Towards operational predictions of the near-term climate
| Autor: | Raymond W. Arritt, George J. Boer, Akihiko Shimpo, Gianpaolo Balsamo, Scott B. Power, Terence J. O’Kane, Rupa Kumar Kolli, Masahide Kimoto, Adam A. Scaife, Matthias Tuma, Katja Matthes, Wolfgang A. Müller, Francisco J. Doblas-Reyes, Judith Perlwitz, Yochanan Kushnir, Bo Wu, Daniela Matei, Ed Hawkins, Marilyn N. Raphael, Doug Smith, Arun Kumar |
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| Rok vydání: | 2019 |
| Předmět: |
0303 health sciences
010504 meteorology & atmospheric sciences Service delivery framework business.industry Environmental resource management Climate change Environmental Science (miscellaneous) 01 natural sciences Term (time) 03 medical and health sciences 13. Climate action Environmental science Climate state Predictability Adaptation (computer science) business Resilience (network) Social Sciences (miscellaneous) 030304 developmental biology 0105 earth and related environmental sciences |
| Zdroj: | Nature Climate Change Nature Climate Change, 9 . pp. 94-101. |
| ISSN: | 1758-678X |
| DOI: | 10.1038/s41558-018-0359-7 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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