Decadal climate variability and predictability: challenges and opportunities

Cassou, C., Kushnir, Y., Hawkins, E. ORCID: https://orcid.org/0000-0001-9477-3677, Pirani, A., Kucharski, F., Kang, I.-S. and Caltabiano, N. (2018) Decadal climate variability and predictability: challenges and opportunities. Bulletin of the American Meteorological Society, 99 (3). pp. 479-490. ISSN 1520-0477 doi: 10.1175/BAMS-D-16-0286.1

Abstract/Summary

The study of Decadal Climate Variability (DCV) and Predictability is the interdisciplinary endeavor to characterize, understand, attribute, simulate, and predict the slow, multi-year variations of climate at global (e.g. the recent slowdown of global mean temperature rise in the early 2000s) and regional scales (e.g. decadal modulation of hurricane activity in the Atlantic, ongoing drought in California or in the Sahel in the 1970s-1980s, etc.). This study remains very challenging in spite of decades of research, extensive progress in climate system modeling and improvements in the availability and coverage of a wide variety of observations. Considerable obstacles in applying this knowledge to actual predictions remain. This short article is a succint review paper about DCV and predictability. Based on listed issues and priorities, it also proposes a unifying theme referred to as “drivers of teleconnectivity” as a backbone to address and structure the core DCV research challenge. This framework goes beyond a preoccupation with changes in the global mean temperature and directly addresses the regional impacts of external (natural and anthropogenic) climate forcing and internal climate interactions; it thus explicitly deals with the societal needs for region-specific climate information. Such a framework also enables the integration of efforts in a large international research community towards advancing the observation, characterization, understanding and prediction of DCV. Recommendations to make progress are provided as part of the contribution of the CLIVAR “DCVP Research Focus” group.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/73146
Identification Number/DOI	10.1175/BAMS-D-16-0286.1
Refereed	No
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	American Meteorological Society
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