Advances in Statistical Climatology, Meteorology and Oceanography
Advances in Statistical Climatology, Meteorology and Oceanography
ASCMO
Articles | Volume 5, issue 2
Articles | Volume 5, issue 2
https://doi.org/10.5194/ascmo-5-147-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-5-147-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 5, issue 2
21 Nov 2019
 | 21 Nov 2019

Automated detection of weather fronts using a deep learning neural network

James C. Biard and Kenneth E. Kunkel

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Short summary
A deep learning convolutional neural network (DL-FRONT) was around 90 % successful in determining the locations of weather fronts over North America when compared against front locations determined manually by forecasters. DL-FRONT detects fronts using maps of air pressure, temperature, humidity, and wind from historical observations or climate models. DL-FRONT makes it possible to do science that was previously impractical because manual front identification would take too much time.
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