Articles | Volume 9, issue 1
https://doi.org/10.5194/esd-9-313-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-9-313-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A bias-corrected CMIP5 dataset for Africa using the CDF-t method – a contribution to agricultural impact studies
Adjoua Moise Famien
Université Félix Houphouët Boigny, LAPAMF-UFR SSMT, 22 BP 582, Abidjan 22, Côte d'Ivoire
Sorbonne Université, IRD, CNRS, MNHN, Laboratoire d'Océanographie et du Climat: Expérimentations et Approches Numériques, LOCEAN, 75005 Paris, France
Serge Janicot
CORRESPONDING AUTHOR
Sorbonne Université, IRD, CNRS, MNHN, Laboratoire d'Océanographie et du Climat: Expérimentations et Approches Numériques, LOCEAN, 75005 Paris, France
Abe Delfin Ochou
Université Félix Houphouët Boigny, LAPAMF-UFR SSMT, 22 BP 582, Abidjan 22, Côte d'Ivoire
Mathieu Vrac
LSCE-IPSL, CNRS/CEA/UVSQ, Centre d'Études de Saclay, Orme des Merisiers, Gif-sur-Yvette, France
Dimitri Defrance
Sorbonne Université, IRD, CNRS, MNHN, Laboratoire d'Océanographie et du Climat: Expérimentations et Approches Numériques, LOCEAN, 75005 Paris, France
ESPACE-DEV, Université Montpellier, IRD, Université Guyane, Université Réunion, Université Antilles, Université Avignon, Montpellier, France
Benjamin Sultan
Sorbonne Université, IRD, CNRS, MNHN, Laboratoire d'Océanographie et du Climat: Expérimentations et Approches Numériques, LOCEAN, 75005 Paris, France
ESPACE-DEV, Université Montpellier, IRD, Université Guyane, Université Réunion, Université Antilles, Université Avignon, Montpellier, France
Thomas Noël
Climate Data Factory, Paris, France
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- A support vector machine-based method for improving real-time hourly precipitation forecast in Japan G. Yin et al.
- A Hybrid Statistical-Dynamical Downscaling of Air Temperature over Scandinavia Using the WRF Model J. Wang et al.
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Saved (final revised paper)
Latest update: 25 Apr 2026
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.
This study uses the cumulative distribution function transform (CDF-t) method to provide...
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