Marine cloud base height retrieval from MODIS cloud properties using machine learning

Lenhardt, Julien; Quaas, Johannes; Sejdinovic, Dino

doi:https://doi.org/10.5194/amt-17-5655-2024

Articles | Volume 17, issue 18

https://doi.org/10.5194/amt-17-5655-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-17-5655-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 18

Research article

|

26 Sep 2024

Research article |

| 26 Sep 2024

Marine cloud base height retrieval from MODIS cloud properties using machine learning

Julien Lenhardt, Johannes Quaas, and Dino Sejdinovic

Data sets

Data for the article: "Marine cloud base height retrieval from MODIS cloud properties using machine learning" Julien Lenhardt et al. https://doi.org/10.5281/zenodo.10517686

MIDAS: Global Marine Meteorological Ob- servations Data Met Office https://catalogue.ceda.ac.uk/uuid/77910bcec71c820d4c92f40d3ed3f249

Cumulo: A Dataset for Learning Cloud Classes Valentina Zantedeschi et al. https://www.dropbox.com/sh/6gca7f0mb3b0ikz/AAAeTWF21WGZ7-y9MpSiL9P3a/CUMULO

Model code and software

Method code for the article: "Marine cloud base height retrieval from MODIS cloud properties using machine learning" Julien Lenhardt et al. https://doi.org/10.5281/zenodo.10517686

Interactive computing environment

Method code and data for the article: "Marine cloud base height retrieval from MODIS cloud properties using machine learning" Julien Lenhardt et al. https://doi.org/10.5281/zenodo.10517686

Short summary

Clouds play a key role in the regulation of the Earth's climate. Aspects like the height of...