Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 1
Articles | Volume 14, issue 1
https://doi.org/10.5194/gmd-14-1-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-1-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 1
Model description paper
 | 
04 Jan 2021
Model description paper |  | 04 Jan 2021

IntelliO3-ts v1.0: a neural network approach to predict near-surface ozone concentrations in Germany

Felix Kleinert, Lukas H. Leufen, and Martin G. Schultz

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Short summary
With IntelliO3-ts v1.0, we present an artificial neural network as a new forecasting model for daily aggregated near-surface ozone concentrations with a lead time of up to 4 d. We used measurement and reanalysis data from more than 300 German monitoring stations to train, fine tune, and test the model. We show that the model outperforms standard reference models like persistence models and demonstrate that IntelliO3-ts outperforms climatological reference models for the first 2 d.
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