CMIP6_CDFDM_JCS (C6CJ)
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High-resolution, bias-corrected climate simulation data, known as climate scenarios, are essential for climate change impact model simulations. This global land-area climate scenario dataset is derived from up to 38 climate models’ simulations under historical conditions and seven future emission scenarios of the Coupled Model Intercomparison Project Phase 6 (CMIP6). The dataset includes ten variables with daily temporal resolution and a spatial resolution of 0.5°. It supports analyses of uncertainties in impact assessments related to climate models and future emission scenarios.
Description
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Creator
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Release date
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2025/10/31
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Temporal coverage
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1850 - 2100
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Data provider
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NIES
Email: cgerdb_admin(at)nies.go.jp |
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DOI
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File format
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netCDF
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Data volume
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56TB
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Version
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ver.1 (Last updated: 2025/10/31)
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Language
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English
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Data Set
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Parameters
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(1) Daily data on downward longwave radiation at the surface (dlwrfsfc), downward shortwave radiation at the surface (dswrfsfc), precipitation (precsfc), surface pressure (pressfc), relative humidity at 2m (rh2m), specific humidity at 2m (spfh2m), daily mean temperature at 2m (tave2m), daily maximum temperature at 2m (tmax2m), daily minimum temperature at 2m (tmin2m), and wind speeds at 10m. The spatial resolution is 0.5° longitude × 0.5° latitude. The experiments include the historical period (1950-2014) and seven shared socioeconomic pathways (SSPs) (2015-2100, O’Neill et al. 2016): ssp119, ssp126, ssp245, ssp370, ssp434, ssp534-over, and ssp585. The number of available climate models varies depending on variables and experiments. Bias corrections were applied only for land areas. (2) The same as (1) but for monthly mean data. (3) Annual-mean global-averaged surface air temperature for all the climate models and experiments. No bias corrections were applied. (4) The land mask file. The land grids are indicated by “1”.
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Domain
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Global
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Keywords
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[Free keywords]
Climate Change, Climate Scenarios, Impact Assessments
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Update history
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[2025/10/31]
Dataset was released. Ver.1.
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Contributors
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Data Manager
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Project member
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Yuji Masutomi*1(
 orcid.org/0000-0003-0083-6337) , Toshichika Iizumi *2(orcid.org/0000-0002-0611-4637), Noriko N. Ishizaki*1 (orcid.org/0000-0002-8331-1175) *1 Center for Climate Change Adaptation, National Institute for Environmental Studies (NIES) *2 Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization |
Acknowledgements
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Acknowledgements
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This study was supported by the Environment Research and Technology Development Fund (JPMEERF20252002) of the Environmental Restoration and Conservation Agency and the Ministry of Environment of Japan, and by the “Project for the development of a barley yield prediction system under climate changes” of Asahi Quality & Innovations, Ltd. We thank Asahi Global Procurement Pte. Ltd., Asahi Breweries, Ltd., Asahi Group Japan, Ltd., and Asahi Group Holdings, Ltd. for their contributions to the project. The supercomputer of NIES was used for the data creation and analysis processes. We appreciate Naota Hanasaki and Kinuyo Tarumoto for distributing this dataset.
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Fund Information
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Funder
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独立行政法人環境再生保全機構（Environmental Restoration and Conservation Agency）
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Grant number
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JPMEERF20252002
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Terms and Conditions of Use*
*By accessing or using the Service you agree to be bound by these Terms. If you disagree with any part of the terms then you may not access the Service.
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License
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Citation format
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When this data set is referred to in publications, it should, as a general rule, be made in the following format.
Hideo Shiogama et al. (2025), CMIP6_CDFDM_JCS (C6CJ), ver. 1*1, NIES,
DOI:10.17595/20251031.001. (Reference date*2: YYYY/MM/DD) *1 The version number is indicated in the name of each data file. *2 As the reference date, please indicate the date you downloaded the files. |