Skip to content

Latest commit

 

History

History
63 lines (41 loc) · 1.95 KB

README.md

File metadata and controls

63 lines (41 loc) · 1.95 KB

MCS

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.