Yau (2026) mwyau/PyStormTracker: v0.5.0.dev0

Identification

• Journal: Open MIND
• Year: 2026
• Date: 2026-03-28
• Authors: Albert Yau
• DOI: 10.5281/zenodo.19295199

Research Groups

No specific research groups or departments are mentioned; the software is authored by Albert M. W. Yau.

Short Summary

This paper presents PyStormTracker, a high-performance Python-based software designed for tracking cyclones, leveraging parallel computing libraries like Dask and MPI.

Objective

• To develop and release PyStormTracker, a high-performance cyclone tracking software in Python.
• To provide a robust and efficient tool for analyzing cyclone variability.

Study Configuration

• Spatial Scale: Not directly applicable to the software itself; its application depends on the spatial resolution of the input meteorological data.
• Temporal Scale: Not directly applicable to the software itself; its application depends on the temporal resolution of the input meteorological data.

Methodology and Data

• Models used: PyStormTracker (the software itself). It utilizes Dask and MPI for high-performance computing.
• Data sources: Not specified in the provided text; the software is designed to process cyclone-related data.

Main Results

• Release of PyStormTracker, a Python-based software for cyclone tracking.
• The software is characterized as "high-performance," implying efficiency in processing large datasets.
• It integrates Dask and MPI for parallel computation, enhancing its performance capabilities.

Contributions

• Provides an open-source, high-performance tool for cyclone tracking, addressing the need for efficient analysis in climate variability studies.
• Leverages modern parallel computing techniques (Dask, MPI) within a Python framework, making it accessible and scalable for researchers.

Funding

No specific funding projects or programs for the PyStormTracker software itself are listed in the provided text.

Citation

@article{Yau2026mwyauPyStormTracker,
  author = {Yau, Albert},
  title = {mwyau/PyStormTracker: v0.5.0.dev0},
  journal = {Open MIND},
  year = {2026},
  doi = {10.5281/zenodo.19295199},
  url = {https://doi.org/10.5281/zenodo.19295199}
}