I use Python and QGIS to visualize geospatial data ranging from hurricane forecasts to super high resolution simulations of severe thunderstorms.
Much of my work is focused on meteorological data visualization:
I write extensively about hurricanes when they threaten land in the western Atlantic.
One goal of mine is to incorporate more customized data analysis into these forecasts to more effectively communicate the forecast for these storms and their hazards.
Inspired by Cameron Nixon’s work plotting small hodographs on a grid, I decided to try the same with skew-Ts.
The result, still very much a work in progress, is a neat new way of visualizing spatial trends in thermodynamic profiles.
As part of my spring 2021 coursework, I’ve been running super high resolution simulations of severe storms using WRF on Cheyenne.
With grid spacing as small as 333m, these simulations have been fascinating (and challenging!) to analyze.
Much of my python visualization code, including the “SkewMap” code, is available on my GitHub page.
I’ve also used QGIS to explore some other datasets too:
Following two outbreaks of severe thunderstorms in the Southeastern US in March 2021, I decided to look at which areas had good low-level doppler radar coverage. I noticed a pattern I had seen elsewhere- in demographic and voting trends.
Sure enough, when I overlaid demographic data onto the radar coverage map, it becomes clear that much of the Black Belt, a corridor of largely Black communities stretching from southern Arkansas into central Georgia, is too far away from radar sites to have good low-level radar coverage.
Dr. Marshall Shepherd of the University of Georgia wrote more about this in Forbes.
Every year after the holidays, we inevitably start thinking about spring. But when does it usually arrive? The answer to such a question largely depends on what you consider “spring”. The first day above 50 where you don’t need a jacket to go outside? The first thunderstorm? First leaves on the trees?
I usually think of spring as really being when the brown landscape left by the melting snow turns to green. I made this map using data from the US National Phenological Network showing when, on average, leaves come out and flowers start blooming.