Authors:

Ulrich Achatz, Joan Alexander, Erich Becker, Hye-Yeong Chun, Andreas Dörnbrack, Laura Holt, Riwal Plougonven, Inna Polichtchouk, Kaoru Sato, Aditi Sheshadri, Claudia Christine Stephan, Annelize van Niekerk, and Corwin J. Wright

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Abstract:

Atmospheric predictability from subseasonal 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 intercomparisons 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.

Plain Language Summary:

Gravity waves are atmospheric disturbances caused by processes like airflow over mountains and thunderstorms, playing a crucial role in weather and climate systems. However, these waves are challenging to capture fully in models used for weather prediction and climate studies. This paper reviews recent advances in observations, simulations, and theories to better understand gravity waves and improve how they are represented in models. By addressing current limitations, such as gaps in data and inaccurate parameterizations, the authors propose strategies to enhance forecasts and predictions of climate change impacts. The work highlights the need for ongoing improvements to ensure accurate and reliable modeling of atmospheric dynamics.