Articles | Volume 10, issue 2
https://doi.org/10.5194/amt-10-445-2017
https://doi.org/10.5194/amt-10-445-2017
Research article
 | 
06 Feb 2017
Research article |  | 06 Feb 2017

New-generation NASA Aura Ozone Monitoring Instrument (OMI) volcanic SO2 dataset: algorithm description, initial results, and continuation with the Suomi-NPP Ozone Mapping and Profiler Suite (OMPS)

Can Li, Nickolay A. Krotkov, Simon Carn, Yan Zhang, Robert J. D. Spurr, and Joanna Joiner

Related authors

Estimation of anthropogenic and volcanic SO2 emissions from satellite data in the presence of snow/ice on the ground
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023,https://doi.org/10.5194/amt-16-5575-2023, 2023
Short summary
Use of machine learning and principal component analysis to retrieve nitrogen dioxide (NO2) with hyperspectral imagers and reduce noise in spectral fitting
Joanna Joiner, Sergey Marchenko, Zachary Fasnacht, Lok Lamsal, Can Li, Alexander Vasilkov, and Nickolay Krotkov
Atmos. Meas. Tech., 16, 481–500, https://doi.org/10.5194/amt-16-481-2023,https://doi.org/10.5194/amt-16-481-2023, 2023
Short summary
Ground-level gaseous pollutants (NO2, SO2, and CO) in China: daily seamless mapping and spatiotemporal variations
Jing Wei, Zhanqing Li, Jun Wang, Can Li, Pawan Gupta, and Maureen Cribb
Atmos. Chem. Phys., 23, 1511–1532, https://doi.org/10.5194/acp-23-1511-2023,https://doi.org/10.5194/acp-23-1511-2023, 2023
Short summary
Version 2 of the global catalogue of large anthropogenic and volcanic SO2 sources and emissions derived from satellite measurements
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Ihab Abboud, Nickolay Krotkov, Peter J. T. Leonard, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Earth Syst. Sci. Data, 15, 75–93, https://doi.org/10.5194/essd-15-75-2023,https://doi.org/10.5194/essd-15-75-2023, 2023
Short summary
A new machine-learning-based analysis for improving satellite-retrieved atmospheric composition data: OMI SO2 as an example
Can Li, Joanna Joiner, Fei Liu, Nickolay A. Krotkov, Vitali Fioletov, and Chris McLinden
Atmos. Meas. Tech., 15, 5497–5514, https://doi.org/10.5194/amt-15-5497-2022,https://doi.org/10.5194/amt-15-5497-2022, 2022
Short summary

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
The importance of digital elevation model accuracy in XCO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product
Nicole Jacobs, Christopher W. O'Dell, Thomas E. Taylor, Thomas L. Logan, Brendan Byrne, Matthäus Kiel, Rigel Kivi, Pauli Heikkinen, Aronne Merrelli, Vivienne H. Payne, and Abhishek Chatterjee
Atmos. Meas. Tech., 17, 1375–1401, https://doi.org/10.5194/amt-17-1375-2024,https://doi.org/10.5194/amt-17-1375-2024, 2024
Short summary
Level0 to Level1B processor for MethaneAIR
Eamon K. Conway, Amir H. Souri, Joshua Benmergui, Kang Sun, Xiong Liu, Carly Staebell, Christopher Chan Miller, Jonathan Franklin, Jenna Samra, Jonas Wilzewski, Sebastien Roche, Bingkun Luo, Apisada Chulakadabba, Maryann Sargent, Jacob Hohl, Bruce Daube, Iouli Gordon, Kelly Chance, and Steven Wofsy
Atmos. Meas. Tech., 17, 1347–1362, https://doi.org/10.5194/amt-17-1347-2024,https://doi.org/10.5194/amt-17-1347-2024, 2024
Short summary
Exploiting the entire near-infrared spectral range to improve the detection of methane plumes with high-resolution imaging spectrometers
Javier Roger, Luis Guanter, Javier Gorroño, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 1333–1346, https://doi.org/10.5194/amt-17-1333-2024,https://doi.org/10.5194/amt-17-1333-2024, 2024
Short summary
A method for estimating localized CO2 emissions from co-located satellite XCO2 and NO2 images
Blanca Fuentes Andrade, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Andreas Richter, Hartmut Boesch, and John P. Burrows
Atmos. Meas. Tech., 17, 1145–1173, https://doi.org/10.5194/amt-17-1145-2024,https://doi.org/10.5194/amt-17-1145-2024, 2024
Short summary
The GeoCarb greenhouse gas retrieval algorithm: simulations and sensitivity to sources of uncertainty
Gregory R. McGarragh, Christopher W. O'Dell, Sean M. R. Crowell, Peter Somkuti, Eric B. Burgh, and Berrien Moore III
Atmos. Meas. Tech., 17, 1091–1121, https://doi.org/10.5194/amt-17-1091-2024,https://doi.org/10.5194/amt-17-1091-2024, 2024
Short summary

Cited articles

Ahmad, Z., Bhartia, P. K., and Krotkov, N.: Spectral properties of backscattered UV radiation in cloudy atmospheres, J. Geophys. Res., 109, D01201, https://doi.org/10.1029/2003JD003395, 2004.
Bhartia, P. K. and Wellemeyer, C. W.: OMI TOMS-V8 Total O3 Algorithm, Algorithm Theoretical Baseline Document: OMI Ozone Products, edited by: Bhartia, P. K., ATBD-OMI-02, version 2.0, available at: http://eospso.gsfc.nasa.gov/sites/default/files/atbd/ATBD-OMI-02.pdf (last access: 31 January 2017), 2002.
Bluth, G. J. S., Schnetzler, C. C., Krueger, A. J., and Walter, L. S.: The contribution of explosive volcanism to global atmospheric sulphur dioxide concentrations, Nature, 366, 327–329, 1993.
Burrows, J. P, Weber, M., Buchwitz, M., Rozanov, V. V., Ladstädter-Weissenmayer, A., Richter, A., de Beek, R., Hoogen, R., Bramstedt, K., Eichmann, K.-U., Eisinger, M., and Perner, D.: The Global Ozone Monitoring Experiment (GOME): Mission concept and first scientific results, J. Atmos. Sci., 56, 151–175, 1999.
Carn, S. A.: Multi-Satellite Volcanic Sulfur Dioxide (SO2) Database Long-Term L4 Global, Version 2, Goddard Earth Science Data and Information Services Center (GES DISC), Greenbelt, MD, USA, available at: http://disc.sci.gsfc.nasa.gov/datacollection/MSVOLSO2L4_V2.html (last access: 17 June 2016), 2015.
Download
Short summary
In this paper, we describe the new-generation OMI volcanic SO2 algorithm based on our principal component analysis (PCA) retrieval technique. We demonstrate significant improvement in the our new OMI volcanic SO2 data, with the retrieval noise reduced by a factor of 2 as compared with the previous dataset. The algorithm also improves the accuracy for large volcanic eruptions. It is also capable of producing consistent retrievals between different instruments.