the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Version 1 NOAA-20/OMPS Nadir Mapper Total Column SO2 Product: Continuation of NASA Long-term Global Data Record
Abstract. For nearly two decades, the Ozone Monitoring Instrument (OMI) aboard the NASA Aura spacecraft (launched in 2004) and the Ozone Mapping and Profiler Suite (OMPS) aboard the NASA/NOAA Suomi National Polar-orbiting Partnership (SNPP) satellite (launched in 2011) have been providing global monitoring of SO2 column densities from both anthropogenic and volcanic activities. Here, we describe the version 1 NOAA-20 (N20)/OMPS SO2 product, aimed at extending the long-term climate data record. To achieve this goal, we apply a principal component analysis (PCA) retrieval technique, also used for the OMI and SNPP/OMPS SO2 products, to N20/OMPS. For volcanic SO2 retrievals, the algorithm is identical between N20 and SNPP/OMPS and produces consistent retrievals for eruptions such as the 2018 Kilauea and 2019 Raikoke. For anthropogenic SO2 retrievals, the algorithm has been customized for N20/OMPS, considering its greater spatial resolution and reduced signal-to-noise ratio as compared with SNPP/OMPS. Over background areas, N20/OMPS SO2 slant column densities (SCD) show relatively small biases, comparable retrieval noise with SNPP/OMPS (after aggregation to the same spatial resolution), and remarkable stability with essentially no drift during 2018–2023. Over major anthropogenic source areas, the two OMPS retrievals are generally well-correlated but N20/OMPS SO2 is biased low especially for India and the Middle East, where the differences reach ~20 % on average. The reasons for these differences are not fully understood but are partly due to algorithmic differences. Better agreement (typical differences of ~10–15 %) is found over degassing volcanoes. SO2 emissions from large point sources, inferred from N20/OMPS retrievals, agree well with those based on OMI, SNPP/OMPS, and TROPOspheric Monitoring Instrument (TROPOMI), with correlation coefficients > 0.98 and overall differences < 10 %. The ratios between the estimated emissions and their uncertainties offer insights into the ability of different satellite instruments to detect and quantify SO2 sources. While TROPOMI has the highest ratios among all four sensors, ratios from N20/OMPS are slightly greater than OMI and substantially greater than SNPP/OMPS. Overall, our results suggest that the version 1 N20/OMPS SO2 product will successfully continue the long-term OMI and SNPP/OMPS SO2 data records. Efforts currently underway will further enhance the consistency of retrievals between different instruments, facilitating the development of multi-decade, coherent global SO2 datasets across multiple satellites.
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RC1: 'Comment on essd-2024-168', Anonymous Referee #1, 25 Jun 2024
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In their paper Can Li and co-authors present the NOAA-20/OMPS SO2 product. The paper is well written. It has a good introduction with a well chosen set of references. The reason for the work, linked to the creation of a multi-sensor long-term coherent NASA/NOAA SO2 data record, is motivated extensively (maybe even more than actually needed). The new dataset is complementing and extending the series from OMI and SNPP/OMPS, and it is important that this dataset is documented in the peer-reviewed literature. The added value of N20 compared to the other platforms is presented in a nice way. It was good to see the emission estimate comparisons, which are very convincing. I am in favour of publishing this work after my comments have been addressed.
General comments:
Validation (e.g. with MAXDOAS, PANDORA, IR satellite data) is not discussed in the paper. Could you add one or two paragraphs on how the (previous OMI/SNPP) retrieval compare with independent observations?
It seems that the product does not contain averaging kernels, like most recent satellite data products do. This would be useful, in particular for the PBL contributions and for data assimilation applications. Is there a chance that kernels will be added in a coming upgrade?
The retrieval is called "version 1", but there are still a few elements missing, in particular the cloud retrieval, AMF calculation and the SAA filtering. Is a new update (v1.1) foreseen for the near future to include these aspects? The final summary paragraph mentions further extensions using machine learning, but this sounds like a more longer term development path (v2.0).
Detailed comments:
l 125: "none-SO2 PCs". Should this be "non-SO2"?
l 141: "Process each orbit separately". If an orbit contains mainly ocean, is there still enough information stored in the PCA to descibe pixels over land? Isn't it better to train the PCA with one or multiple days of data?
l 183: (new volcanic screening): What is the impact? are there now more, or less pixels flagged?
l 194: "five subsectors". Are these five latitude bands? Why is this important? Please add a few lines to explain the subsectors.
l 202: "has not yet been implemented with N20/OMPS." Is there a special (technical) reason why this has not yet been implemented? The benefits seem to be big, as shown in Fig. 4.
l 203: "a fixed AMF (0.36) is used to convert all SCDs to SO2 VCDs," I was confused here, because line 169 mentioned "and a priori SO2 profiles based on a climatology from multi-year global model simulations". Please clarify. I assume this is linked to the missing cloud product. Maybe move this remark up to the beginning of the paragraph.
l 248: "the the"
Fig.2 left seems to indicate jumps in the NH. Is this within the noise, or linked somehow to the subsectors?
