GENERAL INFORMATION ------------------- 1. Dataset Title: (Data accompanying the manuascript "Predicting the climate impact of aviation for en-route emissions: The algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53") 2. Authorship: Name: Feijia Yin Institution: TU Delft Email: F.Yin@tudelft.nl ORCID: https://orcid.org/0000-0002-6081-9136 (---------ADD----------) Name: Federica Castino Institution: TU Delft Email: F.Castino@tudelft.nl ORCID: https://orcid.org/0000-0002-7069-0356 (---------ADD----------) DESCRIPTION ----------- 1. Abstract: This dataset consists of the data used in the study published by Yin et al., 2022 (https://doi.org/10.5194/gmd-2022-220) In particular, we indicate below which figures can be reproduced using each file: Figures File 7 ------------- Annual_mean_FATR20_CH4_PMO_2016.nc 8 ------------- Annual_mean_FATR20_contrail_2016.nc 7 ------------- Annual_mean_FATR20_H2O_2016.nc 7 ------------- Annual_mean_FATR20_O3_2016.nc 7,8 ----------- Annual_mean_Surface_Pressure_2016.nc 3 ------------- Atmospheric_conditions_20151218_0000_ECHAM5.nc 4,5,6 --------- Climate_impact_aviation_20151218_0000_accf_gp.nc 10 ------------ NOx_O3_optimal_aircraft_trajectories_daily_airtraf_ac.nc 10 ------------ Cost_optimal_aircraft_trajectories_daily_airtraf_ac.nc 11 ------------ NOx_mixing ratio_diff_ClimCost_monmean.nc 11 ------------ O3_mixing ratio_diff_ClimCost_monmean.nc 12 ------------ Climate_optimal_aircraft_trajectories_20151218_0000_airtraf_ac.nc 12 ------------ Cost_optimal_aircraft_trajectories_20151218_0000_airtraf_ac.nc 2. Keywords: "aviation climate impact", "aircraft trajectory optimization", "contrails", "aircaft en-route emissions" 3. Date of data collection: 2 August 2022 4. Date of dataset publication: 1st May 2023 5. Funding: The current study has been supported by the previous ATM4E project and the current FlyATM4E project. Both projects have received funding from the SESAR Joint Undertaking under grant agreements No. 699395 (ATM4E) and No. 891317 (FlyATM4E) under European Union's Horizon 2020 research and innovation program. The computing resources to conduct simulations with the ECHAM/MESSy Atmospheric Chemistry (EMAC) model were provided by the TU Delft High Performance Cluster (HPC12). This work used resources of the Deutsches Klimarechenzentrum (DKRZ) granted by its Scientific Steering Committee (WLA) under project ID bd0781 and bd1062. ACCESS INFORMATION ------------------ 1. Creative Commons License of the dataset: CC BY-NC 4.0 2. Dataset DOI: 10.4121/bea8a3fe-e34c-4598-9f94-c5a5c63348e5 VERSIONING AND PROVENANCE ------------------------- 1. Last modification date: April 2023 2. Was data derived from another source? If yes, which source? The ECHAM/MESSy Atmospheric Chemistry (EMAC) model was employed to produce the data. METHODOLOGICAL INFORMATION -------------------------- 1. Description of data collection methods: The dataset results from: - simulation output preduced running the ECHAM/MESSy Atmospheric Chemistry (EMAC) model as described by Yin et al., 2022 (https://doi.org/10.5194/gmd-2022-220). - Annual_mean_*_2016.nc files result from post-processing of the model output. 2. Methods for processing the data: NCL scripts. 3. Instrument- or software- specific information (incl. software version) needed to interpret the data: The data is provided as netCDF files, so no specific tool is needed to interpret the data. FILE OVERVIEW ------------- 1. Explain the file naming convention, if applicable: Two file naming conventions are used: - For the model output, relative to midnight of December 18, 2015: {CONTENT DESCRIPTION}_20151218_0000_{MODEL NAME}.nc - For the files resulting from the model output post-processing: Annual_mean_{VARIABLE NAME}_2016.nc