Articles | Volume 14, issue 6
https://doi.org/10.5194/esd-14-1107-2023
© Author(s) 2023. 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-14-1107-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Nov 2023
Research article |
| 07 Nov 2023
| 07 Nov 2023
MIROC6 Large Ensemble (MIROC6-LE): experimental design and initial analyses
Earth System Division, National Institute for Environmental Studies, Tsukuba, 305-8506, Japan
Hiroaki Tatebe
Japan Agency for Marine-Earth Science and Technology, Yokohama, 236-0001, Japan
Michiya Hayashi
Earth System Division, National Institute for Environmental Studies, Tsukuba, 305-8506, Japan
Manabu Abe
Japan Agency for Marine-Earth Science and Technology, Yokohama, 236-0001, Japan
Miki Arai
Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, 277-8564, Japan
Hiroshi Koyama
Japan Agency for Marine-Earth Science and Technology, Yokohama, 236-0001, Japan
Yukiko Imada
Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, 277-8564, Japan
Yu Kosaka
Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, 153-8904, Japan
Tomoo Ogura
Earth System Division, National Institute for Environmental Studies, Tsukuba, 305-8506, Japan
Masahiro Watanabe
Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, 277-8564, Japan
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Latest update: 01 Nov 2024
Short summary
We produced one of the largest single model initial-condition ensembles thus far using the MIROC6 coupled atmosphere–ocean global climate model (MIROC6-LE). MIROC6-LE includes historical simulations, eight single forcing historical experiments, five future scenario experiments and three single forcing future experiments with 10- or 50-ensemble members. We describe the experimental design and show initial analyses. This dataset would be useful to a wide range of research communities.
We produced one of the largest single model initial-condition ensembles thus far using the...
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