Technical Skills

Drone Skills

  • Part 107 Licensed Pilot, September 2016 - Present
    • Current through March 2023
  • Experience flying (approximately 150 total hours as remote pilot in command):
    • DJI Matrice 100
    • Matrice 600
    • Matrice 600 Pro
    • Phantom 2
    • Mini 2
  • Experience repairing:
    • DJI Matrice 600
    • Matrice 600 Pro

Part 107 Waiver Experience

  • Responsible Person and Principal Author, 107W-2017-00889; waiver of 107.51b (altitude). Waiver allows for flights to 1200ft in an area covering parts of CO, WY, NE, KS. This was the first waiver of its type granted over a large area.
  • Principal Author, 107W-2018-15638; waiver of 107.29 (nighttime operation)

Computer Skills and Experience

  • Extremely Proficient: Python (including Scipy, Numpy, xarray, pandas), Fortran, C++ (including object-oriented C++), Git, C, HTML, PHP, Windows, MacOS, Linux, Microsoft Office Suite, HDF5/NetCDF4
  • Proficient: CUDA, SQL, Wolfram Mathematica, Bash, Java, GRIB, JavaScript, JSON, Adobe Lightroom, Bootstrap
  • Currently Learning: Docker, React/Gatsby (including this website!)

Software Developed

  • Regional Atmospheric Modeling System (RAMS) Model v6.2.16, 6.3.0, 6.3.1
    • Improved HDF5 subroutines, including optimization of output procedures for very large grids.
    • Fixed several bugs around I/O and enabled compatibility with HDF5 1.10 and 1.12.
    • RAMS Website RAMS GitHub
    • van den Heever, Susan C., Saleeby, Stephen M., Grant, Leah D., Igel, Adele L., and Freeman, Sean W. (2021). RAMSmodel/RAMS: RAMS release version 6.3.01 (v6.3.01). Zenodo. https://doi.org/10.5281/zenodo.5348024
  • Currently developing improvements to the Tracking and Object Based Analysis of Clouds (tobac) package
    • Enhanced speed of tracking (from exponential growth to linear growth) and feature detection (approximately 10x faster than original code)
    • Documentation and testing improvements
    • tobac repository: https://github.com/climate-processes/tobac
  • Ongoing development of the GPU-enabled Mesoscale and Cloud Model (GMAC)
    • A new model that runs on graphics cards (GPUs) and CPUs
    • Targeted at idealized cloud and storm research