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Vahid Yousefnia, Kianusch and Bölle, Tobias and Metzl, Christoph (2024) SALAMA. [Other]
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Abstract
SALAMA 1D is a deep neural network model designed to infer the probability of thunderstorm occurrence from the vertical profiles of ten atmospheric fields from numerical weather prediction (NWP).
| Item URL in elib: | https://elib.dlr.de/209207/ | ||||||||||||||||
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| Document Type: | Other | ||||||||||||||||
| Title: | SALAMA | ||||||||||||||||
| Authors: |
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| Date: | 24 November 2024 | ||||||||||||||||
| Journal or Publication Title: | zenodo.org | ||||||||||||||||
| Refereed publication: | No | ||||||||||||||||
| Open Access: | No | ||||||||||||||||
| DOI: | 10.5281/zenodo.14212889 | ||||||||||||||||
| Status: | Published | ||||||||||||||||
| Keywords: | Machine Learning, thunderstorms, numerical weather prediction, deep moist convection | ||||||||||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||
| HGF - Program: | Aeronautics | ||||||||||||||||
| HGF - Program Themes: | Air Transportation and Impact | ||||||||||||||||
| DLR - Research area: | Aeronautics | ||||||||||||||||
| DLR - Program: | L AI - Air Transportation and Impact | ||||||||||||||||
| DLR - Research theme (Project): | L - Climate, Weather and Environment | ||||||||||||||||
| Location: | Oberpfaffenhofen | ||||||||||||||||
| Institutes and Institutions: | Institute of Atmospheric Physics > Applied Meteorology | ||||||||||||||||
| Deposited By: | Vahid Yousefnia, Kianusch | ||||||||||||||||
| Deposited On: | 25 Nov 2024 08:01 | ||||||||||||||||
| Last Modified: | 25 Nov 2024 08:01 |
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