Abstract
A high-resolution climate projections dataset is produced by statistically downscaling climate projections from the CMIP6 experiment. This global dataset is at a spatial resolution of 0.0375° × 0.0375° from 19 climate models over Senegal domain. It includes five essential surface daily variables: mean, minimum, and maximum air temperatures, precipitation, and terrestrial radiation. The dataset covers daily climate data for the historical period (1850–2014) and future projections (2015–2100) for three greenhouse gas emissions scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. The downscaling method used is the “Cumulative Distribution Function-transform”, which is utilized for bias correction and has been widely referenced in peer-reviewed literature. The data processing includes rigorous quality control of metadata following climate modelling community standards and outlier detection to ensure data integrity.
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Data availability
The high-resolution downscaled CMIP6 climate projections dataset generated and analysed in this study is openly available at the official data repository of the Institut Pierre-Simon Laplace (IPSL). The dataset can be accessed through the following https://doi.org/10.14768/5c360e73-3337-48e6-8eaa-2295203d86c3. This repository ensures long-term preservation, reliable hosting, and user-friendly access to all bias-corrected and downscaled CMIP6 climate data for Senegal.
Code availability
All bias correction and downscaling procedures in this study were performed using the open-source Python package XSBCK (a command line interface to SBCK, specifically designed for large-scale bias correction). XSBCK provides implementations of state-of-the-art methods such as the Cumulative Distribution Function-transform (CDF-t) used in this work. The package is freely available on GitHub at https://github.com/yrobink/XSBCK and can be installed directly from PyPI (pip install XSBCK). Detailed documentation and usage instructions are provided within the repository. Users are encouraged to cite the following references when using XSBCK or SBCK in their work:
• SBCK: https://doi.org/10.5281/zenodo.7985160
• XSBCK: https://doi.org/10.5281/zenodo.7985173
XSBCK is distributed under the terms of the GNU General Public License v3.
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Acknowledgements
The activities described in this article were funded as part of my thesis by the Water Cycle and Climate Change (CECC) project. We also thank the IRD and the administration of the ESPACE-DEV Laboratory for all the logistics to carry out this work. This is an opportunity to thank the National Agency for Civil Aviation and Meteorology of Senegal (ANACIM) for allowing us to carry out this research and especially for making the field data available. To process the data, this study benefited from the ESPRI installation of the IPSL mesocenter, which is supported by the CNRS, the SU and the École Polytechnique. We also thank the Pierre Simon Laplace Institute for its help in welcoming us for a stay in 2023 to get to grips with the bias correction tools, particularly at Redouane Lguensat. This work contributes to the outcomes of the PEPR TRACCS PC3 DEMOCLIMA (project ANR-22-EXTR-0004).
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A. Mbengue: Conceptualization, Methodology, Data curation, Investigation and Data Analysis, Writing- Original draft preparation. R. Lguensat: Software. B. Sultan: Supervision. B. Sultan, R. Lguensat, M. Vrac, A. Diongue-Niang, O. Ndiaye, A.T. Gaye: Writing- Reviewing and Editing.
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Mbengue, A., Sultan, B., Lguensat, R. et al. High-Resolution Downscaled CMIP6 Projections dataset of Key Climate Variables for Senegal. Sci Data (2026). https://doi.org/10.1038/s41597-026-07059-9
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DOI: https://doi.org/10.1038/s41597-026-07059-9
