Articles | Volume 25, issue 15
https://doi.org/10.5194/acp-25-8533-2025
https://doi.org/10.5194/acp-25-8533-2025
Research article
 | 
07 Aug 2025
Research article |  | 07 Aug 2025

Quantifying biases in TROPESS AIRS, CrIS, and joint AIRS+OMI tropospheric ozone products using ozonesondes

Elyse A. Pennington, Gregory B. Osterman, Vivienne H. Payne, Kazuyuki Miyazaki, Kevin W. Bowman, and Jessica L. Neu

Related authors

Tropospheric Ozone Assessment Report (TOAR): 16-year ozone trends from the IASI Climate Data Record
Anne Boynard, Catherine Wespes, Juliette Hadji-Lazaro, Selviga Sinnathamby, Daniel Hurtmans, Pierre-François Coheur, Marie Doutriaux-Boucher, Jacobus Onderwaater, Wolfgang Steinbrecht, Elyse A. Pennington, Kevin Bowman, and Cathy Clerbaux
EGUsphere, https://doi.org/10.5194/egusphere-2025-1054,https://doi.org/10.5194/egusphere-2025-1054, 2025
Short summary
Applications of Machine Learning and Artificial Intelligence in Tropospheric Ozone Research
Sebastian H. M. Hickman, Makoto Kelp, Paul T. Griffiths, Kelsey Doerksen, Kazuyuki Miyazaki, Elyse A. Pennington, Gerbrand Koren, Fernando Iglesias-Suarez, Martin G. Schultz, Kai-Lan Chang, Owen R. Cooper, Alexander T. Archibald, Roberto Sommariva, David Carlson, Hantao Wang, J. Jason West, and Zhenze Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3739,https://doi.org/10.5194/egusphere-2024-3739, 2025
Short summary
An updated modeling framework to simulate Los Angeles air quality – Part 1: Model development, evaluation, and source apportionment
Elyse A. Pennington, Yuan Wang, Benjamin C. Schulze, Karl M. Seltzer, Jiani Yang, Bin Zhao, Zhe Jiang, Hongru Shi, Melissa Venecek, Daniel Chau, Benjamin N. Murphy, Christopher M. Kenseth, Ryan X. Ward, Havala O. T. Pye, and John H. Seinfeld
Atmos. Chem. Phys., 24, 2345–2363, https://doi.org/10.5194/acp-24-2345-2024,https://doi.org/10.5194/acp-24-2345-2024, 2024
Short summary

Related subject area

Subject: Gases | Research Activity: Remote Sensing | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
State-wide California 2020 carbon dioxide budget estimated with OCO-2 and OCO-3 satellite data
Matthew S. Johnson, Sofia D. Hamilton, Seongeun Jeong, Yu Yan Cui, Dien Wu, Alex Turner, and Marc Fischer
Atmos. Chem. Phys., 25, 8475–8492, https://doi.org/10.5194/acp-25-8475-2025,https://doi.org/10.5194/acp-25-8475-2025, 2025
Short summary
Satellite detection of NO2 distributions using TROPOMI and TEMPO and comparison with ground-based concentration measurements
Summer Acker, Tracey Holloway, and Monica Harkey
Atmos. Chem. Phys., 25, 8271–8288, https://doi.org/10.5194/acp-25-8271-2025,https://doi.org/10.5194/acp-25-8271-2025, 2025
Short summary
Measurement report: Diurnal variability in NO2 and HCHO lower-tropospheric vertical profiles in southeastern Los Angeles
Peter K. Peterson, Lisa F. Hernandez, Leslie Tanaka, and Alejandro Dunnick
Atmos. Chem. Phys., 25, 7777–7788, https://doi.org/10.5194/acp-25-7777-2025,https://doi.org/10.5194/acp-25-7777-2025, 2025
Short summary
Biosphere–atmosphere related processes influence trace-gas and aerosol satellite–model biases
Emma Sands, Ruth M. Doherty, Fiona M. O'Connor, Richard J. Pope, James Weber, and Daniel P. Grosvenor
Atmos. Chem. Phys., 25, 7269–7297, https://doi.org/10.5194/acp-25-7269-2025,https://doi.org/10.5194/acp-25-7269-2025, 2025
Short summary
Estimation of diurnal emissions of CO2 from thermal power plants using spaceborne integrated path differential absorption (IPDA) lidar
Xuanye Zhang, Hailong Yang, Lingbing Bu, Zengchang Fan, Wei Xiao, Binglong Chen, Lu Zhang, Sihan Liu, Zhongting Wang, Jiqiao Liu, Weibiao Chen, and Xuhui Lee
Atmos. Chem. Phys., 25, 6725–6740, https://doi.org/10.5194/acp-25-6725-2025,https://doi.org/10.5194/acp-25-6725-2025, 2025
Short summary

Cited articles

AIRS: AIRS/Aqua L1B Infrared (IR) geolocated and calibrated radiances V005, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/YZEXEVN4JGGJ, 2007. a
AIRS: Aqua/AIRS L2 Near Real Time (NRT) Standard Physical Retrieval (AIRS-only) V7.0, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/RAEHAOH4VZM5, 2019. a
Aumann, H., Chahine, M., Gautier, C., Goldberg, M., Kalnay, E., McMillin, L., Revercomb, H., Rosenkranz, P., Smith, W., Staelin, D., Strow, L., and Susskind, J.: AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products, and processing systems, IEEE T. Geosci. Remote Sens., 41, 253–264, https://doi.org/10.1109/TGRS.2002.808356, 2003. a, b
Barnet, C. D., Divakarla, M., Gambacorta, A., Iturbide-Sanchez, F., Nalli, N. R., Pryor, K., Tan, C., Wang, T., Warner, J., Zhang, K., and Zhu, T.: NOAA Unique Combined Atmospheric Processing System (NUCAPS): Algorithm Theoretical Basis Document, Tech. Rep. Version 3.1, NOAA NESDIS STAR, https://www.star.nesdis.noaa.gov/jpss/documents/ATBD/ATBD_NUCAPS_v3.1.pdf (last access: 22 November 2024), 2021. a
Beer, R.: TES on the aura mission: scientific objectives, measurements, and analysis overview, IEEE T. Geosci. Remote Sens., 44, 1102–1105, https://doi.org/10.1109/TGRS.2005.863716, 2006. a
Download
Short summary
Tropospheric ozone is a harmful pollutant and powerful greenhouse gas. For satellite products to accurately quantify trends in tropospheric ozone, they must have a low bias compared to a reliable source of data. This study compares three NASA satellite products to ozonesonde data. They have low global measurement bias and thus can be used to detect global tropospheric ozone trends, but the measurement bias should be considered in certain regions and time periods.
Share
Altmetrics
Final-revised paper
Preprint