American Psychological Association 6th edition

Brüning, S., Tost, H., & Wand, M. [ca. 2025]. Obtaining 3 D convective characteristics from a machine learning-based integration of multi-sensor satellite observations (Johannes Gutenberg-Universität Mainz) [Cd]. Johannes Gutenberg-Universität Mainz, Mainz. https://doi.org/10.25358/openscience-13525

ISO-690 (author-date, English)

BRÜNING, Sarah, TOST, Holger und WAND, Michael, 2025. Obtaining 3 D convective characteristics from a machine learning-based integration of multi-sensor satellite observations. Mainz: Johannes Gutenberg-Universität Mainz.

Modern Language Association 9th edition

Brüning, S., H. Tost, und M. Wand. Obtaining 3 D convective characteristics from a machine learning-based integration of multi-sensor satellite observations. cd, Johannes Gutenberg-Universität Mainz, 2025, https://doi.org/10.25358/openscience-13525.

Mohr Siebeck - Recht (Deutsch - Österreich)

Emerald - Harvard

Brüning, S., Tost, H. und Wand, M. (2025), Obtaining 3 D convective characteristics from a machine learning-based integration of multi-sensor satellite observations, Johannes Gutenberg-Universität Mainz, Mainz, verfügbar unter:https://doi.org/10.25358/openscience-13525.

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.