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Two Limits of Initial-Value Decadal Predictability in a CGCM
Abstract
When the climate system experiences time-dependent external forcing (e.g., from increases in greenhouse gas and aerosol concentrations), there are two inherent limits on the gain in skill of decadal climate predictions that can be attained from initializing with the observed ocean state. One is the classical initial-value predictability limit that is a consequence of the system being chaotic, and the other corresponds to the forecast range at which information from the initial conditions is overcome by the forced response. These limits are not caused by model errors; they correspond to limits on the range of useful forecasts that would exist even if nature behaved exactly as the model behaves. In this paper these two limits are quantified for the Community Climate System Model, version 3 (CCSM3), with several 40-member climate change scenario experiments. Predictability of the upper-300-m ocean temperature, on basin and global scales, is estimated by relative entropy from information theory. Despite some regional variations, overall, information from the ocean initial conditions exceeds that from the forced response for about 7 yr. After about a decade the classical initial-value predictability limit is reached, at which point the initial conditions have no remaining impact. Initial-value predictability receives a larger contribution from ensemble mean signals than from the distribution about the mean. Based on the two quantified limits, the conclusion is drawn that, to the extent that predictive skill relies solely on upper-ocean heat content, in CCSM3 decadal prediction beyond a range of about 10 yr is a boundary condition problem rather than an initial-value problem. Factors that the results of this study are sensitive and insensitive to are also discussed.
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A signal-to-noise paradox in climate science
Scaife, A. A., & Smith, D. (2018) · npj Climate and Atmospheric Science · doi:10.1038/s41612-018-0038-4 · Cited by 411
Metadata
- Authors
- Branstator, G., & Teng, H.
- Venue
- Journal of Climate
- Publisher
- American Meteorological Society
- Published
- 2010-12-01
- Volume
- 23
- Issue
- 23
- Pages
- 6292-6311
- ISSN
- 0894-8755 (ISSN-L)
- 1520-0442
- OpenAlex
- W2031685624
- Cited by
- 159
- References
- 0
- FWCI
- 14.86
- Type
- journal article
- Language
- en
- Open access
- closed
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