Articles | Volume 9, issue 1
https://doi.org/10.5194/esd-9-313-2018
https://doi.org/10.5194/esd-9-313-2018
Research article
 | 
28 Mar 2018
Research article |  | 28 Mar 2018

A bias-corrected CMIP5 dataset for Africa using the CDF-t method – a contribution to agricultural impact studies

Adjoua Moise Famien, Serge Janicot, Abe Delfin Ochou, Mathieu Vrac, Dimitri Defrance, Benjamin Sultan, and Thomas Noël

Viewed

Total article views: 5,108 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,617 1,356 135 5,108 457 131 108
  • HTML: 3,617
  • PDF: 1,356
  • XML: 135
  • Total: 5,108
  • Supplement: 457
  • BibTeX: 131
  • EndNote: 108
Views and downloads (calculated since 04 Dec 2017)
Cumulative views and downloads (calculated since 04 Dec 2017)

Viewed (geographical distribution)

Total article views: 5,108 (including HTML, PDF, and XML) Thereof 4,853 with geography defined and 255 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 29 Jun 2024
Download
Short summary
This study uses the cumulative distribution function transform (CDF-t) method to provide bias-corrected data over Africa using WFDEI as a reference dataset. It is shown that CDF-t is very effective in removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets, particularly for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields.
Altmetrics
Final-revised paper
Preprint