The biases seem to be linked to changes in the algorithm, and especially the threshold for SO2 containing pixels. In Figs 6 and 7 the product is again bias corrected to check consistency with SNPP. This leaves the question why the procedure was changed in N20 after all. Why do you bias-correct N20 and not SNPP? It would be useful to extend the discussion on this. Does the old procedure lead to problems for N20? If so, where do the problems occur and how big are these problems?
Fig.8: It is nice to see the N20/SNPP ratio plots. Indeed, this seems to indicate that the increase in resolution has a benefit over the lower SNR for emission estimates.
What I found surprising is the good match with TROPOMI. The retrieval is very different, the AMF is different and the SNR and resolution are also very different. It would be useful to discuss this in more detail, maybe even add an extra figure, and an extra paragraph. Apparently the local contrasts in SO2 columns and absolute column values are very similar compared to the NASA algorithm.l 448: A weighted average based on inverse variances is suitable for unbiased datasets. In the average of the four platforms algorithm and instrument differences play a role. Why did the authors choose this approach?
Sec 3.5: It would be interesting to see the TROPOMI results as well for the two eruptions.
Inviting one representative from the TROPOMI retrieval team as co-author could be considered.
The code and data availability section is missing.
Citation: https://doi.org/10.5194/essd-2024-168-RC1 -
RC2: 'Comment on essd-2024-168', Anonymous Referee #2, 27 Jun 2024
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Review of the manuscript “Version 1 NOAA-20/OMPS Nadir Mapper Total Column SO2 Product: Continuation of NASA Long-term Global Data Record” by Can Li et al.
The manuscript entitled “Version 1 NOAA-20/OMPS Nadir Mapper Total Column SO2 Product: Continuation of NASA Long-term Global Data Record“ describes the NOAA-20 (N20)/OMPS SO2 product, which aims at extending the long-term climate data record of OMI, SNPP/OMPS of SO2 column densities from both anthropogenic and volcanic activities.
The authors not only describe the new algorithm for N20/OMPS but also perform a comparison with the existing data record, showing the added value of this additional satellite product.
The manuscript is very well written and already in a very good state and require only minor revision, as detailed in the detailed comments hereafter:
Detailed comments:
Figure 1: Instead of showing arrows for each instrument that all end in 2024 it is perhaps better to show the planned mission timeline. Otherwise one gets the impression that all missions end in 2024 (except for JPSS3-4/OMPS). What is meant with “Direct readout only” for NOAA-21/OMPS?
Section 2.2.1 Line 134: Perhaps mention which RT code is used for the calculation of AMFs
Section 2.2.1 Line 162: You mention that the pixels are subdivided into 3 subgroups based on their latitude. What is the latitude range of each subgroup?
Section 2.2.2 Line 185: You are using two reference orbits to derive the PCs. Can you show or indicate the effect on your results when you use a different orbit/day, e.g. in 2024?
Section 2.3: I guess think this section should be moved to the end since it is out of context at this location and disturbs the readability.
Section 2.4 Line 248. Typo “the the”
Section 3.1, Figure 2 and 3: From the figure you see an offset between the mean SO2 VCD of SNPP/OMPS and N20/OMPS. Where is this bias of SNPP/OMPS coming from? Maybe you should address this as well. Does a rebinning of N2O/OMPS have an effect on the mean SCD and associated bias?
Section 3.2 Figure 4: Why do you see a stronger difference in mountain areas, especially in the South American Andes (negative) and Scandinavia (positive difference). Is this related to icy surfaces and related albedo effects?
Section 3.3 Third paragraph & Figure 6: The differences in the text and in the figure subtitles are slightly different, probably due to different rounding. E.g. for Norilsk a 8% difference is written in the text, but the figure title states 7% difference.
Section 3.3 Figure 6. It is really hard to distinguish the three colored lines from each other. Maybe it would help if you show only the timeframe with N20/OMPS results, i.e. show the plot with data from 2018 onwards?
Section 3.3 Figure 7 Same suggestion as the two above: Perhaps show only data for 2018+ and check numbers in text and figure title.
Section 3.4 Figure 8. The x axis label of d and e are missing a “/” character, i.e. N20/OMPS instead of N20 OMPS.
Section 3.4 Figure 8d-f. Perhaps you find a better y axis label, since “OMI and SNPP ratio” is a bit hard to understand when only looking at the figure. Perhaps use “OMI emission/uncertainty ratio” or so.
Section 3.5 Figure 10 Perhaps it would be useful to show the comparison with TROPOMI.
Section 4, This section should appear after the conclusions and then Section 2.3 should come after (see my comment above).
Citation: https://doi.org/10.5194/essd-2024-168-RC2
Data sets
OMPS-N20 NM PCA SO2 Step 1 Total Column 1-Orbit L2 Swath 17x13km Can Li et al. https://doi.org/10.5067/OMPS/OMPS_N20_NMSO2_PCA_L2_Step1.1
Multi-Satellite Air Quality Sulfur Dioxide (SO2) Database Long-Term L4 Global V2 Vitali Fioletov, Chris A. McLinden, Debora Griffin, Ihab Abboud, Nickolay Krotkov, Peter J. T. Leonard, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn https://doi.org/10.5067/MEASURES/SO2/DATA406
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