Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 15, issue 15
Articles | Volume 15, issue 15
https://doi.org/10.5194/gmd-15-6197-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-6197-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 15
Development and technical paper
 | 
11 Aug 2022
Development and technical paper |  | 11 Aug 2022

Hybrid ensemble-variational data assimilation in ABC-DA within a tropical framework

Joshua Chun Kwang Lee, Javier Amezcua, and Ross Noel Bannister

Viewed

Total article views: 2,430 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,781 581 68 2,430 59 61
  • HTML: 1,781
  • PDF: 581
  • XML: 68
  • Total: 2,430
  • BibTeX: 59
  • EndNote: 61
Views and downloads (calculated since 18 Mar 2022)
Cumulative views and downloads (calculated since 18 Mar 2022)

Viewed (geographical distribution)

Total article views: 2,430 (including HTML, PDF, and XML) Thereof 2,263 with geography defined and 167 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Apr 2025
Download
Short summary
In this article, we implement a novel data assimilation method for the ABC–DA system which combines traditional data assimilation approaches in a hybrid approach. We document the technical development and test the hybrid approach in idealised experiments within a tropical framework of the ABC–DA system. Our findings indicate that the hybrid approach outperforms individual traditional approaches. Its potential benefits have been highlighted and should be explored further within this framework.
Read more
Share