Global, high-resolution mapping of tropospheric ozone – explainable machine learning and impact of uncertainties

The preprint of the article “Global, high-resolution mapping of tropospheric ozone – explainable machine learning and impact of uncertainties” is now available here: https://doi.org/10.5194/gmd-2022-2

This work is a follow-up collaboration between KISTE members and Clara Betancourt. To create a reliable map of average ozone on a global scale using machine learning, the researchers combined their knowledge in explainable machine learning and uncertainty quantification.