After a long hiatus – much longer than I like to think about or admit to – I am finally back. I just finished the last semester of my undergraduate degree, which was by far the busiest few months I’ve ever experienced.
This was largely due to my honours thesis, on which I spent probably three times more effort than was warranted. I built a (not very good, but still interesting) model of ocean circulation and implemented it in Python. It turns out that (surprise, surprise) it’s really hard to get a numerical solution to the Navier-Stokes equations to converge. I now have an enormous amount of respect for ocean models like MOM, POP, and NEMO, which are extremely realistic as well as extremely stable. I also feel like I know the physics governing ocean circulation inside out, which will definitely be useful going forward.
Convocation is not until early June, so I am spending the month of May back in Toronto working with Steve Easterbrook. We are finally finishing up our project on the software architecture of climate models, and writing it up into a paper which we hope to submit early this summer. It’s great to be back in Toronto, and to have a chance to revisit all of the interesting places I found the first time around.
In August I will be returning to Australia to begin a PhD in Climate Science at the University of New South Wales, with Katrin Meissner and Matthew England as my supervisors. I am so, so excited about this. It was a big decision to make but ultimately I’m confident it was the right one, and I can’t wait to see what adventures Australia will bring.
If you haven’t already guessed, I am a real math and science geek (and rapidly becoming a computer programming geek as well). So, when I got my first taste of quantitative climate analysis from Dana’s articles over at Skeptical Science, I was really interested. It will be a while before my education takes me in that direction, and I’m starting to think I’m not that patient. I would like to learn some relevant physics and programming ahead of time.
Here is my list of plans and resources, roughly in order of priority:
Learn Fortran. The majority of code in climate models is written in Fortran, and this probably isn’t going to change any time soon. I have begun studying an online Fortran 77 tutorial, and am finding that learning a second programming language is far easier than the first (Java, in my case). The major concepts are virtually identical – it’s all a case of syntax.
Read and do problems from some relevant chapters in my physics textbook that we will not be covering in the course: fluid dynamics and thermodynamics.
Follow through, in detail, a derivation of a zero-dimensional energy balance model for the Earth that was kindly sent to me by a reader.
Read David Archer’s textbook, Global Warming: Understanding the Forecast. I attempted to read it a year or two ago, but I hadn’t done very much physics yet and consequently became kind of lost (“Electrons are waves?!” the younger Kate said incredulously). Dr. Archer has also posted accompanying video lectures from the University of Chicago course the book is based on, which will help.
Try to find a copy of Ray Pierrehumbert’s new book, Principles of Planetary Climate. From what I have heard, this will involve learning some Python.
I have several textbooks on loan or second hand, two regarding climate physics, and one about general atmospheric dynamics.
That will probably keep me busy for some time, but I would appreciate recommendations for additions/changes!