Articles | Volume 18, issue 7
https://doi.org/10.5194/essd-18-5463-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-5463-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
27 Jul 2026
Data description article |
| 27 Jul 2026
| 27 Jul 2026
Climate Modes evaluation datasets from CMIP6 pre-industrial control simulations and observations
Sandeep Mohapatra
CORRESPONDING AUTHOR
Australian Centre for Excellence in Antarctic Science, University of Tasmania, Hobart, Australia
Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Australia
Alex Sen Gupta
Australian Centre for Excellence in Antarctic Science, University of Tasmania, Hobart, Australia
Climate Change Research Centre, University of New South Wales, Sydney, Australia
Nathaniel L. Bindoff
Australian Centre for Excellence in Antarctic Science, University of Tasmania, Hobart, Australia
Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Australia
Australian Antarctic Program Partnership, University of Tasmania, Hobart, Australia
Yuxuan Lyu
Australian Centre for Excellence in Antarctic Science, University of Tasmania, Hobart, Australia
Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Australia
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Benoît Pasquier, Mark Holzer, Matthew A. Chamberlain, Richard J. Matear, Nathaniel L. Bindoff, and François W. Primeau
Biogeosciences, 20, 2985–3009, https://doi.org/10.5194/bg-20-2985-2023, https://doi.org/10.5194/bg-20-2985-2023, 2023
Short summary
Short summary
Modeling the ocean's carbon and oxygen cycles accurately is challenging. Parameter optimization improves the fit to observed tracers but can introduce artifacts in the biological pump. Organic-matter production and subsurface remineralization rates adjust to compensate for circulation biases, changing the pathways and timescales with which nutrients return to the surface. Circulation biases can thus strongly alter the system’s response to ecological change, even when parameters are optimized.
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Short summary
This study provides a new open-access datasets that capture how natural climate patterns shape the global climate. The datasets are built from climate model simulations and observations, allowing researcher to see how well models reproduce natural climate behaviour. Our openly available datasets will help researchers to better distinguish natural climate variability from human-caused changes. These resources also provide a foundation for improving climate models and long-term projections.
This study provides a new open-access datasets that capture how natural climate patterns shape...
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