Articles | Volume 22, issue 17
https://doi.org/10.5194/acp-22-11603-2022
https://doi.org/10.5194/acp-22-11603-2022
Research article
 | 
08 Sep 2022
Research article |  | 08 Sep 2022

Model output statistics (MOS) applied to Copernicus Atmospheric Monitoring Service (CAMS) O3 forecasts: trade-offs between continuous and categorical skill scores

Hervé Petetin, Dene Bowdalo, Pierre-Antoine Bretonnière, Marc Guevara, Oriol Jorba, Jan Mateu Armengol, Margarida Samso Cabre, Kim Serradell, Albert Soret, and Carlos Pérez Garcia-Pando

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Cited articles

Borrego, C., Monteiro, A., Pay, M., Ribeiro, I., Miranda, A., Basart, S., and Baldasano, J.: How bias-correction can improve air quality forecasts over Portugal, Atmos. Environ., 45, 6629–6641, https://doi.org/10.1016/j.atmosenv.2011.09.006, 2011. a
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Copernicus Climate Change Service (C3S): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate, 2017. a
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This study investigates the extent to which ozone forecasts provided by the Copernicus Atmospheric Monitoring Service (CAMS) can be improved using surface observations and state-of-the-art statistical methods. Through a case study over the Iberian Peninsula in 2018–2019, it unambiguously demonstrates the value of these methods for improving the raw CAMS O3 forecasts while at the same time highlighting the complexity of improving the detection of the highest O3 concentrations.
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