Abstract
Farmers face increasing challenges in maintaining stable crop production as climate change alters growing conditions through higher temperatures, variable rainfall, and extreme weather events. To adapt, farmers often select new crop varieties and adjust planting dates before changing crops, as these strategies involve lower costs and risks. To support assessments of future crop production under climate change, we developed a global gridded dataset that provides simulated yields and consumptive water use for multiple crop varieties and sowing dates for maize, soybean, winter wheat, spring wheat, and rice. The dataset is based on simulations with the WOrld FOod STudies crop growth model under five global climate models and three greenhouse gas concentration scenarios, at a spatial resolution of 0.5 by 0.5 degrees (~55 km at the equator), covering the years 1961 to 2100. It can help identify suitable crop varieties and planting dates that sustain yields and optimize water use. This dataset is intended for use in crop modelling, climate impact assessments, and agricultural adaptation planning.
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Data availability
The global dataset used in this study is available for 64,055 (excluding Greenland) grid cells at a 0.5 × 0.5-degree spatial resolution for each of the six crops (maize, soybean, winter wheat, spring wheat, rice1, and rice2) over the 1961–2100 period. The data are provided in a TXT format and can be accessed via the landing page: https://public.yoda.uu.nl/geo/UU01/8V0A4N.html or through the https://doi.org/10.24416/UU01-WUCN2F33. A detailed description of the dataset, including structure, variables and usage guidelines, is also available at the DOI link.
All external datasets used as inputs to generate the results of this study are publicly accessible and were obtained from established repositories or official institutional sources. Climate forcing data were sourced from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) database and are available via the https://doi.org/10.48364/ISIMIP.842396.1. Crop calendar information was obtained from the AgMIP-GGCMI crop calendars repository https://doi.org/10.5281/zenodo.5062513. Crop cultivar parameters were sourced from the WOFOST crop parameter repository https://github.com/ajwdewit/WOFOST_crop_parameters. Soil properties were derived from the FAO Digital Soil Map of the World (DSMW), available through the Food and Agriculture Organization of the United Nations https://www.fao.org/land-water/land/land-governance/land-resources-planning-toolbox/category/details/en/c/1026564/.
All external datasets are openly available for research use. Reuse, redistribution, and potential commercial use are subject to the specific licensing terms of each data provider, and users are advised to consult the original repositories for detailed license conditions and attribution requirements.
Code availability
An Python executable scripts used to process the data, test, and validate yield outputs, and filter the dataset using crop specific masks (e.g., restricting analyses to currently cultivated areas or regions of interest based on latitude and longitude selection) are available in the GitHub repository https://github.com/SnehaChevuru/Climate_Responsive_Crop_Selection_Global_Dataset.
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Acknowledgements
This research has been funded by the European Union Horizon Programme GoNexus project (Grant Agreement Number 101003722). MTHvV was financially supported by the Netherlands Scientific Organisation (NWO) by a VIDI grant (VI.Vidi.193.019) and the European Research Council (ERC) under the European Union’s Horizon Europe research and innovation program (grant agreement 101039426 B-WEX). We acknowledge the NWO for the grant that enabled us to use the national supercomputer Snellius (project no. EINF-11826).
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The research was designed by S.C., L.P.H.v.B., M.T.H.v.V. and M.F.P.B. The computational work, dataset development and result visualization were performed by S.C. under the supervision of L.P.H.v.B., M.T.H.v.V. and M.F.P.B. S.C. wrote the original draft manuscript, and all co-authors reviewed and edited the manuscript.
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Chevuru, S., van Beek, R.L.P.H., van Vliet, M.T.H. et al. Global Gridded Climate-Responsive Crop Selection: Sowing Dates and Crop Varieties in a Warming World. Sci Data (2026). https://doi.org/10.1038/s41597-026-07164-9
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DOI: https://doi.org/10.1038/s41597-026-07164-9
