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.; Fiore, A.; Frankignoul, C.; Fyfe, J. C.; Horton, D. E.; Kay, J. E.; Knutti, R.; Lovenduski, N. S.; Marotzke, J.; McKinnon, K. A.; Minobe, S.; Randerson, J.; Screen, J. A.; Simpson, I. R.; Ting, M.

doi:10.1038/s41558-020-0731-2

i

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

2020
By Deser, C. ; Lehner, F. ; Rodgers, K. B. ; ...

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Journal Title:

Nature Climate Change
Personal Author:

Deser, C. ; Lehner, F. ; Rodgers, K. B. ; Ault, T. ; Delworth, T. L. ; DiNezio, P. N. ; Fiore, A. ; Frankignoul, C. ; Fyfe, J. C. ; Horton, D. E. ; Kay, J. E. ; Knutti, R. ; Lovenduski, N. S. ; Marotzke, J. ; McKinnon, K. A. ; Minobe, S. ; Randerson, J. ; Screen, J. A. ; Simpson, I. R. ; Ting, M.
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; GFDL (Geophysical Fluid Dynamics Laboratory) ; CIRES (Cooperative Institute for Research in Environmental Sciences)
Description:

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.
Source:

Nature Climate Change, 10(4), 277-286
DOI:

https://doi.org/10.1038/s41558-020-0731-2
ISSN:

1758-678X ; 1758-6798
Format:

PDF
Publisher:

Springer Science and Business Media LLC
Document Type:

Journal Article
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Accepted Manuscript
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Submitted
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https://repository.library.noaa.gov/view/noaa/66074/noaa_66074_DS1.pdf
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