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

doi:https://doi.org/10.5194/acp-22-2601-2022

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

Fredy & Nadine Herrmann Institute of Earth Sciences

The Hebrew University of Jerusalem

Research output: Contribution to journal › Review article › peer-review

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 language	English
Pages (from-to)	2601-2623
Number of pages	23
Journal	Atmospheric Chemistry and Physics
Volume	22
Issue number	4
DOIs	https://doi.org/10.5194/acp-22-2601-2022
State	Published - 25 Feb 2022

All Science Journal Classification (ASJC) codes

Atmospheric Science

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https://doi.org/10.5194/acp-22-2601-2022

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Scaife, A. A., Baldwin, M. P., Butler, A. H., Charlton-Perez, A. J., Domeisen, D. I. V., Garfinkel, C. I., Hardiman, S. C., Haynes, P., Karpechko, A. Y., Lim, E. P., Noguchi, S., Perlwitz, J., Polvani, L., Richter, J. H., Scinocca, J., Sigmond, M., Shepherd, T. G., Son, S. W., & Thompson, D. W. J. (2022). Long-range prediction and the stratosphere. Atmospheric Chemistry and Physics, 22(4), 2601-2623. https://doi.org/10.5194/acp-22-2601-2022

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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.",

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

year = "2022",

month = feb,

day = "25",

doi = "https://doi.org/10.5194/acp-22-2601-2022",

language = "الإنجليزيّة",

volume = "22",

pages = "2601--2623",

journal = "Atmospheric Chemistry and Physics",

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Scaife, AA, Baldwin, MP, Butler, AH, Charlton-Perez, AJ, Domeisen, DIV, Garfinkel, CI, Hardiman, SC, Haynes, P, Karpechko, AY, Lim, EP, Noguchi, S, Perlwitz, J, Polvani, L, Richter, JH, Scinocca, J, Sigmond, M, Shepherd, TG, Son, SW & Thompson, DWJ 2022, 'Long-range prediction and the stratosphere', Atmospheric Chemistry and Physics, vol. 22, no. 4, pp. 2601-2623. https://doi.org/10.5194/acp-22-2601-2022

TY - JOUR

T1 - Long-range prediction and the stratosphere

AU - Scaife, Adam A.

AU - Baldwin, Mark P.

AU - Butler, Amy H.

AU - Charlton-Perez, Andrew J.

AU - Domeisen, Daniela I.V.

AU - Garfinkel, Chaim I.

AU - Hardiman, Steven C.

AU - Haynes, Peter

AU - Karpechko, Alexey Yu

AU - Lim, Eun Pa

AU - Noguchi, Shunsuke

AU - Perlwitz, Judith

AU - Polvani, Lorenzo

AU - Richter, Jadwiga H.

AU - Scinocca, John

AU - Sigmond, Michael

AU - Shepherd, Theodore G.

AU - Son, Seok Woo

AU - Thompson, David W.J.

PY - 2022/2/25

Y1 - 2022/2/25

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85125848370&partnerID=8YFLogxK

U2 - https://doi.org/10.5194/acp-22-2601-2022

DO - https://doi.org/10.5194/acp-22-2601-2022

M3 - مقالة مرجعية

SN - 1680-7316

VL - 22

SP - 2601

EP - 2623

JO - Atmospheric Chemistry and Physics

JF - Atmospheric Chemistry and Physics

IS - 4

ER -

Long-range prediction and the stratosphere

Abstract

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