Articles | Volume 16, issue 15
https://doi.org/10.5194/gmd-16-4405-2023
https://doi.org/10.5194/gmd-16-4405-2023
Development and technical paper
 | 
02 Aug 2023
Development and technical paper |  | 02 Aug 2023

A Python library for computing individual and merged non-CO2 algorithmic climate change functions: CLIMaCCF V1.0

Simone Dietmüller, Sigrun Matthes, Katrin Dahlmann, Hiroshi Yamashita, Abolfazl Simorgh, Manuel Soler, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Christian Weder, Volker Grewe, Feijia Yin, and Federica Castino

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Cited articles

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Castino, F., Yin, F., Grewe, V., Soler, M., Simorgh, A., Yamashita, H., Matthes, S., Baumann, S., Dietmüller, S., Linke, F., and Lührs, B.: Seasonal Variability of Aircraft Trajectories reducing NOx-climate Impacts under a Multitude of Weather Patterns, in: 11th SESAR Innovation Days, online, 7–9 December 2021, https://pure.tudelft.nl/ws/portalfiles/portal/113785893/SIDs_2021_paper_81.pdf (last access: 3 March 2022), 2021. a, b
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Short summary
Climate-optimized aircraft trajectories avoid atmospheric regions with a large climate impact due to aviation emissions. This requires spatially and temporally resolved information on aviation's climate impact. We propose using algorithmic climate change functions (aCCFs) for CO2 and non-CO2 effects (ozone, methane, water vapor, contrail cirrus). Merged aCCFs combine individual aCCFs by assuming aircraft-specific parameters and climate metrics. Technically this is done with a Python library.
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