The MAESTRO turbulence dataset derived from  the SAFIRE ATR42 aircraft

Jaffeux, Louis; Lothon, Marie; Couvreux, Fleur; Bouniol, Dominique; Cayez, Grégoire; Joly, Lilian; Burgalat, Jérémie; De Saint Leger, Cyrille; Bellec, Hubert; Henry, Olivier; Chbib, Dyaa; Jiang, Tetyana; Gilles, Vergez; Bony, Sandrine

doi:10.5194/essd-18-8229-2026

Articles | Volume 18, issue 11

https://doi.org/10.5194/essd-18-8229-2026

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

https://doi.org/10.5194/essd-18-8229-2026

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

Articles | Volume 18, issue 11

Data description article

|

11 Nov 2026

Data description article |

| 11 Nov 2026

The MAESTRO turbulence dataset derived from the SAFIRE ATR42 aircraft

Louis Jaffeux, Marie Lothon, Fleur Couvreux, Dominique Bouniol, Grégoire Cayez, Lilian Joly, Jérémie Burgalat, Cyrille De Saint Leger, Hubert Bellec, Olivier Henry, Dyaa Chbib, Tetyana Jiang, Vergez Gilles, and Sandrine Bony

Data sets

MAESTRO_2024_Turbulence_Dataset L. Jaffeux and M. Lothon https://doi.org/10.25326/812#v7.0

MAESTRO-2024_SAFIRE-ATR42_SAFIRE_FAST Temperature and Humidity Fast Observation 25HZ S. Bony https://doi.org/10.25326/738

MAESTRO Thermodynamic and dynamic data 1HZ S. Bony https://doi.org/10.25326/744

Short summary

A new dataset from the MAESTRO airborne campaign over the tropical Atlantic near Cabo Verde offers detailed turbulence measurements of temperature, moisture, and wind. The data was processed exploiting exceptional instrumental redundancy to provide best quality turbulence statistics and ensure their reliability. This resource can benefit weather and climate models by providing a clearer picture of how turbulence below clouds influences their formation and organization.