The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/bea8a3fe-e34c-4598-9f94-c5a5c63348e5

Yin, Feijia; Castino, Federica; Rao, Pratik (2023): Data accompanying the manuscript "Predicting the climate impact of aviation for en-route emissions: The algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/bea8a3fe-e34c-4598-9f94-c5a5c63348e5.v1

Dataset

• Aerospace Transport
• Environmentally Sustainable Transport
• Atmospheric Sciences
• Earth Sciences
• Transport

algorithmic climate change functions, aviation climate impact, climate optimized flight trajectories, contrails

CC BY-NC 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Feijia Yin , Federica Castino , Pratik Rao

This dataset includes results data of the publication titled "Predicting the climate impact of aviation for en-route emissions: The algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53", which contains the average temperature response over 20 years estimated by the algorithmic climate change functions (aCCFs). The data has been produced by running the submodel ACCF v1.0 and the submodel AirTraf 2.0 coupled with the ECHAM5 Atmospheric-Chemistry Model (EMAC) framework over a year from December 2015 to December 2016.

• 2023-05-23 first online, published, posted

4TU.ResearchData

netCDF

Predicting the climate impact of aviation for en-route emissions: The algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53

• H2020 SESAR joint undertaking (grant code 891317) H2020

Aircraft Noise and Climate Effects, Faculty of Aerospace Engineering, Delft University of Technology