The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
Do seasonal‐to‐decadal climate predictions underestimate the predictability of the real world?
Open accessAbstract
Seasonal‐to‐decadal predictions are inevitably uncertain, depending on the size of the predictable signal relative to unpredictable chaos. Uncertainties can be accounted for using ensemble techniques, permitting quantitative probabilistic forecasts. In a perfect system, each ensemble member would represent a potential realization of the true evolution of the climate system, and the predictable components in models and reality would be equal. However, we show that the predictable component is sometimes lower in models than observations, especially for seasonal forecasts of the North Atlantic Oscillation and multiyear forecasts of North Atlantic temperature and pressure. In these cases the forecasts are underconfident, with each ensemble member containing too much noise. Consequently, most deterministic and probabilistic measures underestimate potential skill and idealized model experiments underestimate predictability. However, skilful and reliable predictions may be achieved using a large ensemble to reduce noise and adjusting the forecast variance through a postprocessing technique proposed here.
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Cites
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Cited by
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
Self-citationConsistency and discrepancy in the atmospheric response to Arctic sea-ice loss across climate models
Screen, J. A., Deser, C., Smith, D. M., Zhang, X., Blackport, R., Kushner, P. J., Oudar, T., McCusker, K. E., & Sun, L. (2018) · Nature Geoscience · doi:10.1038/s41561-018-0059-y · Cited by 382
Self-citationNonlinear response of mid-latitude weather to the changing Arctic
Overland, J. E., Dethloff, K., Francis, J. A., Hall, R. J., Hanna, E., Kim, S.-J., Screen, J. A., Shepherd, T. G., & Vihma, T. (2016) · Nature Climate Change · doi:10.1038/nclimate3121 · Cited by 371
Smith, D. M., Screen, J. A., Deser, C., Cohen, J., Fyfe, J. C., García-Serrano, J., Jung, T., Kattsov, V., Matei, D., Msadek, R., et al. (2019) · Geoscientific Model Development · doi:10.5194/gmd-12-1139-2019 · Cited by 357
Self-citationRobust skill of decadal climate predictions
Smith, D. M., Eade, R., Scaife, A. A., Caron, L.-P., Danabasoglu, G., DelSole, T. M., Delworth, T., Doblas-Reyes, F. J., Dunstone, N. J., Hermanson, L., et al. (2019) · npj Climate and Atmospheric Science · doi:10.1038/s41612-019-0071-y · Cited by 299
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Metadata
- Authors
- Eade, R., Smith, D., Scaife, A., Wallace, E., Dunstone, N., Hermanson, L., & Robinson, N.
- Venue
- Geophysical Research Letters
- Publisher
- American Geophysical Union (AGU)
- Published
- 2014-08-08
- Volume
- 41
- Issue
- 15
- Pages
- 5620-5628
- ISSN
- 0094-8276 (ISSN-L)
- 1944-8007
- OpenAlex
- W1835770454
- Cited by
- 383
- References
- 59
- FWCI
- 20.08
- Type
- journal article
- Language
- en
- Open access
- hybrid
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