Atmospheric Gravity Waves: Processes and Parameterization

Ulrich Achatz; M. Joan Alexander; Erich Becker; Hye-Yeong Chun; Andreas Doernbrack; Laura A. Holt; Riwal Plougonven; Inna Polichtchouk; Kaoru Sato; Aditi Seshadri; Claudia Stephan; Annelize van Niekerk; Corwin Wright

doi:10.1175/JAS-D-23-0210.1

Atmospheric Gravity Waves: Processes and Parameterization

Ulrich Achatz, M. Joan Alexander, Erich Becker, Hye-Yeong Chun, Andreas Doernbrack, Laura A. Holt, Riwal Plougonven, Inna Polichtchouk, Kaoru Sato, Aditi Seshadri, Claudia Stephan, Annelize van Niekerk, Corwin Wright

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

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Abstract

Atmospheric predictability from sub-seasonal to seasonal time scales and climate variability are both influenced critically by gravity waves (GW). The quality of regional and global numerical models relies on thorough understanding of GW dynamics and its interplay with chemistry, precipitation, clouds and climate across many scales. For the foreseeable future, GWs and many other relevant processes will remain partly unresolved, and models will continue to rely on parameterizations. Recent model inter-comparisons and studies show that present-day GW parameterizations do not accurately represent GW processes. These shortcomings introduce uncertainties, among others, in predicting the effects of climate change on important modes of variability. However, the last decade has produced new data and advances in theoretical and numerical developments that promise to improve the situation. This review gives a survey of these developments, discusses the present status of GW parameterizations and formulates recommendations on how to proceed from there.

Original language	English
Pages (from-to)	237-262
Number of pages	26
Journal	Journal of the Atmospheric Sciences
Volume	81
Issue number	2
Early online date	23 Jan 2024
DOIs	https://doi.org/10.1175/JAS-D-23-0210.1
Publication status	Published - 29 Feb 2024

Data Availability Statement

Except for Fig. 7, no datasets were generated or analyzed during the current study. With regard to Fig. 7, the raw model output on the native grids amounts to few hundred terabytes, and thus it is not possible to make all data available for more than a few steps. However, postprocessed output used to make the figures will be retained and made available to those who request it. The analysis codes can be made available upon request.

Funding

Author Chun was supported by a National Research Foundation of Korea grant funded by the South Korea government (2021R1A2C100710212). Author Dörnbrack has been partly funded by the Federal Ministry for Education and Research under Grants 01 LG 1907 (Project WASCLIM) in the frame of the Role of the Middle Atmosphere in Climate (ROMIC) program. Further support by DFG under Grants GW-TP/DO 1020/9-1 and PACOG/RA 1400/6-1 in the frame of the DFG-Research Group MS-GWAVES is also acknowledged. Author Holt was supported by the NASA Aura Science Team (NASA Grant 80NSSC20K0950). Author Sato acknowledges support by JSPS KAKENHI Grant 22H00169. Author Plougonven is supported by ANR Project BOOST3R (ANR-17-CE01-0016-01) and by the Strateole-2 project, which is sponsored by CNES, CNRS/INSU, and NSF. Author Sheshadri acknowledges support from the NSF through Grant OAC-2004492. Author Stephan was funded by the Minerva Fast Track Programme of the Max Planck Society. Author Wright acknowledges support from a Royal Society University Research Fellowship (URFR-023) and by NERC Grants NE/S00985X/1 and NE/V01837X/1. Achatz, Sheshadri, and Ste-phan are furthermore grateful for support by Eric and Wendy Schmidt through the Schmidt Futures VESRI “DataWave” project. Acknowledgments. Author Achatz thanks the German Research Foundation (DFG) for partial support through the Research Unit “Multiscale Dynamics of Gravity Waves” (MS-GWaves; Grants AC 71/8-2, AC 71/9-2, and AC 71/12-2), CRC 181 “Energy transfers in Atmosphere an Ocean” (Project Number 274762653, Projects W01 “Gravity-wave parameterization for the atmosphere” and S02 “Improved Parameterizations and Numerics in Climate Models”), and CRC 301 “TPChange” (Project-ID 428312742, Projects B06 “Impact of small-scale dynamics on UTLS transport and mixing” and B07 “Impact of cirrus clouds on tropopause structure”). He also thanks the German Federal Ministry of Education and Research (BMBF) for partial support through the program Role of the Middle Atmosphere in Climate (ROMIC II: QUBICC) and through Grant 01LG1905B. Author Alexander was supported by the U.S. National Science Foundation under Awards 1642644 and 2004512.

