Serendipity

I mentioned before that I’m teaching a new course this term, a first-year undergraduate seminar course on climate computing. Course starts next week, so I’m busy putting together some material. It’s intended to be pretty open ended, as it’s a small group seminar, and we can jump into topics that the students are interested in. So I put together a core set of topics I want to cover, and then a long list of other possible topics. Here’s what I have so far:

Core topics:

Part 1: Background & History

Week 1: Climate Science BC (Before Computers), in which we cover Fourier, Tyndall, Arrhenius, Callendar, and the discovery of global warming. We’ll introduce the key concepts for understanding how the physical climate system works.

Week 2: Taming Chaos in which we talk about Bjerknes and Lorenz, and look at the basic equations for modeling the atmosphere, and a gentle introduction to Chaos theory.

Week 3: The Giant Brain in which we talk about von Neumann, Charney, ENIAC and the first general circulation models.

Part 2: Basics of Climate Modeling

Week 4: Inside the simulation (also known as “Computational Fluid Dynamics on a Rotating Sphere for beginners”), where we look at the major elements of a climate model, including grids, dynamics, radiation, parameterizations, etc.

Week 5: What happens at the Boundaries? in which we look at the physical boundaries (land and ocean, the boundary layer), spatial boundaries (subgrid processes), temporal boundaries (start states, long runs, etc), and climate state boundaries (forcings, emissions scenarios, etc), and talk about the difference between Initial Value and Boundary Value problems.

Week 6: Towards Earth System Models in which we look at the growing complexity of modern GCMs, and the trade-offs between more resolution, more earth system processes, and more complexity.

Part 3: Choosing and Using Models

Week 8: On the Catwalk in which we look at the vast range of different types of models that are available, and what they are used for.

Week 9: Experimentation in which we look at what’s involved in running a model, and the kinds of experiments you might do with one. If we’re lucky, we’ll get to try running some experiments for real.

Week 10: How good are the models? in which we look at how to test and validate models, what it means to “do science” with a model, what model inter-comparison projects tell us, and some of weaknesses of current earth system models.

Part 4: What we can know, and what we can do

Week 11: Knowledge and Uncertainty, in which we talk about what we know and what we don’t know about climate change, sources of uncertainty, and whether we can predict the future. We’ll also explore how climate models interact with other types of knowledge about global climate change.

Week 12: Decisions, Decisions, Decisions in which we look at what policymakers need, and what they get. We’ll talk about the IPCC process, and maybe a bit about some of the policy options. We’ll talk about the need for better predictions of climate extremes, and regional impacts. And we’ll look at the difference between GCMs and IAMs.

Week 13: Enough talk, time for action! in which we face up to the question that given we now have to learn how to manage the earth’s climate systems, what should we be doing about climate change, and what other tools do we need in order to be successful?

Additional Topics:

We can include any of these based on interest and enthusiasm (but probably not all of them!). Some of these stray away from the “computing” them of the course, so we might need to agree on some criteria for which ones to include. In no particular order:

• Carbon calculators (and other softwre for personal/community decision support);
• Data Collection for weather and climate: how the global observing system works;
• Supercomputers and the path to exascale computing;
• Media potrayals of climate models and their projections;
• The role of Free/Open source software in climate science;
• The carbon footprint of computing;
• Other sources of evidence about climate change: paleoclimate, observational data, measurable impacts;
• Controversy and disinformation – how do you know who to trust? Is there really a debate, and if so, what about?
• How bad will it get?
• Climate Change and other global issues: over-population, peak oil, conservation of ecosystems, international conflict, food security, renewable energy, etc.;
• Geo-engineering;
• Climate Ethics: inter-nation and inter-generational issues.