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Pletzer, Johannes (2026) stratospheric-transport. Zenodo. [Other]
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Official URL: https://zenodo.org/records/18868143
Abstract
Proof-of-concept: Physics-informed neural network for stratospheric transport. This repository provides a neural network for stratospheric transport studies. The model is designed to predict residence time from age-of-air observations using physics-informed or supervised boundaries. Data workflows for retrieval of renanalysis tropopause-derived features or retrieval of age-of-air training data are part of the repository. Three approaches to learn time patterns (seasonal, multi-annual, decadal) can be selected in addition.
| Item URL in elib: | https://elib.dlr.de/223231/ | ||||||||
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| Document Type: | Other | ||||||||
| Title: | stratospheric-transport | ||||||||
| Authors: |
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| Date: | March 2026 | ||||||||
| Refereed publication: | No | ||||||||
| Open Access: | No | ||||||||
| DOI: | 10.5281/zenodo.18868142 | ||||||||
| Publisher: | Zenodo | ||||||||
| Status: | Published | ||||||||
| Keywords: | pinn, physics-informed, neural network. stratosphere, residence time, age-of-air | ||||||||
| 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 - Air Transport Operations and Impact Assessment | ||||||||
| Location: | Oberpfaffenhofen | ||||||||
| Institutes and Institutions: | Institute of Atmospheric Physics > Earth System Modelling | ||||||||
| Deposited By: | Pletzer, Dr. Johannes | ||||||||
| Deposited On: | 05 Mar 2026 07:48 | ||||||||
| Last Modified: | 05 Mar 2026 10:56 |
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