MCS Segmentation, Classification, and Tracking Project: Data, Analyses, and Results
Requirements:
- Python 3.5
- numpy
- scipy
- matplotlib
- scikit-image / pillow
- scikit-learn (0.18.2 preferred)
- xgboost-python (linux only)
- cartopy
- pandas
- geopandas
Public access to data will be available soon.
MCS Climatology Paper Citation
Haberlie, A. M., and W. S. Ashley, 2019: A radar-based climatology of mesoscale convective systems in the United States. Journal of Climate.
If using slice data generated by this project or the described methods, please cite:
Haberlie, A. M., and W. S. Ashley, 2018: Identifying mesoscale convective systems in radar mosaics. Part I. Segmentation and classification. Journal of Applied Meteorology and Climatology, 57, 1575-1598.
If using swath data generated by this project or the described methods, please cite this paper in addition to the first paper:
Haberlie, A. M., and W. S. Ashley, 2018: Identifying mesoscale convective systems in radar mosaics. Part II. Tracking and application. Journal of Applied Meteorology and Climatology, 57, 1599-1621.
Dynamical Downscaling Paper:
Haberlie, A. M., and W. S. Ashley, 2018: Climatological representation of mesoscale convective systems in a dynamically downscaled climate simulation. International Journal of Climatology. In Press.
This research is supported by National Science Foundation Grant ATM-1637225, an NIU Division of Research and Innovation Partnerships Research and Artistry Grant, and an NIU Graduate School Dissertation Completion Fellowship.
