Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 16, issue 4
Articles | Volume 16, issue 4
https://doi.org/10.5194/amt-16-1043-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-16-1043-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 4
Research article
 | 
02 Mar 2023
Research article |  | 02 Mar 2023

A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations

William K. Jones, Matthew W. Christensen, and Philip Stier

Data sets

tobac-flow Validation data William K. Jones https://doi.org/10.5281/zenodo.5885722

Model code and software

tobac-flow v1.0 (https://github.com/w-k-jones/tobac-flow/releases/tag/v1.0) William K. Jones https://doi.org/10.5281/zenodo.5889171

tobac-flow William K. Jones https://github.com/w-k-jones/tobac-flow/

tobac-flow: Tracking Paper Plots William K. Jones https://github.com/w-k-jones/tobac-flow/blob/master/examples/TrackingPaperPlots.ipynb

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Short summary
Geostationary weather satellites have been used to detect storm clouds since their earliest applications. However, this task remains difficult as imaging satellites cannot observe the strong vertical winds that are characteristic of storm clouds. Here we introduce a new method that allows us to detect the early development of storms and continue to track them throughout their lifetime, allowing us to study how their early behaviour affects subsequent weather.
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