Kushnir, Y., Scaife, A. A., Arritt, R., Balsamo, G., Boer, G., Doblas-Reyes, F., Hawkins, E.
ORCID: https://orcid.org/0000-0001-9477-3677, Kimoto, M., Kolli, R. K., Kumar, A., Matei, D., Matthes, K., Müller, W. A., O'Kane, T., Perlwitz, J., Power, S., Raphael, M., Shimpo, A., Smith, D., Tuma, M. and Wu, B.
(2019)
Towards operational predictions of the near-term climate.
Nature Climate Change, 9.
pp. 94-101.
ISSN 1758-6798
doi: 10.1038/s41558-018-0359-7
Abstract/Summary
Near-term climate predictions — which operate on annual to decadal timescales — offer benefits for climate adaptation and resilience, and are thus important for society. Although skilful near-term predictions are now possible, particularly when coupled models are initialized from the current climate state (most importantly from the ocean), several scientific challenges remain, including gaps in understanding and modelling the underlying physical mechanisms. This Perspective discusses how these challenges can be overcome, outlining concrete steps towards the provision of operational near-term climate predictions. Progress in this endeavour will bridge the gap between current seasonal forecasts and century-scale climate change projections, allowing a seamless climate service delivery chain to be established.
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| Item Type | Article |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/83631 |
| Identification Number/DOI | 10.1038/s41558-018-0359-7 |
| Refereed | Yes |
| Divisions | Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology |
| Publisher | Nature |
| Download/View statistics | View download statistics for this item |
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