Journal article
Using deep learning for an analysis of atmospheric rivers in a high-resolution large ensemble climate data set
- Abstract:
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There is currently large uncertainty over the impacts of climate change on precipitation trends over the US west coast. Atmospheric rivers (ARs) are a significant source of US west coast precipitation and trends in ARs can provide insight into future precipitation trends. There are already a variety of different methods used to identify ARs, but many are used in contexts that are often difficult to apply to large climate datasets due to their computational cost and requirement of integrated v...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 2.2MB, Terms of use)
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- Publisher copy:
- 10.1029/2022MS003495
Authors
Bibliographic Details
- Publisher:
- American Geophysical Union
- Journal:
- Journal of Advances in Modeling Earth Systems More from this journal
- Volume:
- 15
- Issue:
- 4
- Article number:
- e2022MS003495
- Publication date:
- 2023-04-15
- Acceptance date:
- 2023-04-05
- DOI:
- EISSN:
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1942-2466
Item Description
- Language:
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English
- Keywords:
- Pubs id:
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1337560
- Local pid:
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pubs:1337560
- Deposit date:
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2023-04-17
Terms of use
- Copyright holder:
- Higgins et al.
- Copyright date:
- 2023
- Rights statement:
- © 2023 The Authors. Journal of Advances in Modeling Earth Systems published by Wiley Periodicals LLC on behalf of American Geophysical Union. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
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