How I became Dr Robin Wilson: Part 1
As many of you probably know, I’ve been working towards a PhD at the University of Southampton. This post is the brief story of my PhD, my graduation and my future plans.
So, back in the dim and distant days of 2010, I started a PhD with the Institute for Complex Systems Simulation (ICSS) at the University of Southampton. This is a Doctoral Training Centre (now known as Centres for Doctoral Training, because of an acronym clash!) which offers four-year PhDs: you start off with a year of taught courses (at MSc level, though you don’t actually get awarded an MSc), focused on building skills for your research, and then continue with a fairly standard three-years of research.
My first year was very useful, and covered a range of topics including introductions to complexity science and simulation methods, significant skills development in programming (particularly high-performance computing) and statistics, plus domain-specific courses (such as computer vision, remote sensing and machine learning). Many of these courses were coursework-focused, and helped me develop my writing skills (I also used this opportunity to properly learn LaTeX).
At the end of the taught year I did a ‘Summer Project’, which was equivalent to a MSc dissertation project. Mine had the wonderful title of “Can a single cloud spoil the view?”: Modelling the effect of an isolated cumulus cloud on calculated surface solar irradiance”. The story of this project is a blog post in itself, but in the mean time you can read my thesis here. I was particularly pleased to find out later that my thesis won the Remote Sensing and Photogrammetry Society (RSPSoc) Masters Thesis Prize – a highly-competitive award.
One of the benefits of doing a PhD through the ICSS was that I didn’t have to have a detailed plan for my entire PhD when I started: in fact, some of my colleagues didn’t even know what department they wanted to work in, and used the first year as an opportunity to ‘date’ potential supervisors and try out potential topics. I came in knowing I wanted to do a PhD in remote sensing, probably focusing on some sort of quantitative methods development, potentially in the areas of correction and calibration of satellite imagery (areas I’d worked on for my undergraduate dissertation), but I didn’t know much more than that.
By the time I got to the end of my taught year and actually started the ‘research component’ I’d narrowed down a little bit, and realised that I wanted to do something to do with atmospheric aerosols and atmospheric correction. I came up with a plan which involved looking at the spatial variability of atmospheric conditions (principally the aerosol content, as measured by Aerosol Optical Thickness, and water content, as measured by Precipitable Water Vapour). I can’t actually find a copy of this plan at the moment (it’s probably on one of my many external hard disks somewhere), so that vague memory will have to do for now!
What I have managed to find, however, is a copy of a report I produced for my first six-monthly supervisory meeting, summarising roughly what I’d done in that period. Looking back, I’m actually impressed as to what I’d managed to achieve:
- I’d started to investigate the spatial variability of the atmosphere over southern England, and had really been struggling with the availability and quality of data. This struggle actually led to a lot of interesting work, one of which was investigating the relationship between visibility (as measured by meteorological stations and airports) and Aerosol Optical Thickness (AOT, the measure of the ‘clarity of the atmosphere’ that I was interested in). According to my notes, I had submitted a paper about this within the first six months – and although that version of the paper was rejected, a later version was published as Wilson et al., 2015 (PDF).
- I had finished v1.0 of Py6S, my Python interface to the 6S Radiative Transfer Model. 6S simulates how light passes through the atmosphere under configurable atmospheric conditions, and is widely-used in atmospheric correction of satellite images. Again, I will probably write another article about how the idea for Py6S came about and the way it developed over time, but here I’ll just summarise by saying that developing Py6S was a great idea, it gave me a really useful framework for implementing the rest of my PhD projects, and it saved me a huge amount of time in the long run. Luckily, my supervisors were very supporting of me taking time to create a fully-featured version of Py6S, and I later published a paper on it in Computers & Geosciences as Wilson, 2013 (PDF)
- I’d investigated various other ideas, some of which came to fruition throughout the rest of my PhD (developing LED-based sun photometers, validation of GPS-based water vapour measurements, working with other radiative transfer models) and some of which didn’t (attempting to use webcams to monitor visibility and therefore AOT, monitoring various other environmental changes from webcams, developing full spectrometers using LEDs).
I’m pretty sure some of those things were done ‘on the side’ during my taught year, but I can’t remember exactly what I did when. Anyway, by the end of the first six months of full-time research I had a number of interesting ideas, some significant frustrations, some potential papers, and some big questions about where my PhD was going.
I was very aware that a PhD had to ‘tell a story’ and have a coherent thread running through it: I was confident that I could do research, but I knew that putting together 4-5 completely unrelated chapters wouldn’t satisfy an examiner. Reading my notes from meetings at the time show that I was really quite worried about this – there are lots of question marks all over the page, and notes about the importance of finding a good overall structure and aim.
This would come, but it would take some time – and you’ll have to wait until Part 2 for that…
Categorised as: Academic