PyStormTracker

PyStormTracker is a Python package for cyclone trajectory analysis. It provides cyclone detection, trajectory construction, track comparison, variable sampling, and storm track statistics for meteorological and climate datasets. The package includes a Numba implementation of the Simple Tracker used in Yau and Chang (2020) and tracking methods based on Hodges (1994, 1995, 1999). The project was initially developed at the National Center for Atmospheric Research (NCAR) during the 2015 SIParCS program.

Features

• Simple tracking with nearest-neighbor linking; Hodges and HEALPix tracking with adaptive constraints and Modified Greedy Exchange.
• NetCDF, GRIB, and Zarr input on regular, Gaussian, reduced-Gaussian, projected, and HEALPix grids; TrackJSON, TRACK tdump, and IMILAST track formats.
• Spectral preprocessing, feature refinement, track comparison, variable sampling, and storm track metrics.
• Serial, Dask, and MPI execution with Numba-accelerated numerical kernels and array-backed track storage.

Usage

PyStormTracker requires Python 3.12+.

pip install PyStormTracker

stormtracker track \
    -i data.nc \
    --variable msl \
    -o tracks.trackjson \
    -m min \
    -a hodges

Python API:

import pystormtracker as pst

tracker = pst.HodgesTracker()
tracks = tracker.track(data="data.nc", variable="msl", detection_mode="min")

See the Quickstart for installation options, CLI and Python usage, formats, sample data, and development commands.

Documentation

Documentation · Quickstart · CLI · API · Architecture · Hodges / TRACK · HEALPix · TrackJSON · Benchmarks

References

If you use PyStormTracker in research, please cite the software:

• Yau, A. M. W., 2026: PyStormTracker: A High-Performance Cyclone Tracker in Python. Zenodo, doi:10.5281/zenodo.18764813.

PyStormTracker was originally presented as:

• Yau, A. M. W., K. Paul, and J. Dennis, 2016: PyStormTracker: A Parallel Object-Oriented Cyclone Tracker in Python. 96th American Meteorological Society Annual Meeting, New Orleans, LA. Zenodo, doi:10.5281/zenodo.18868625.

For SimpleTracker and storm track metrics:

• Yau, A. M. W., and E. K. M. Chang, 2020: Finding Storm Track Activity Metrics That Are Highly Correlated with Weather Impacts. Part I: Frameworks for Evaluation and Accumulated Track Activity. J. Climate, 33, 10169–10186, doi:10.1175/JCLI-D-20-0393.1.

For the methods implemented by HodgesTracker:

• Hodges, K. I., 1994: A General Method for Tracking Analysis and Its Application to Meteorological Data. Mon. Wea. Rev., 122, 2573–2586, doi:10.1175/1520-0493(1994)122<2573:AGMFTA>2.0.CO;2.
• Hodges, K. I., 1995: Feature Tracking on the Unit Sphere. Mon. Wea. Rev., 123, 3458–3465, doi:10.1175/1520-0493(1995)123<3458:FTOTUS>2.0.CO;2.
• Hodges, K. I., 1999: Adaptive Constraints for Feature Tracking. Mon. Wea. Rev., 127, 1362–1373, doi:10.1175/1520-0493(1999)127<1362:ACFFT>2.0.CO;2.

PyStormTracker uses spharmgrid for spherical harmonic filtering, regridding, and wind kinematics on Gauss–Legendre and Clenshaw–Curtis grids. It uses ducc0 directly for reduced Gaussian and HEALPix grids, polar regridding, and regional cosine transforms:

• Yau, A. M. W., 2026: spharmgrid. Zenodo, doi:10.5281/zenodo.22559210.

• Reinecke, M., 2020: DUCC: Distinctly Useful Code Collection. Astrophysics Source Code Library, record ascl:2008.023.

For the IMILAST intercomparison:

• Neu, U., et al., 2013: IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms. Bull. Amer. Meteor. Soc., 94, 529–547, doi:10.1175/BAMS-D-11-00154.1.

Additional method-specific references are given in the relevant documentation.

License

PyStormTracker is distributed under the BSD 3-Clause License.