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Abstract Atmospheric turbulence plays a key role in the mixing of trace gases and diffusion of heat and momentum, as well as in aircraft operations. Although numerous observational turbulence studies have been conducted using campaign experiments and operational data, understanding the turbulence characteristics particularly in the free atmosphere remains challenging due to its small-scale, intermittent, and sporadic nature, along with limited observational data. To address this, turbulence in the free atmosphere is estimated herein based on the Thorpe method by using operational high vertical-resolution radiosonde data (HVRRD) with vertical resolutions of about 5 or 10 m across near-global regions, provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) via the U.S. National Centers for Environmental Information (NCEI) for 6 years (October 2017–September 2023). Globally, turbulence is stronger in the troposphere than in the stratosphere, with maximum turbulence occurring about 6 km below the tropopause, followed by a sharp decrease above. Seasonal variations show strong tropospheric turbulence in summer and weak turbulence in winter for both hemispheres, while the stratosphere exhibits strong turbulence during spring. Regional analyses identify strong turbulence regions over the South Pacific and South Africa in the troposphere and over East Asia and South Africa in the stratosphere. Notably, turbulence information can be provided in regions and high altitudes that are not covered by commercial aircraft, suggesting its potential utility for both present and future high-altitude aircraft operations. 

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.