Copyright Notice:

The documents distributed by this server have been provided by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a noncommercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Publications of SPCL

P. Grönquist, T. Ben-Nun, N. Dryden, P. Dueben, L. Lavarini, S. Li, T. Hoefler:

 Predicting Weather Uncertainty with Deep Convnets

(In Machine Learning and the Physical Sciences Workshop at the 33rd Conference on Neural Information Processing Systems (NeurIPS), presented in Vancouver, BC, Canada, , Dec. 2019)

Abstract

Modern weather forecast models perform uncertainty quantification using ensemble prediction systems, which collect nonparametric statistics based on multiple perturbed simulations. To provide accurate estimation, dozens of such computationally intensive simulations must be run. We show that deep neural networks can be used on a small set of numerical weather simulations to estimate the spread of a weather forecast, significantly reducing computational cost. To train the system, we both modify the 3D U-Net architecture and explore models that incorporate temporal data. Our models serve as a starting point to improve uncertainty quantification in current real-time weather forecasting systems, which is vital for predicting extreme events.

Documents

access preprint on arxiv:
 

BibTeX

@article{,
  author={Peter Grönquist and Tal Ben-Nun and Nikoli Dryden and Peter Dueben and Luca Lavarini and Shigang Li and Torsten Hoefler},
  title={{Predicting Weather Uncertainty with Deep Convnets}},
  year={2019},
  month={12},
  booktitle={Machine Learning and the Physical Sciences Workshop at the 33rd Conference on Neural Information Processing Systems (NeurIPS)},
  location={Vancouver, BC, Canada},
  publisher={},
}