Recent applications and potential of near-term (interannual to decadal) climate predictions

O'Kane, T. J., Scaife, A. A., Kushnir, Y., Brookshaw, A., Buontempo, C., Carlin, D., Connell, R. K., Doblas-Reyes, F., Dunstone, N., Förster, K., Graça, A., Hobday, A. J., Kitsios, V., van der Laan, L., Lockwood, J., Merryfield, W. J., Paxian, A., Payne, M. R., Reader, M. C., Saville, G. R., Smith, D., Solaraju-Murali, B., Caltabiano, N., Carman, J., Hawkins, E. ORCID: https://orcid.org/0000-0001-9477-3677, Keenlyside, N., Kumar, A., Matei, D., Pohlmann, H., Power, S., Raphael, M., Sparrow, M. and Wu, B. (2023) Recent applications and potential of near-term (interannual to decadal) climate predictions. Frontiers in Climate, 5. ISSN 2624-9553 doi: 10.3389/fclim.2023.1121626

Abstract/Summary

Following efforts from leading centres for climate forecasting, sustained routine operational near-term climate predictions (NTCP) are now produced that bridge the gap between seasonal forecasts and climate change projections offering the prospect of seamless climate services. Though NTCP is a new area of climate science and active research is taking place to increase understanding of the processes and mechanisms required to produce skillful predictions, this significant technical achievement combines advances in initialisation with ensemble prediction of future climate up to a decade ahead. With a growing NTCP database, the predictability of the evolving externally-forced and internally-generated components of the climate system can now be quantified. Decision-makers in key sectors of the economy can now begin to assess the utility of these products for informing climate risk and for planning adaptation and resilience strategies up to a decade into the future. Here, case studies are presented from finance and economics, water management, agriculture and fisheries management demonstrating the emerging utility and potential of operational NTCP to inform strategic planning across a broad range of applications in key sectors of the global economy.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/112369
Identification Number/DOI	10.3389/fclim.2023.1121626
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Frontiers
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