Funders	Funder number
INSU
MS-GWaves	CRC 301, AC 71/12-2, 274762653, AC 71/9-2, AC 71/8-2
NASA Aura Science Team
South Korea government	2021R1A2C100710212
National Science Foundation	1642644, 2004512, OAC-2004492
National Aeronautics and Space Administration	80NSSC20K0950
Natural Environment Research Council	NE/V01837X/1, NE/S00985X/1
Royal Society	URF\R\221023
Deutsche Forschungsgemeinschaft (DFG)
Japan Society for the Promotion of Science	22H00169, ANR-17-CE01-0016-01
Bundesministerium für Bildung und Forschung	01LG1905B, GW-TP/DO 1020/9-1, 01 LG 1907, PACOG/RA 1400/6-1
Centre National d'Etudes Spatiales
National Research Foundation of Korea
Max-Planck-Gesellschaft
Centre national de la recherche scientifique

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Keywords

Atmosphere
Climate models
Gravity waves
Numerical weather prediction/forecasting
Subgrid-scale processes

ASJC Scopus subject areas

Atmospheric Science

Access to Document

10.1175/JAS-D-23-0210.1

Atmospheric Gravity Waves (accepted author manuscript)
© Copyright 20 November 2023 American Meteorological Society (AMS). The final publication is available at Journal of the Atmospheric Sciences via https://doi.org/10.1175/JAS-D-23-0210.1
Accepted author manuscript, 8.3 MB

Cite this

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title = "Atmospheric Gravity Waves: Processes and Parameterization",

abstract = "Atmospheric predictability from sub-seasonal to seasonal time scales and climate variability are both influenced critically by gravity waves (GW). The quality of regional and global numerical models relies on thorough understanding of GW dynamics and its interplay with chemistry, precipitation, clouds and climate across many scales. For the foreseeable future, GWs and many other relevant processes will remain partly unresolved, and models will continue to rely on parameterizations. Recent model inter-comparisons and studies show that present-day GW parameterizations do not accurately represent GW processes. These shortcomings introduce uncertainties, among others, in predicting the effects of climate change on important modes of variability. However, the last decade has produced new data and advances in theoretical and numerical developments that promise to improve the situation. This review gives a survey of these developments, discusses the present status of GW parameterizations and formulates recommendations on how to proceed from there.",

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AU - Becker, Erich

AU - Chun, Hye-Yeong

AU - Doernbrack, Andreas

AU - Holt, Laura A.

AU - Plougonven, Riwal

AU - Polichtchouk, Inna

AU - Sato, Kaoru

AU - Seshadri, Aditi

AU - Stephan, Claudia

AU - van Niekerk, Annelize

AU - Wright, Corwin

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AB - Atmospheric predictability from sub-seasonal to seasonal time scales and climate variability are both influenced critically by gravity waves (GW). The quality of regional and global numerical models relies on thorough understanding of GW dynamics and its interplay with chemistry, precipitation, clouds and climate across many scales. For the foreseeable future, GWs and many other relevant processes will remain partly unresolved, and models will continue to rely on parameterizations. Recent model inter-comparisons and studies show that present-day GW parameterizations do not accurately represent GW processes. These shortcomings introduce uncertainties, among others, in predicting the effects of climate change on important modes of variability. However, the last decade has produced new data and advances in theoretical and numerical developments that promise to improve the situation. This review gives a survey of these developments, discusses the present status of GW parameterizations and formulates recommendations on how to proceed from there.

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KW - Climate models

KW - Gravity waves

KW - Numerical weather prediction/forecasting

KW - Subgrid-scale processes

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DO - 10.1175/JAS-D-23-0210.1

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EP - 262

JO - Journal of the Atmospheric Sciences

JF - Journal of the Atmospheric Sciences

IS - 2

ER -

Atmospheric Gravity Waves: Processes and Parameterization

Abstract

Data Availability Statement

Funding

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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MesoS2D: Mesospheric sub-seasonal to decadal predictability

Planetary and Gravity Waves as Drivers of Sudden Stratospheric Warmings

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