Atmosphere, Volume 11, Issue 3 (March 2020) – 92 articles
Cover Story (view full-size image): One of the most crucial applications of radar-based precipitation nowcasting systems is the short-term forecast of extreme rainfall. A novel method to improve deep learning prediction skills of extreme rainfall regimes is presented based on model stacking. A convolutional neural network is trained to combine an ensemble of deep learning models along with orographic features, doubling the prediction skills with respect to the ensemble members and their average on extreme rain rates, and outperforming them on all rain regimes. The ensemble is built by training four models with the same architecture over different rainfall thresholds. This combination can reach the same skill of Lagrangian persistence on extreme rain rates while retaining a superior performance on lower rain regimes. View this paper.
- Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
- You may sign up for e-mail alerts to receive table of contents of newly released issues.
- PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.