Articles | Volume 9, issue 10
https://doi.org/10.5194/gmd-9-3751-2016
https://doi.org/10.5194/gmd-9-3751-2016
Model experiment description paper
 | 
25 Oct 2016
Model experiment description paper |  | 25 Oct 2016

The Decadal Climate Prediction Project (DCPP) contribution to CMIP6

George J. Boer, Douglas M. Smith, Christophe Cassou, Francisco Doblas-Reyes, Gokhan Danabasoglu, Ben Kirtman, Yochanan Kushnir, Masahide Kimoto, Gerald A. Meehl, Rym Msadek, Wolfgang A. Mueller, Karl E. Taylor, Francis Zwiers, Michel Rixen, Yohan Ruprich-Robert, and Rosie Eade

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Cited articles

Asrar, R. A. and Hurrell, J. W. (Eds.): Climate Science for Serving Society, Springer, Dordrecht, 484 pp., https://doi.org/10.1007/978-94-007-6692-1, 2013.
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical weather prediction, Nature, 525, 47–55, https://doi.org/10.1038/nature14956, 2015.
Boer, G. J., Kharin, V. V., and Merryfield, W. J.: Decadal predictability and forecast skill, Clim. Dynam., 41, 1817, https://doi.org/10.1007/s00382-013-1705-0, 2013.
Caron, L.-P., Hermanson, L., and Doblas-Reyes, F. J.: Multi-annual forecasts of Atlantic U.S. tropical cyclone wind damage potential, Geophys. Res. Lett., 42, 2417–2425, https://doi.org/10.1002/2015GL063303, 2015.
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The Decadal Climate Prediction Project (DCPP) investigates our ability to skilfully predict climate variations from a year to a decade ahead by means of a series of retrospective forecasts. Quasi-real-time forecasts are also produced for potential users. In addition, the DCPP investigates how perturbations such as volcanoes affect forecasts and, more broadly, what new information can be learned about the mechanisms governing climate variations by means of case studies of past climate behaviour.