Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 14, issue 4
Articles | Volume 14, issue 4
https://doi.org/10.5194/amt-14-2699-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-2699-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 4
Research article
 | 
08 Apr 2021
Research article |  | 08 Apr 2021

Applying machine learning methods to detect convection using Geostationary Operational Environmental Satellite-16 (GOES-16) advanced baseline imager (ABI) data

Yoonjin Lee, Christian D. Kummerow, and Imme Ebert-Uphoff

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Short summary
Convective clouds are usually associated with intense rain that can cause severe damage, and thus it is important to accurately detect convective clouds. This study develops a machine learning model that can identify convective clouds from five temporal visible and infrared images as humans can point at convective regions by finding bright and bubbling areas. The results look promising when compared to radar-derived products, which are commonly used for detecting convection.
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