Articles | Volume 19, issue 12
https://doi.org/10.5194/gmd-19-5765-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-5765-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
01 Jul 2026
Methods for assessment of models |
| 01 Jul 2026
| 01 Jul 2026
TOAR-classifier v2: a data-driven classification tool for global air quality stations
Ramiyou Karim Mache
CORRESPONDING AUTHOR
independent researcher
formerly at: Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
Sabine Schröder
Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
Michael Langguth
independent researcher
formerly at: Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
Ankit Patnala
Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
Martin G. Schultz
Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
Department of Mathematics and Computer Science, University of Cologne, Cologne, Germany
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Short summary
The TOAR-classifier model is a data-driven tool that allows for an objective classification of air quality measuring stations as urban, rural, or suburban. Such classification is important in the analysis of air pollutant trends and regional signatures. The model is employed in the second Tropospheric Ozone Assessment Report but can also be used in other research work.
The TOAR-classifier model is a data-driven tool that allows for an objective classification of...
