Articles | Volume 17, issue 6
https://doi.org/10.5194/gmd-17-2247-2024
https://doi.org/10.5194/gmd-17-2247-2024
Model description paper
 | 
19 Mar 2024
Model description paper |  | 19 Mar 2024

cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands

Romain Pilon and Daniela I. V. Domeisen

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Cited articles

Anaconda, Inc.: Anaconda Software Distribution., Anaconda, Inc., https://www.anaconda.com (last access: 13 March 2024), 2016. a
Bengston, L., Botzet, M., and Esch, M.: Hurricane-type vortices in a general circulation model, Tellus A, 47, 175–196, https://doi.org/10.1034/j.1600-0870.1995.t01-1-00003.x, 1995. a
Beucler, T., Ebert-Uphoff, I., Michael, S. R., Pritchard, M., and Gentine, P.: Machine Learning for Clouds and Climate, invited Chapter for the AGU Geophysical Monograph Series “Clouds and Climate”, https://doi.org/10.1002/essoar.10506925.1, 2021. a
Brown, J. R., Lengaigne, M., Lintner, B. R., Widlansky, M. J., van der Wiel, K., Dutheil, C., Linsley, B. K., Matthews, A. J., and Renwick, J.: South Pacific Convergence Zone dynamics, variability and impacts in a changing climate, Nat. Rev. Earth Environ., 1, 530–543, https://doi.org/10.1038/s43017-020-0078-2, 2020. a, b
Camargo, S. J. and Zebiak, S. E.: Improving the Detection and Tracking of Tropical Cyclones in Atmospheric General Circulation Models, Weather Forecast., 17, 1152–1162, https://doi.org/10.1175/1520-0434(2002)017<1152:ITDATO>2.0.CO;2, 2002. a
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Short summary
This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
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