Articles | Volume 18, issue 11
https://doi.org/10.5194/amt-18-2333-2025
https://doi.org/10.5194/amt-18-2333-2025
Research article
 | 
03 Jun 2025
Research article |  | 03 Jun 2025

A channel selection methodology for enhancing volcanic SO2 monitoring using FY-3E/HIRAS-II hyperspectral data

Xinyu Li, Lin Zhu, Hongfu Sun, Jun Li, Ximing Lv, Chengli Qi, and Huanhuan Yan

Related authors

Technical note: Applicability of physics-based and machine-learning-based algorithms of a geostationary satellite in retrieving the diurnal cycle of cloud base height
Mengyuan Wang, Min Min, Jun Li, Han Lin, Yongen Liang, Binlong Chen, Zhigang Yao, Na Xu, and Miao Zhang
Atmos. Chem. Phys., 24, 14239–14256, https://doi.org/10.5194/acp-24-14239-2024,https://doi.org/10.5194/acp-24-14239-2024, 2024
Short summary
Reconstruction of 3D precipitation measurements from FY-3G MWRI-RM imaging and sounding channels
Yunfan Yang, Wei Han, Haofei Sun, Jun Li, Jiapeng Yan, and Zhiqiu Gao
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-175,https://doi.org/10.5194/amt-2024-175, 2024
Revised manuscript accepted for AMT
Short summary
Applicability of physics-based and machine-learning-based algorithms of geostationary satellite in retrieving the diurnal cycle of cloud base height
Mengyuan Wang, Min Min, Jun Li, Han Lin, Yongen Liang, Binlong Chen, Zhigang Yao, Na Xu, and Miao Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2023-2843,https://doi.org/10.5194/egusphere-2023-2843, 2023
Preprint archived
Short summary
Optimal estimation retrieval of tropospheric ammonia from the Geostationary Interferometric Infrared Sounder on board FengYun-4B
Zhao-Cheng Zeng, Lu Lee, Chengli Qi, Lieven Clarisse, and Martin Van Damme
Atmos. Meas. Tech., 16, 3693–3713, https://doi.org/10.5194/amt-16-3693-2023,https://doi.org/10.5194/amt-16-3693-2023, 2023
Short summary
Diurnal carbon monoxide observed from a geostationary infrared hyperspectral sounder: first result from GIIRS on board FengYun-4B
Zhao-Cheng Zeng, Lu Lee, and Chengli Qi
Atmos. Meas. Tech., 16, 3059–3083, https://doi.org/10.5194/amt-16-3059-2023,https://doi.org/10.5194/amt-16-3059-2023, 2023
Short summary

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Retrieval of NO2 profiles from 3 years of Pandora MAX-DOAS measurements in Toronto, Canada
Ramina Alwarda, Kristof Bognar, Xiaoyi Zhao, Vitali Fioletov, Jonathan Davies, Sum Chi Lee, Debora Griffin, Alexandru Lupu, Udo Frieß, Alexander Cede, Yushan Su, and Kimberly Strong
Atmos. Meas. Tech., 18, 2397–2423, https://doi.org/10.5194/amt-18-2397-2025,https://doi.org/10.5194/amt-18-2397-2025, 2025
Short summary
Predictions of failed satellite retrieval of air quality using machine learning
Edward Malina, Jure Brence, Jennifer Adams, Jovan Tanevski, Sašo Džeroski, Valentin Kantchev, and Kevin W. Bowman
Atmos. Meas. Tech., 18, 1689–1715, https://doi.org/10.5194/amt-18-1689-2025,https://doi.org/10.5194/amt-18-1689-2025, 2025
Short summary
Deep transfer learning method for seasonal TROPOMI XCH4 albedo correction
Alexander C. Bradley, Barbara Dix, Fergus Mackenzie, J. Pepijn Veefkind, and Joost A. de Gouw
Atmos. Meas. Tech., 18, 1675–1687, https://doi.org/10.5194/amt-18-1675-2025,https://doi.org/10.5194/amt-18-1675-2025, 2025
Short summary
Global retrieval of TROPOMI tropospheric HCHO and NO2 columns with improved consistency based on the updated Peking University OMI NO2 algorithm
Yuhang Zhang, Huan Yu, Isabelle De Smedt, Jintai Lin, Nicolas Theys, Michel Van Roozendael, Gaia Pinardi, Steven Compernolle, Ruijing Ni, Fangxuan Ren, Sijie Wang, Lulu Chen, Jos Van Geffen, Mengyao Liu, Alexander M. Cede, Martin Tiefengraber, Alexis Merlaud, Martina M. Friedrich, Andreas Richter, Ankie Piters, Vinod Kumar, Vinayak Sinha, Thomas Wagner, Yongjoo Choi, Hisahiro Takashima, Yugo Kanaya, Hitoshi Irie, Robert Spurr, Wenfu Sun, and Lorenzo Fabris
Atmos. Meas. Tech., 18, 1561–1589, https://doi.org/10.5194/amt-18-1561-2025,https://doi.org/10.5194/amt-18-1561-2025, 2025
Short summary
Quantitative estimate of several sources of uncertainty in drone-based methane emission measurements
Tannaz H. Mohammadloo, Matthew Jones, Bas van de Kerkhof, Kyle Dawson, Brendan J. Smith, Stephen Conley, Abigail Corbett, and Rutger IJzermans
Atmos. Meas. Tech., 18, 1301–1324, https://doi.org/10.5194/amt-18-1301-2025,https://doi.org/10.5194/amt-18-1301-2025, 2025
Short summary

Cited articles

Ackerman, S. A., Schreiner, A. J., Schmit, T. J., Woolf, H. M., Li, J., and Pavolonis, M.: Using the GOES Sounder to monitor upper level SO2 from volcanic eruptions, J. Geophys. Res., 113, D14S11, https://doi.org/10.1029/2007JD009622, 2008. 
Aires, F., Chédin, A., Scott, N. A., and Rossow, W. B.: A regularized neural net approach for retrieval of atmospheric and surface temperatures with the IASI instrument, J. Appl. Meteorol., 41, 144–159, https://doi.org/10.1175/1520-0450(2002)041<0144:ARNNAF>2.0.CO;2, 2002. 
Aires, F., Pellet, V., Prigent, C., and Moncet, J.-L.: Dimension reduction of satellite observations for remote sensing. Part 1: A comparison of compression, channel selection and bottleneck channel approaches, Q. J. Roy. Meteor. Soc., 142, 2658–2669, https://doi.org/10.1002/qj.2855, 2016. 
Bauduin, S., Clarisse, L., Theunissen, M., George, M., Hurtmans, D., Clerbaux, C., and Coheur, P. F.: IASI's sensitivity to near-surface carbon monoxide (CO): Theoretical analyses and retrievals on test cases, J. Quant. Spectrosc. Ra., 189, 428–440, https://doi.org/10.1016/j.jqsrt.2016.12.022, 2017. 
Cady-Pereira, K., Alvarado, M., Mlawer, E., Iacono, M., Delamere, J., and Pernak, R.: AER Line File Parameters (v3.8.2), Zenodo [data set], https://doi.org/10.5281/zenodo.7853414, 2020. 
Download
Short summary
This paper proposes a novel methodology for selecting sulfur-dioxide-sensitive channels from FY-3E/HIRAS-II hyperspectral IR atmospheric sensors to quantitatively monitor volcanic sulfur dioxide. This methodology considers the interference of atmospheric temperature, humidity, and surface temperature with sulfur dioxide detection and retrieval, laying the groundwork for developing a more accurate and flexible volcanic sulfur dioxide retrieval algorithm under different atmospheric conditions.
Share