Long-range prediction and the stratosphere

Adam A. Scaife*, Mark P. Baldwin, Amy H. Butler, Andrew J. Charlton-Perez, Daniela I.V. Domeisen, Chaim I. Garfinkel, Steven C. Hardiman, Peter Haynes, Alexey Yu Karpechko, Eun Pa Lim, Shunsuke Noguchi, Judith Perlwitz, Lorenzo Polvani, Jadwiga H. Richter, John Scinocca, Michael Sigmond, Theodore G. Shepherd, Seok Woo Son, David W.J. Thompson

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

27 Scopus citations


Over recent years there have been concomitant advances in the development of stratosphere-resolving numerical models, our understanding of stratosphere-troposphere interaction, and the extension of long-range forecasts to explicitly include the stratosphere. These advances are now allowing for new and improved capability in long-range prediction. We present an overview of this development and show how the inclusion of the stratosphere in forecast systems aids monthly, seasonal, and annual-to-decadal climate predictions and multidecadal projections. We end with an outlook towards the future and identify areas of improvement that could further benefit these rapidly evolving predictions.

Original languageAmerican English
Pages (from-to)2601-2623
Number of pages23
JournalAtmospheric Chemistry and Physics
Issue number4
StatePublished - 25 Feb 2022

Bibliographical note

Funding Information:
Financial support. Adam A. Scaife and Steven C. Hardiman were supported by the Met Office Hadley Centre Climate Programme funded by BEIS (Department for Business, Energy & Industrial Strategy) and Defra (Department for Environment, Food & Rural Affairs). Mark P. Baldwin was supported by the Natural Environment Research Council (grant no. NE/M006123/1). Jadwiga H. Richter was supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling programme of the U.S. Department of Energy’s Office of Biological and Environmental Research (BER) via the National Science Foundation (NSF; interagency agreement no. 1844590). Shunsuke Noguchi was supported by the Japan Society for the Promotion of Science (KAKENHI; grant no. 19K14798). Eun-Pa Lim was supported by the Australian government’s National Environmental Science Program phase 2 and the Victorian Water and Climate Initiative phase 2. Seok-Woo Son was supported by the National Research Foundation of Korea (NRF), funded by the government of the Republic of Korea (Ministry of Science and ICT; grant no. 2017R1E1A1A01074889). David W. J. Thompson is supported by the US National Science Foundation Climate and Large-Scale Dynamics programme. Daniella I. V. Domeisen is supported by the Swiss National Science Foundation (project nos. PP00P2_170523 and PP00P2_198896). Chaim I. Garfinkel was supported by a European Research Council starting grant under the European Union Horizon 2020 research and innovation programme (agreement no. 677756).

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