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glm-forecast-graphic

This package recreates the tropical cyclone intensity change forecasting graphic aid proposed by Stevenson et al. in their 2017 paper, cited below:

Stevenson, Stephanie N., et al. “A 10-Year Survey of Tropical Cyclone Inner-Core Lightning Bursts and Their Relationship to Intensity Change.” Weather and Forecasting, vol. 33, no. 1, Feb. 2018, pp. 23–36., doi:10.1175/waf-d-17-0096.1.

Prerequisites

  • Python 3.6
    • Boto3
    • Botocore
    • Cartopy
    • Functools
    • Matplotlib
    • NetCDF4
    • Numpy
    • Pandas
    • Pyproj
    • Shapely
    • urllib

Data Sources

  • National Oceanic & Atmospheric Administration (NOAA)
    • GOES-16
      • Advanced Baseline Imager (ABI)
      • Geostationary Lightning Mapper (GLM)
    • Statistical Hurricane Intensity Prediction Scheme (SHIPS)
  • National Hurricane Center (NHC)
    • NOAA Aircraft Operations Center (AOC) & USAFRC 53rd Weather Reconnaissance Squadron (53rd WRS)
      • Vortex Data Message (VDM)
      • TEMP DROP

Authors

  • Matt Nicholson - Department of Atmospheric & Oceanic Science, University of Maryland, College Park

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

  • Pat Meyers, Cooperative Institute for Climate & Satellites - Maryland (CICS-MD)
  • Tim Canty, Department of Atmospheric & Oceanic Science, University of Maryland, College Park
  • Scott Rudlosky, Cooperative Institute for Climate & Satellites - Maryland (CICS-MD)

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