Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-3013-2023
https://doi.org/10.5194/gmd-16-3013-2023
Development and technical paper
 | 
31 May 2023
Development and technical paper |  | 31 May 2023

Data-driven aeolian dust emission scheme for climate modelling evaluated with EMAC 2.55.2

Klaus Klingmüller and Jos Lelieveld

Viewed

Total article views: 1,912 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,420 439 53 1,912 46 37
  • HTML: 1,420
  • PDF: 439
  • XML: 53
  • Total: 1,912
  • BibTeX: 46
  • EndNote: 37
Views and downloads (calculated since 29 Sep 2022)
Cumulative views and downloads (calculated since 29 Sep 2022)

Viewed (geographical distribution)

Total article views: 1,912 (including HTML, PDF, and XML) Thereof 1,829 with geography defined and 83 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Jul 2024
Download
Short summary
Desert dust has significant impacts on climate, public health, infrastructure and ecosystems. An impact assessment requires numerical predictions, which are challenging because the dust emissions are not well known. We present a novel approach using satellite observations and machine learning to more accurately estimate the emissions and to improve the model simulations.