Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 9
Articles | Volume 17, issue 9
https://doi.org/10.5194/gmd-17-3839-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-3839-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 9
Model description paper
 | 
14 May 2024
Model description paper |  | 14 May 2024

DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties

Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen

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Short summary
Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
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