (UKCA) model version 11.0 with satellite measurements from NASA’s Earth Observing System (EOS) Aura satellite Ozone Monitoring Instrument (OMI) to investigate the seasonality and trends of tropospheric NO2 over South and East Asia (S/E Asia). UKCA is the atmospheric composition component of the UK Earth System Model (UKESM). UKCA was run with nudged meteorology, producing hourly output over S/E Asia for 2005–2015. OMI averaging kernels have been applied to the model hourly data sampled at Aura’s local overpass time of 13:45±15 to allow consistent model-data comparison. Background UKCA and OMI tropospheric column NO2 typically ranges between 0–2 × 1015 molecules/cm2. Diurnal cycles and vertical profiles of the tropospheric NO2 column in UKCA show that the daily minimum tropospheric column NO2 occurs around the satellite overpass time. UKCA captures the seasonality but overestimates NO2, by a factor of ~2.5, especially during winter over Eastern China and North India, at times and locations with high aerosol loadings. Heterogeneous chemistry is represented in the version of UKCA used here as uptake of N2O5 on internally generated sulfate aerosol. However, aerosol surface area may be underestimated in polluted locations, contributing to overestimation of NO2. In addition, the model may underestimate emissions of volatile organic compounds and associated peroxy acetyl (PAN) formation, leading to insufficient long-range transport of oxidised nitrogen, also contributing to overestimation of NO2 over polluted regions and underestimation over remote regions. Quantifying and understanding discrepancies in modelled NO2 warrant further investigation as they propagate into modelling of multiple environmental issues.
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RC1: 'Comment on egusphere-2024-2686', Anonymous Referee #1, 11 Oct 2024
This paper compares NO2 and its variability in the UKCA model over South and East Asia to OMI observations. The impact of sampling at the time of day corresponding to the satellite overpass and incorporating the OMI averaging kernel is investigated. The evaluation reveals areas and seasons of bias in the simulated NO2 and suggests several possible factors that could contribute to the bias. The study provides a robust evaluation of the UKCA simulation of NO2 over South and East Asia. The manuscript would benefit from additional discussion of whether the results can be generalized to other models or regions to broaden its scientific significance.
General comments:
1. In the discussion, can you compare your results to other modeling studies or comment on whether the same biases are likely to affect other models? This could broaden the applicability of the study.
2. While the study focuses on South and East Asia, it would be helpful to include a figure or some discussion of how the model compares to OMI observations globally. Are the biases found over South and East Asia present in other regions as well? This might provide additional information on what the most likely cause is.
3. Uncertainties in NOx emissions and emission trends are another potential cause of model biases. More discussion is needed on the NOx emissions used in the model and their uncertainties.
Specific comments:
Page 5: Do you sample the model every day or only on days when there is a retrieval for a specific grid box? Is the model-obs comparison affected by clear-sky sampling?
Line 145: How were these regions chosen?
Fig. S3: The caption of Fig. S3 says “trends” but the figure appears to show a timeseries.
Figs. S5 and S6: Are these discussed in the text?
Line 195: Can you explain why the averaging kernel makes a larger difference in winter?
Line 197: The statement “clearly demonstrates the importance of…” may need a caveat as the difference looks quite small in summer.
Section 3.5: It would be helpful to plot a timeseries or trends for the NOx emissions for each of the regions.
Section 3.5: How do the trend magnitudes compare in terms of % trends?
Discussion: Could errors in the assumed emission trends also be a cause of model-obs mismatch? This should be discussed.
Citation: https://doi.org/10.5194/egusphere-2024-2686-RC1 -
RC2: 'Comment on egusphere-2024-2686', Anonymous Referee #2, 16 Oct 2024
This paper provides valuable insights for modeling NO2 in south and east Asia. A comprehensive comparison between UKCA modeled NO2 concentrations and OMI NO2 observations and trend analyses using both datasets are performed. The results show that in south and east Asia, UKCA tends to overestimate NO2 compared to OMI while exhibits similar trends over 2005 -2015. However, more detailed and quantitative discussions need to be done to better illustrate the results.
