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)