the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 May 2025
Retrieval of SO2 columns from FY3F/OMS instrument observations
Abstract. Atmospheric SO2 has a significant impact on the urban environment and on global climate. Remote sensing provides an unprecedented tool for the continuous and real-time monitoring of atmospheric SO2 from volcanic eruptions and anthropogenic emissions. The Ozone Monitoring Suite (OMS) onboard the Chinese FENGYUN-3F (FY-3F) satellite launched in August 2023 is a new hyperspectral UV-VIS instrument in the FY-3 family of satellites, aiming to obtain information about atmospheric trace gases. In this study, we use the OMS Nadir (OMS-N) top-of-atmosphere (TOA) measurements and Differential Optical Absorption Spectroscopy (DOAS) inversion to for the first time retrieve global SO2 columns from these measurements. Based on the characteristics of the OMS instrument and the performance of its L1 data, specific schemes including solar spectrum selection, spectral soft calibration, and background offset correction were developed to effectively reduce along-track stripes and across-track asymmetry found in the initial OMS SO2 retrievals. The accuracy of FY-3F/OMS SO2 retrievals was evaluated by comparing them with the DOAS and COvariance-Based Retrieval Algorithm (COBRA) SO2 products from the TROPOspheric Monitoring Instrument (TROPOMI) onboard Copernicus Sentinel-5 Precursor (Sentinel-5P) over three typical areas: clean oceanic regions, volcanic eruption regions, and anthropogenic emission regions. The results indicate that the OMS SO2 retrievals exhibit good stability over clean oceanic regions, successfully capture volcanic SO2 plumes, and effectively detect the elevated SO2 columns from anthropogenic emissions in regions such as the Middle East, Eastern India, and Northern Russia. Air mass factor (AMF) uncertainty remains the primary error source of this first version of OMS SO2 retrievals. This study is the first to present SO2 retrievals from FY3F/OMS observations, which is crucial for a comprehensive understanding of OMS’s capability in SO2 retrievals.
Competing interests: The second author "Andreas Richter" is one of the Executive Editors at the EGU journal Atmospheric Measurement Techniques.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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RC1: 'Comment on egusphere-2025-2177', Anonymous Referee #1, 01 Jul 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2177/egusphere-2025-2177-RC1-supplement.pdf
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AC1: 'Reply on RC1', huanhuan yan, 09 Sep 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2177/egusphere-2025-2177-AC1-supplement.pdf
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AC1: 'Reply on RC1', huanhuan yan, 09 Sep 2025
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RC2: 'Comment on egusphere-2025-2177', Anonymous Referee #2, 29 Jul 2025
The paper introduces the first SO2 column retrievals from the new FY-3F/OMS instrument using the DOAS method, leveraging the TSIS HSRS solar reference and incorporating essential calibration and background correction steps. While the initial validation against TROPOMI provides a strong foundation for the OMS SO2 product, the manuscript would benefit from clearer explanations of uncertainties and the implications of its current simplifications. Below are specific comments and questions for further consideration.
1. The authors refer to this as the “first version” of the OMS SO2 It would be useful to clearly state this in the title or abstract to manage reader expectations about its development stage and limitations.
2. The paper (L95-96)recommends filtering OMS data for SZA < 70°, near-nadir, and cloud-free pixels. Were these recommended filters (including cloud-free) applied to the OMS data before comparison with TROPOMI? Please clarify the exact filtering used, especially given the statement about no cloud products.
3. The paper mentions the use of the TSIS HSRS hybrid solar reference spectrum instead of OMS L1 solar irradiance due to degradation. Could this lead to systematic biases in the long term?What plans are in place to account for this degradation?
4. The results in Figure 2 from using the 325–335 nm and 360–390 nm windows alone appear unconvincing. While these windows might be noisy in isolation, their value (as seen in TROPOMI's algorithm) lies in their combined use with stronger windows to avoid saturation at high SO2 Since OMS shows saturation and underestimation for high SO2, have the authors explored a multi-window fitting strategy to improve this?
5. Section 3.3.2 states a single fixed Ring spectrum was used. However, Figure 19 clearly shows the Ring spectrum varies significantly with atmospheric and viewing conditions. Please clarify this apparent contradiction: was a single fixed Ring spectrum or a variable one used? If a single fixed spectrum was used, the significant error introduced by ignoring these variations should be quantitatively discussed andthe actual Ring spectrum settings should be reflected in Table 3.
6. Whatimprovements are considered at orbit edges in a future update?
7. For the Persian Gulf, the 0.5-0.6 correlations are not particularly high. What does this imply regarding the agreement between the OMS and TROPOMI products, and what factors contribute to these differences?
8. How much does the difference of the overpass time between OMS and TROPOMI contribute to the observed differences in SO2retrievals, particularly in dynamic regions like volcanic or strong anthropogenic plumes?
9. The paper highlights the simplified AMF approach as introducing significant errors and large uncertainties. Could the authors elaborate further on the estimated magnitude of biases introduced by these simplifications across a range of atmospheric and surface conditions? Furthermore, to enhance the accuracy and robustness of the product, particularly in complex regions like urban areas or near industrial sources, what are the plans for incorporating a more physically-based AMF calculation?
10. The current retrieval does not account for cloud and aerosol effects, which can introduce significant biases, particularly for boundary layer SO2. What are the plans to integrate cloud and aerosol effects into future updates of the retrieval algorithm?
Citation: https://doi.org/10.5194/egusphere-2025-2177-RC2 -
AC2: 'Reply on RC2', huanhuan yan, 09 Sep 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2177/egusphere-2025-2177-AC2-supplement.pdf
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AC2: 'Reply on RC2', huanhuan yan, 09 Sep 2025
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