TAMS

TAMS (Tracking Algorithm for Mesoscale Convective Systems) in Python and with more flexibility.

The original TAMS is described in Núñez Ocasio et al. [1]. Núñez Ocasio et al. [U1] applied TAMS to African Easterly Wave research.

Note

A paper describing this implementation of TAMS [2] in Python has been published in GMD (2024-08-15).

Datasets used in the examples can be retrieved with tams.data.download_examples().

Installing

TAMS is available on conda-forge.

conda install -c conda-forge tams

The recipe includes the core dependencies and some extras, but you may also wish to install:

• pyarrow – to save results with CE or MCS shapes in GeoDataFrame format to disk as Parquet files with to_parquet()

• ipykernel – to use your conda environment in another environment’s Jupyter (for example, NCAR JupyterHub)

Attention

Current tams.identify() doesn’t work with matplotlib 3.8.0 (mid Sep 2023), but 3.8.1 (end of Oct 2023) restored the previous behavior.

Note

In the past (before TAMS v0.1.5, mid Aug 2024), the TAMS conda-forge recipe included PyGEOS, in order to make certain GeoPandas and regionmask operations faster. In Shapely v2 (mid Dec 2022, but not relevant to TAMS until mid 2023), PyGEOS is part of Shapely and doesn’t need to be installed separately. GeoPandas dropped support for Shapely v1 and PyGEOS in their v1 release (late Jun 2024). PyGEOS on conda-forge has been retired, so you likely won’t be able to install it in new conda environments in any case.

Development install

If you want to modify the code, you can first clone the repo and then do an editable install to the dev conda environment:

git clone https://github.com/knubez/TAMS.git
cd TAMS
conda env create -f environment-dev.yml
conda activate tams-dev
pip install -e . --no-deps

Citing

If you use TAMS in your research, we would appreciate it if you cite Núñez Ocasio and Moon [2]. Since v0.1.2 (late Sep 2023), you can additionally cite the specific version of TAMS that you used via Zenodo.

References

[2] (1,2)

Kelly M. Núñez Ocasio and Zachary L. Moon. TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets. Geoscientific Model Development, 17(15):6035–6049, Aug 2024. doi:10.5194/gmd-17-6035-2024.

[1]

Kelly M. Núñez Ocasio, Jenni L. Evans, and George S. Young. Tracking mesoscale convective systems that are potential candidates for tropical cyclogenesis. Monthly Weather Review, 148(2):655–669, Feb 2020. doi:10.1175/MWR-D-19-0070.1.

Papers using TAMS

[U6]

Giselle Martinez, Angela K. Rowe, Kelly M. Núñez Ocasio, Zachary L. Moon, and Benjamin D. Rodenkirch. Evaluating environmental moisture relative to tropical deep convective growth using CPEX-CV airborne and satellite observations. Journal of Geophysical Research: Atmospheres, Sep 2025. doi:10.1029/2025JD043877.

[U5]

Zhe Feng, Andreas F. Prein, Julia Kukulies, Thomas Fiolleau, William K. Jones, Ben Maybee, Zachary L. Moon, Kelly M. Núñez Ocasio, Wenhao Dong, Maria J. Molina, Mary Grace Albright, Manikandan Rajagopal, Vanessa Robledo, Jinyan Song, Fengfei Song, L. Ruby Leung, Adam C. Varble, Cornelia Klein, Remy Roca, Ran Feng, and John F. Mejia. Mesoscale convective systems tracking method intercomparison (MCSMIP): application to DYAMOND global km-scale simulations. Journal of Geophysical Research: Atmospheres, Apr 2025. doi:10.1029/2024JD042204.

[U4]

Sanaullah Zehri, Agung Adiputra, Hasna Rofifah, and Afiq Mahasin. Implementation of tracking algorithm for mesoscale convective systems in flood disaster events over East Belitung, Indonesia. Jurnal Meteorologi dan Geofisika, 25(1):69–81, Mar 2025. doi:10.31172/jmg.v25i1.1075.

[U3]

Edward P. Nowottnick, Angela K. Rowe, Amin R. Nehrir, Jonathan A. Zawislak, Aaron J. Piña, Will McCarty, Rory A. Barton-Grimley, Kristopher M. Bedka, J. Ryan Bennett, Alan Brammer, Megan E. Buzanowicz, Gao Chen, Shu-Hua Chen, Shuyi S. Chen, Peter R. Colarco, John W. Cooney, Ewan Crosbie, James Doyle, Thorsten Fehr, Richard A. Ferrare, Steven D. Harrah, Svetla M. Hristova-Veleva, Bjorn H. Lambrigtsen, Quinton A. Lawton, Allan Lee, Eleni Marinou, Elinor R. Martin, Griša Močnik, Edoardo Mazza, Raquel Rodriguez Monje, Kelly M. Núñez Ocasio, Zhaoxia Pu, Manikandan Rajagopal, Jeffrey S. Reid, Claire E. Robinson, Rosimar Rios-Berrios, Benjamin D. Rodenkirch, Naoko Sakaeda, Vidal Salazar, Michael A. Shook, Leigh Sinclair, Gail M. Skofronick-Jackson, K. Lee Thornhill, Ryan D. Torn, David P. Van Gilst, Peter G. Veals, Holger Vömel, Sun Wong, Shun-Nan Wu, Luke D. Ziemba, and Edward J. Zipser. Dust, convection, winds, and waves: the 2022 NASA CPEX-CV campaign. Bulletin of the American Meteorological Society, 105(11):E2097–E2125, Nov 2024. doi:10.1175/BAMS-D-23-0201.1.

[U2]

Andreas F. Prein, Zhe Feng, Thomas Fiolleau, Zachary L. Moon, Kelly M. Núñez Ocasio, Julia Kukulies, Rémy Roca, Adam C. Varble, Amanda Rehbein, Changhai Liu, Kyoko Ikeda, Ye Mu, and Roy M. Rasmussen. Km-scale simulations of mesoscale convective systems over South America—a feature tracker intercomparison. Journal of Geophysical Research: Atmospheres, Apr 2024. doi:10.1029/2023JD040254.

[U1]

Kelly M. Núñez Ocasio, Jenni L. Evans, and George S. Young. A wave-relative framework analysis of AEW–MCS interactions leading to tropical cyclogenesis. Monthly Weather Review, 148(11):4657–4671, Nov 2020. doi:10.1175/MWR-D-20-0152.1.

Example notebook timings

Document	Modified	Method	Run Time (s)	Status
examples/get	2025-09-13 20:44	cache	78.79	✅
examples/identify	2025-09-13 20:44	cache	9.46	✅
examples/sample-mpas-ug-data	2025-09-13 20:45	cache	18.69	✅
examples/sample-satellite-data	2025-09-13 20:45	cache	12.24	✅
examples/tams-run	2025-09-13 20:45	cache	8.38	✅