Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-2753-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-2753-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
23 May 2023
Methods for assessment of models |
| 23 May 2023
| 23 May 2023
PyFLEXTRKR: a flexible feature tracking Python software for convective cloud analysis
Atmospheric Sciences and Global Change Division, Pacific Northwest
National Laboratory, Richland, Washington, USA
Joseph Hardin
Atmospheric Sciences and Global Change Division, Pacific Northwest
National Laboratory, Richland, Washington, USA
Hannah C. Barnes
Atmospheric Sciences and Global Change Division, Pacific Northwest
National Laboratory, Richland, Washington, USA
Cooperative Institute for Research in Environmental Sciences at the
University of Colorado, Boulder, Colorado, USA
NOAA Global Systems Laboratory, Boulder, Colorado, USA
Jianfeng Li
Atmospheric Sciences and Global Change Division, Pacific Northwest
National Laboratory, Richland, Washington, USA
L. Ruby Leung
Atmospheric Sciences and Global Change Division, Pacific Northwest
National Laboratory, Richland, Washington, USA
Adam Varble
Atmospheric Sciences and Global Change Division, Pacific Northwest
National Laboratory, Richland, Washington, USA
Zhixiao Zhang
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, Utah, USA
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- On the relationship between precipitation extreme and local temperature over eastern China based on convection permitting simulations: roles of different moisture processes and precipitation types G. Dai et al. https://doi.org/10.1007/s00382-024-07467-w
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- Summertime Near‐Surface Temperature Biases Over the Central United States in Convection‐Permitting Simulations H. Qin et al. https://doi.org/10.1029/2023JD038624
- AUS2200: a high-resolution limited-area modelling project for Australia Y. Huang et al. https://doi.org/10.1071/ES25068
- cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands R. Pilon & D. Domeisen https://doi.org/10.5194/gmd-17-2247-2024
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Saved (final revised paper)
Latest update: 28 May 2026
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.
PyFLEXTRKR is a flexible atmospheric feature tracking framework with specific capabilities to...