Major comments:
(1) To me, the motivation of this study remains unclear. Does this paper aim at model evaluation? If so, I recommend a review of CCMs in the introduction, and more technical details of UKCA in section 2.1. Also, more background information is needed to explain why this paper focuses on south/east Asia besides the large population, e.g., lack of ground monitoring networks, and discrepancies between model and observations.
(2) Overall, there is a lack of comparisons with previous studies, e.g., is overestimating NOx a common problem for CCMs; does this study improve any existing problems? Also, the role and uncertainties of nitrogen deposition should be included. Moreover, the discussion and conclusions need to be more quantitative. The author mentions uncertainties in NOx emission inventories and the representation of heterogeneous chemistry without quantifying the uncertainties, as a result, it is difficult to draw any strong conclusions.
(3) Trend analysis:
What is the statistical method used for trend analysis? Are annual trends deseasonalized? Please add a paragraph of methodology description in Section 2.
What are the statistical significance values? I suspect that a lot of regions do not have statistically significant trends.
Is 2011 double-counted in both 2005-2011 and 2011-2015 periods?
(4) Please highlight the novelty of this study.
Minor comments:
Line 52 and line 296: NOx: subscript
Line 82: BLH affects NO2 column surface NO2
Figure 5: it would be better to show the 2005 – 2015 mean instead of just using 1-year data. Also, please plot the number of OMI NO2 pixels for each month
Figure 7 (a): please adjust the legend to avoid blocking the text
Figure 11 and 12: add number of points to the scatter plot
Citation: https://doi.org/10.5194/egusphere-2024-2686-RC2 -
RC3: 'Comment on egusphere-2024-2686', Anonymous Referee #3, 16 Oct 2024
This paper presents an evaluation/comparison of modeled tropospheric nitrogen dioxide in UKCA with OMI satellite observation. The model results are presented and compared with satellite data. The following are my comments;
Major comments:
- The manuscript keeps mentioning evaluation/comparison of two datasets. For example, the title describes it as ‘evaluation’ but abstract section mentioned it as ‘comparison’. From my understanding, comparison involves analyzing the similarities or differences while evaluation is a quantitative assessment of how well a model replicates reality (OMI satellite retrievals in this case). The authors need to clearly describe whether they are evaluating or comparing the two datasets.
- The need for the comparison is not well established in the introduction section. Is this the first-time comparison between UKCA model and OMI or the comparisons reported before for two datasets? Further, why did the authors choose OMI for evaluating/comparing the UKCA results? Are the OMI NO2 observations evaluated before in the study region? and are good enough to make comparisons. If so, authors can mention some studies conducted for evaluation of OMI NO2 columns in different regions.
- The paper is describing the diurnal simulations from UKCA model, but the OMI only provides one measurement per day (as described by the authors), then what about evaluation/comparison of diurnal variation? or the authors only evaluating for satellite overpass time? If this is the case, then figure 02 may lead to a confusion for the readers as if diurnal variations are evaluated.
Minor Comments
- Line 99-100: “The model’s horizontal resolution (N96: 1.875º longitude × 1.25º latitude) is much coarser than the satellite data products used.” I think there is a need to explain how the data is matched on a spatial scale for fair evaluation/comparison.
- Line 109: What’s the resolution of ECMWF ERA-interim data used here?
- Line 144: The study area is mentioned at the end of methodological section. I would suggest moving the description of study area at the start of methodological section.
- For figure 1, why the percentage change is much higher over the oceans, what could be the possible sources/reasons? also it would be helpful to show the emissions for 2005.
- Line 174-175: Other than the pollution, what could be the role of meteorological parameters in modulating the vertical distribution/height of NO2 in different regions of study area?
Citation: https://doi.org/10.5194/egusphere-2024-2686-RC3
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