Supporting data and code for "Data-driven discovery and model reduction methods for the atmospheric effects of high altitude emissions"
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This repository contains the data and code supporting the journal article "Data-driven discovery and model reduction methods for the atmospheric effects of high altitude emissions" in Geoscientific Model Development (https://doi.org/10.5194/gmd-19-1867-2026). The repository contains two archives: The PREPROCESSED archive contains pre-processed data describing the zonal-average changes in the ozone distribution (in kg) in response to supersonic emission scenarios, these datasets are based on data from van 't Hoff et al. 2025 and 2024. The CODE archive contains a set of python files containing the code used for the generation of the results of the manuscript associated with this dataset. The README file contains a summary of the archive's contents and how to use the code within this repository. The data supporting this work is made public as supplementary data to this article, and in order to allow other researchers to use these datasets for their own research. The dataset was generated using computational resources of the Cartesius and Snellius supercomputers of the Dutch e-infrastructure network provided by the SURF collective under grant numbers EINF-1504, EINF-3690, and …
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