Intercomparison of global ground-level ozone datasets for health-relevant metrics

Wang, Hantao; Miyazaki, Kazuyuki; Sun, Haitong Zhe; Qu, Zhen; Liu, Xiang; Inness, Antje; Schultz, Martin; Schröder, Sabine; Serre, Marc; West, J. Jason

doi:10.5194/acp-25-15969-2025

Articles | Volume 25, issue 22

https://doi.org/10.5194/acp-25-15969-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Tropospheric Ozone Assessment Report Phase II (TOAR-II) Community...

https://doi.org/10.5194/acp-25-15969-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 22

Research article

|

18 Nov 2025

Research article |

| 18 Nov 2025

Intercomparison of global ground-level ozone datasets for health-relevant metrics

Hantao Wang, Kazuyuki Miyazaki, Haitong Zhe Sun, Zhen Qu, Xiang Liu, Antje Inness, Martin Schultz, Sabine Schröder, Marc Serre, and J. Jason West

Supplement

https://doi.org/10.5194/acp-25-15969-2025-supplement

Data sets

Global Surface Ozone Concentration Dataset 1990-2017 Mapped at Fine Resolution through the Bayesian Maximum Entropy Data Fusion of Observations and Model Output (2.0) Marissa N. DeLang et al. https://doi.org/10.5281/zenodo.10498857

Second release of the data associated with the paper entitled "Cluster-enhanced ensemble learning for mapping global monthly surface ozone from 2003 to 2019" Xiang Liu et al. https://doi.org/10.5281/zenodo.6378092

CAMS global reanalysis (EAC4) Copernicus Atmosphere Monitoring Service https://doi.org/10.24381/d58bbf47

TROPESS Chemical Reanalysis Surface O3 2-Hourly 2-dimensional Product V1 Kazuyuki Miyazaki https://doi.org/10.5067/NN87W53OVGUS

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Short summary

We compare six datasets of global ground-level ozone, developed using geostatistical, machine learning, or reanalysis methods. The datasets show important differences from one another in ozone magnitude, greater than 5 ppb, and trends, globally and regionally. Compared with measurements, performance varies among datasets, and most overestimate ozone, particularly at lower concentrations. These differences among datasets highlight uncertainties for applications to health and other impacts.