Effects on middle atmospheric dynamics by energetic particle precipitation above the Antarctic

This project was undertaken Summer 2018. I was being guided by Tracy Moffat Griffin and Andrew Kavanagh at the British Antarctic Survey in Cambridge. This was one of the most memorable and formative summers, academically, professionally and also personally. I was introduced to Atmospheric Physics (and hence went onto pursue the PhD at UofT) and also Space Plasma Physics, studying more the following semester under my tutor Daniel Whiter. This is where I learnt to leverage the scientific python stack (numpy, pandas, scipy), and also present my results (in the now defacto standard) Jupyter Notebooks. During the summer, I’d decided I wanted to become a scientific software engineer, helping scientists further pursue science.

See this article for a flavor of relevant work : EOS Science News by AGU featuring my supervisor Tracy.

Analysis

Briefly, the analysis we were conducting required me to:

• remove daily tidal influence. We found dominant modes with periods of 8hr, 12hr and ~24 hr using Lomb-Scargle analysis
• following which, we constructed windows of +/- 10 days from the energetic particle precipitation events
• then a superposed epoch analysis (a fancy term for averaging epochs)

I analysed ~21 years of raw data. We found some signal for high and middle energy proton events at the +4 to 6 day marks, however, there was not enough events for a statistically significant conclusion.

I left my supervisors Tracy Moffat Griffin and Andrew Kavanagh with interactive notebooks, so they could alter the energy thresholds for of what low/middle/high energetic particle precipitation events, as this effected the number of epochs we had in each category. This required me to heavily document and package my code, as they were not familiar with Python the python ecosystem at all.