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

Dietmüller, Simone and Matthes, Sigrun and Dahlmann, Katrin and Yamashita, Hiroshi and Simorgh, Abolfazl and Soler, Manuel and Linke, Florian and Lührs, Benjamin and Meuser, Maximilian M. and Weder, Christian Martin and Grewe, Volker and Yin, Feijia and Castino, Federica (2023) A Python library for computing individual and merged non-CO2 algorithmic climate change functions: CLIMaCCF V1.0. Geoscientific Model Development (16), pp. 4405-4425. Copernicus Publications. doi: 10.5194/gmd-16-4405-2023. ISSN 1991-959X.

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Official URL: https://doi.org/10.5194/gmd-16-4405-2023


Aviation aims to reduce its climate effect by adopting trajectories that avoid regions of the atmosphere where aviation emissions have a large impact. To that end, prototype algorithmic climate change functions (aCCFs) can be used, which provide spatially and temporally resolved information on aviation's climate effect in terms of future near-surface temperature change. These aCCFs can be calculated with meteorological input data obtained from, e.g., numerical weather prediction models. We present here the open-source Python library called CLIMaCCF, an easy-to-use and flexible tool which efficiently calculates both the individual aCCFs (i.e., aCCF of water vapor, nitrogen oxide (NOx)-induced ozone production and methane depletion, and contrail cirrus) and the merged non-CO2 aCCFs that combine all these individual contributions. To construct merged aCCFs all individual aCCFs are converted to the same physical unit. This unit conversion needs the technical specification of aircraft and engine parameters, i.e., NOx emission indices and flown distance per kilogram of burned fuel. These aircraft- and engine-specific values are provided within CLIMaCCF version V1.0 for a set of aggregated aircraft and engine classes (i.e., regional, single-aisle, wide-body). Moreover, CLIMaCCF allows the user to choose from a range of physical climate metrics (i.e., average temperature response for pulse or future scenario emissions over the time horizons of 20, 50, or 100 years). Finally, we demonstrate the abilities of CLIMaCCF through a series of example applications.

Item URL in elib:https://elib.dlr.de/197192/
Document Type:Article
Title:A Python library for computing individual and merged non-CO2 algorithmic climate change functions: CLIMaCCF V1.0
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Matthes, SigrunDLR, IPAhttps://orcid.org/0000-0002-5114-2418UNSPECIFIED
Dahlmann, KatrinDLR, IPAhttps://orcid.org/0000-0003-3198-1713UNSPECIFIED
Yamashita, HiroshiDLR, IPAhttps://orcid.org/0000-0003-2458-1826UNSPECIFIED
Simorgh, AbolfazlUniversität Madrid, Spainhttps://orcid.org/0000-0002-8374-4915UNSPECIFIED
Soler, ManuelUniversität Madrid, Spainhttps://orcid.org/0000-0002-4664-1693UNSPECIFIED
Linke, FlorianUNSPECIFIEDhttps://orcid.org/0000-0003-1403-3471UNSPECIFIED
Meuser, Maximilian M.DLR, LufttransportsystemeUNSPECIFIEDUNSPECIFIED
Grewe, VolkerDLR, IPAhttps://orcid.org/0000-0002-8012-6783UNSPECIFIED
Yin, FeijiaDelft University of Technology, Delft, NLUNSPECIFIEDUNSPECIFIED
Castino, FedericaDelft University of Technology, Delfthttps://orcid.org/0000-0002-7069-0356UNSPECIFIED
Date:2 August 2023
Journal or Publication Title:Geoscientific Model Development
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Page Range:pp. 4405-4425
Publisher:Copernicus Publications
Keywords:spatially and temporally resolved climate impact of aviation, algorithmic climate change functions
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 > Earth System Modelling
Deposited By: Dietmüller, Simone
Deposited On:12 Sep 2023 07:45
Last Modified:18 Sep 2023 08:13

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