Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-2753-2023
https://doi.org/10.5194/gmd-16-2753-2023
Methods for assessment of models
 | 
23 May 2023
Methods for assessment of models |  | 23 May 2023

PyFLEXTRKR: a flexible feature tracking Python software for convective cloud analysis

Zhe Feng, Joseph Hardin, Hannah C. Barnes, Jianfeng Li, L. Ruby Leung, Adam Varble, and Zhixiao Zhang

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Cited articles

Ashley, W. S., Mote, T. L., Dixon, P. G., Trotter, S. L., Powell, E. J., Durkee, J. D., and Grundstein, A. J.: Distribution of Mesoscale Convective Complex Rainfall in the United States, Mon. Weather Rev., 131, 3003–3017, https://doi.org/10.1175/1520-0493(2003)131<3003:DOMCCR>2.0.CO;2, 2003. 
Barber, K. A., Burleyson, C. D., Feng, Z., and Hagos, S. M.: The influence of shallow cloud populations on transitions to deep convection in the Amazon, J. Atmos. Sci., 79, 723–743, https://doi.org/10.1175/jas-d-21-0141.1, 2021. 
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Chen, J., Hagos, S., Feng, Z., Fast, J. D., and Xiao, H.: The Role of Cloud-Cloud Interactions in the Organization of Shallow Cumulus Clouds, J. Atmos. Sci., 80, 671–686, https://doi.org/10.1175/jas-d-22-0004.1, 2022. 
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Short summary
PyFLEXTRKR is a flexible atmospheric feature tracking framework with specific capabilities to track convective clouds from a variety of observations and model simulations. The package has a collection of multi-object identification algorithms and has been optimized for large datasets. This paper describes the algorithms and demonstrates applications for tracking deep convective cells and mesoscale convective systems from observations and model simulations at a wide range of scales.