A new method for estimating atmospheric turbulence from global high-resolution radiosonde data  and comparison with the Thorpe method

Ko, Han-Chang; Chun, Hye-Yeong

doi:10.5194/essd-18-1905-2026

Articles | Volume 18, issue 3

https://doi.org/10.5194/essd-18-1905-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-18-1905-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 3

Data description article

|

12 Mar 2026

Data description article |

| 12 Mar 2026

A new method for estimating atmospheric turbulence from global high-resolution radiosonde data and comparison with the Thorpe method

Han-Chang Ko and Hye-Yeong Chun

Supplement

https://doi.org/10.5194/essd-18-1905-2026-supplement

Data sets

High vertical-resolution radiosonde data (HVRRD) NCEI https://www.ncei.noaa.gov/data/ecmwf-global-upper-air-bufr/

In-situ flight EDR data NOAA MADIS https://madis-data.cprk.ncep.noaa.gov/madisPublic1/data/archive/

Atmospheric turbulence estimation from high vertical-resolution radiosonde data (HVRRD) using the minimum Richardson number. Part 1. Han-Chang Ko and Hye-Yeong Chun https://doi.org/10.5281/zenodo.16899801

Atmospheric turbulence estimation from high vertical-resolution radiosonde data (HVRRD) using the minimum Richardson number. Part 2. Han-Chang Ko and Hye-Yeong Chun https://doi.org/10.5281/zenodo.16899803

Atmospheric turbulence estimation from high vertical-resolution radiosonde data (HVRRD) using the minimum Richardson number. Part 3. Han-Chang Ko and Hye-Yeong Chun https://doi.org/10.5281/zenodo.16899805

Atmospheric turbulence estimation from high vertical-resolution radiosonde data (HVRRD) using the minimum Richardson number. Part 4. Han-Chang Ko and Hye-Yeong Chun https://doi.org/10.5281/zenodo.16810246

Atmospheric turbulence estimation from high vertical-resolution radiosonde data (HVRRD) using the minimum Richardson number. Part 5. Han-Chang Ko and Hye-Yeong Chun /10.5281/zenodo.16899789

ERA5 reanalysis datasets European Centre for Medium-Range Weather forecasts (ECMWF) https://doi.org/10.24381/cds.bd0915c6

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Short summary

We developed a new method to detect turbulence in the atmosphere using global high-resolution balloon measurements of temperature and wind. Unlike earlier methods, ours can detect turbulence not only in unstable air but also in stable layers with strong wind changes. This approach better matches aircraft turbulence reports and reveals global patterns, such as seasonal shifts linked to jet streams and convection, helping improve flight safety and our understanding of extreme weather.