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

Research output: Contribution to journalReview articlepeer-review

10 Citations (Scopus)

Abstract

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 languageEnglish
Pages (from-to)2601-2623
Number of pages23
JournalAtmospheric Chemistry and Physics
Volume22
Issue number4
DOIs
Publication statusPublished - Feb 25 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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