Articles | Volume 16, issue 4
https://doi.org/10.5194/amt-16-1043-2023
https://doi.org/10.5194/amt-16-1043-2023
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

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Cited articles

Aggarwal, J. and Nandhakumar, N.: On the computation of motion from sequences of images-A review, P. IEEE, 76, 917–935, https://doi.org/10.1109/5.5965, 1988. a
Allen, M. R. and Ingram, W. J.: Constraints on future changes in climate and the hydrologic cycle, Nature, 419, 228–232, https://doi.org/10.1038/nature01092, 2002. a
Aumann, H. H., Behrangi, A., and Wang, Y.: Increased Frequency of Extreme Tropical Deep Convection: AIRS Observations and Climate Model Predictions, Geophys. Res. Lett., 45, 13530–13537, https://doi.org/10.1029/2018GL079423, 2018. a
Austin, P. M.: Relation between Measured Radar Reflectivity and Surface Rainfall, Mon. Weather Rev., 115, 1053–1070, https://doi.org/10.1175/1520-0493(1987)115<1053:RBMRRA>2.0.CO;2, 1987. a
Baker, S., Scharstein, D., Lewis, J. P., Roth, S., Black, M. J., and Szeliski, R.: A Database and Evaluation Methodology for Optical Flow, Int. J. Comput. Vision, 92, 1–31, https://doi.org/10.1007/s11263-010-0390-2, 2011. a
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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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