Articles | Volume 9, issue 6
https://doi.org/10.5194/gmd-9-2279-2016
https://doi.org/10.5194/gmd-9-2279-2016
Development and technical paper
 | 
01 Jul 2016
Development and technical paper |  | 01 Jul 2016

Improved forecasting of thermospheric densities using multi-model ensembles

Sean Elvidge, Humberto C. Godinez, and Matthew J. Angling

Viewed

Total article views: 3,089 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,805 1,159 125 3,089 150 157
  • HTML: 1,805
  • PDF: 1,159
  • XML: 125
  • Total: 3,089
  • BibTeX: 150
  • EndNote: 157
Views and downloads (calculated since 19 Jan 2016)
Cumulative views and downloads (calculated since 19 Jan 2016)

Cited

Latest update: 14 Apr 2024
Download
Short summary
This paper presents the first known application of multi-model ensembles to the forecasting of the thermosphere. A multi-model ensemble (MME) is a method for combining different, independent models. The main advantage of using an MME is to reduce the effect of model errors and bias, since it is expected that the model errors will, at least partly, cancel. This paper shows that use of MMEs for forecasting thermospheric densities can reduce errors by 60 %.