Supplementary Data of "Transport Patterns of Global Aviation NOx and their Short-term O3 Radiative Forcing – A Machine Learning Approach"

doi: 10.4121/16886977.v1
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: 10.4121/16886977
Datacite citation style:
Maruhashi, Jin; Grewe, Volker; Frömming, Christine; Jöckel, Patrick; Irene C Dedoussi (2022): Supplementary Data of "Transport Patterns of Global Aviation NOx and their Short-term O3 Radiative Forcing – A Machine Learning Approach". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/16886977.v1
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Supplementary data accompanying the article "Transport Patterns of Global Aviation NOx and their Short-term O3 Radiative Forcing – A Machine Learning Approach". 


This data tracks the global transport of emitted NOx throughout a 90-day period since its emission from a representative aircraft cruising altitude of 250 hPa (~10.4 km) in 5 regions (North America, South America, Eurasia, Africa and Australasia) during the first day of January and July of 2014.


The short-term NOx-induced net O3 production is also calculated as well as its associated instantaneous radiative forcing impact. The Lagrangian modelling approach adopted in this study allows for the amount of NOx emitted and consequent O3 produced to be accompanied along each point of every air parcel trajectory. Lastly, information regarding the background NOx conditions during the times of emission is also included. 

history
  • 2022-12-09 first online, published, posted
publisher
4TU.ResearchData
format
netCDF (.nc)
funding
  • Advancing the Science for Aviation and ClimAte (grant code 875036) [more info...] European Commission
organizations
TU Delft, Faculty of Aerospace Engineering, Section Aircraft Noise and Climate Effects

Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre

DATA

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