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Earth System Dynamics An interactive open-access journal of the European Geosciences Union

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© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
04 Dec 2017
Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Earth System Dynamics (ESD) and is expected to appear here in due course.
A bias-corrected CMIP5 dataset for Africa using CDF-t method. A contribution to agricultural impact studies
Adjoua Moise Famien1,2, Serge Janicot2, Abe Delfin Ochou1, Mathieu Vrac3, Dimitri Defrance2, Benjamin Sultan2, and Thomas Noël4 1Université Félix Houphouët Boigny, LAPAMF-UFR SSMT, 22 BP 582, Abidjan 22, Ivory Coast
2UMR 7159 LOCEAN, Sorbonne Universités UPMC-CNRS-IRD-MNHN, Paris, France
3LSCE-IPSL, CNRS/CEA/UVSQ, Centre d’Études de Saclay, Orme des Merisiers, Gif-sur-Yvette, France
4Climate Data Factory, Paris, France
Abstract. The objective of this paper is to present a new data set of bias-corrected CMIP5 global climate models (GCMs) daily data over Africa. This dataset was obtained in using the Cumulative Distribution Function Transform (CDF-t) method, a method that has been applied on several regions and contexts but never on Africa. Here CDF-t is used over the period 1950–2099 combining historical runs and climate change scenarios on 6 variables, precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface down-welling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. Evaluation of the results is carried out over West Africa on a list of priority users-based metrics that was discussed and selected with stakeholders and on simulated yield using a crop model simulating maize growth. Bias-corrected GCMs data are compared with another available dataset of bias-corrected GCMs, and the impact of three different reference datasets on bias-corrections is also examined in details. CDF-t is very effective in removing the biases and in reducing the high inter-GCMs scattering. Differences with other bias-corrected GCMs data are mainly due to the differences between the reference datasets. This is particular true for surface down-welling shortwave radiation, which has impacts in terms of simulated maize yields. Projections of future yields over West Africa have quite different levels, depending on bias-correction method used, but they all show a similar relative decreasing trend over the 21st century.
Citation: Famien, A. M., Janicot, S., Ochou, A. D., Vrac, M., Defrance, D., Sultan, B., and Noël, T.: A bias-corrected CMIP5 dataset for Africa using CDF-t method. A contribution to agricultural impact studies, Earth Syst. Dynam. Discuss.,, in review, 2017.
Adjoua Moise Famien et al.
Adjoua Moise Famien et al.


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