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A python library for computing individual and merged non-CO2 algorithmic climate change functions: CLIMaCCF V1.0.
- Source :
-
Geoscientific Model Development Discussions . 10/17/2022, p1-33. 33p. - Publication Year :
- 2022
-
Abstract
- Aviation aims to reduce its climate impact by adopting trajectories, that avoid those 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 impact 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 here present the open-source Python Library called CLIMaCCF, an easy to use and flexible tool which efficiently calculates both the individual aCCFs (i.e., water vapour, nitrogen oxide (NOx) induced ozone and methane, and contrail-cirrus aCCFs) and the merged non-CO2 aCCFs that combine all these individual contributions. These merged aCCFs can be only constructed with the technical specification of aircraft/engine parameters, i.e., NOx emission indices and flown distance per kg burnt fuel. These aircraft/engine specific values are provided within CLIMaCCF version V1.0 for a set of aggregated aircraft/engine classes (i.e. regional, single-aisle, wide-body). Moreover, CLIMaCCF allows by a user-friendly configuration setting to choose between a set of different 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 by a series of example applications. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19919611
- Database :
- Academic Search Index
- Journal :
- Geoscientific Model Development Discussions
- Publication Type :
- Academic Journal
- Accession number :
- 159734323
- Full Text :
- https://doi.org/10.5194/gmd-2022-203