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  Insights from Earth system model initial-condition large ensembles and future prospects

Deser, C., Lehner, F., Rodgers, K. B., Ault, T., Delworth, T. L., DiNezio, P. N., et al. (2020). Insights from Earth system model initial-condition large ensembles and future prospects. Nature Climate Change, 10, 277-286. doi:10.1038/s41558-020-0731-2.

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 Creators:
Deser, C.1, 2, Author
Lehner, F.1, 2, Author
Rodgers, K. B.1, 2, Author
Ault, T.1, 2, Author
Delworth, T. L.1, 2, Author
DiNezio, P. N.1, 2, Author
Fiore, A.1, 2, Author
Frankignoul, C.1, 2, Author
Fyfe, J. C.1, 2, Author
Horton, D. E.1, 2, Author
Kay, J. E.1, 2, Author
Knutti, R.1, 2, Author
Lovenduski, N. S.1, 2, Author
Marotzke, Jochem2, 3, Author           
McKinnon, K. A.1, 2, Author
Minobe, S.1, 2, Author
Randerson, J.1, 2, Author
Screen, J. A.1, 2, Author
Simpson, I. R.1, 2, Author
Ting, M.1, 2, Author
(US CLIVAR Working Group on Large Ensembles), Author               more..
Affiliations:
1external, ou_persistent22              
2US CLIVAR Working Group on Large Ensembles, Washington, DC, ou_persistent22              
3Director’s Research Group OES, The Ocean in the Earth System, MPI for Meteorology, Max Planck Society, ou_913553              

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 Abstract: Internal variability in the climate system confounds assessment of human-induced climate change and imposes irreducible limits on the accuracy of climate change projections, especially at regional and decadal scales. A new collection of initial-condition large ensembles (LEs) generated with seven Earth system models under historical and future radiative forcing scenarios provides new insights into uncertainties due to internal variability versus model differences. These data enhance the assessment of climate change risks, including extreme events, and offer a powerful testbed for new methodologies aimed at separating forced signals from internal variability in the observational record. Opportunities and challenges confronting the design and dissemination of future LEs, including increased spatial resolution and model complexity alongside emerging Earth system applications, are discussed.

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Language(s): eng - English
 Dates: 2020-02-122020-03-302020-04-01
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41558-020-0731-2
Other: Deser2020
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Title: Nature Climate Change
Source Genre: Journal
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Pages: - Volume / Issue: 10 Sequence Number: - Start / End Page: 277 - 286 Identifier: ISBN: 1758-6798