Serendipity

On March 30, David Mackay, author of Sustainable Energy without the Hot Air, will be giving the J Tuzo Wilson lecture in the dept of Physics (Details of the time/location here). Here’s the abstract for his talk:

How easy is it get off our fossil fuel habit? What do the fundamental limits of physics say about sustainable energy? Could a typical “developed” country live on its own renewables? The technical potential of renewables is often said to be “huge” -but we need to know how this “huge” resource compares with another  “huge”: our huge power consumption. The public discussion of energy policy needs numbers, not adjectives. In this talk I will express power consumption and sustainable production in a single set of personal, human-friendly units. Getting off fossil fuels is not going to be easy, but it is possible.

The book itself is brilliant (and freely available online). But David’s visit is even more relevant, because it will give us a chance to show him a tool our group has been developing to facilitate and share the kinds of calculations that David does so well in the book.

We started from the question of how to take “back of the envelope” calculations and make them explicitly shareable over the web. And not just shareable, but to turn them into structured objects that can be discussed, updated, linked to evidence and so on (in much the same way that wikipedia entries are). Actually, the idea started with Jono’s calculations for the carbon footprint of “paper vs. screen”. When he first showed me his results, we got into a discussion of how other people might validate his calculations, and customize them for different contexts (e.g. for different hardware setups, different parts of the world with different energy mixes, etc). He came up with a graphical layout for the calculations, and we speculated how we would apply version control to this, make it a live calculator (so that changes in the input assumptions propagate like they would in a spreadsheet), and give each node it’s own URL, so that it can be attached to discussions, sources of evidence, etc. We brainstormed a long list of other features we’d want in such a tool, and we’re now busy creating a first prototype.

What kind of tool is it? My short description is that it is a crowd-sourced carbon calculator. Because I find existing carbon calculators to be very frustrating, because I can’t play with the assumptions in the calculations. Effectively, they are closed-source.

At the time we came up with these ideas, we were also working on modeling the analysis in David Mackay’s book (JP shows some preliminary results, here and here), to see if we could come up with a way of comparing his results with other books that also attempt to layout solutions to climate change. We created a domain model (as a UML class diagram), which was big and ugly, and a strategic actor goal model (using i*), which helped to identify key stakeholders, but didn’t capture the main content of Mackay’s analysis. So we tried modeling a chapter of the book as a calculation in Jonathan’s style, and it worked remarkably well. So we realized we needed to actually build the tool. And the rest, as they say, is history. Or at least will be, once we have a demo-able prototype…

I’ve been collecting examples of different types of climate model that students can use in the classroom to explore different aspects of climate science and climate policy. In the long run, I’d like to use these to make the teaching of climate literacy much more hands-on and discovery-based. My goal is to foster more critical thinking, by having students analyze the kinds of questions people ask about climate, figure out how to put together good answers using a combination of existing data, data analysis tools, simple computational models, and more sophisticated simulations. And of course, learn how to critique the answers based on the uncertainties in the lines of evidence they have used.

Anyway, as a start, here’s a collection of runnable and not-so-runnable models, some of which I’ve used in the classroom:

Simple Energy Balance Models (for exploring the basic physics)

• Zero dimensional Energy Balance from Wolfram. Allows you to adjust one parameter, the greenhouse effect, and explore the resulting equilibrium global temperature. Also serves to show off Wolfram’s Computable Document Format (CDF) which might be a neat way to share simple models with students.
• A simple spreadsheet zero-dimension energy balance model from Climateprediction.net. I like the idea of getting the students to do this in spreadsheets, because most of them already understand spreadsheets. This one has a parameter for heat capacity, so you can see how long it takes to reach a new equilibrium temperature.
• Energy Balance Model with ability to add atmosphere layers from Phet. This simulation shows off how greenhouse gas molecules interact with photons, trapping them or allowing them through. Pretty neat for giving students an intuition for how the greenhouse effect works.
• One-dimensional Energy Balance model from Shodor. Calculates the equilibrium temperature for each latitude zone on the planet, allowing you to specify cloud and ice albedo, solar constant, longwave radiation loss, and starting temperatures for each zone. Not very usable, but good illustration of what a 1-dimensional model might do. (Note: Shodor also have a great ecosystem sim with rabbits and wolves, and a disease transmission sim).
• A one-layer energy-balance model developed by Michael Mann at Penn state, for use in his course on global warming. Allows you to alter different feedback factors (albedo, clouds, ice, water vapour), to test their effect on temperature and climate sensitivity.
• A Java applet Global Energy Balance Model, from Rob MacKay at Clark College (part of a whole collection of Java Physlets from Davidson University)
• The Global Equilibrium Energy Balance Interactive Tinker Toy (Geebitt) from Chris Petersen at NASA GISS, a more sophisticated spreadsheet model.
• An energy flow simulator written in NetLogo from Northwestern U, showing how heat transfer works between the sun, atmosphere and ground, and allowing you to adjust CO2 and cloudiness dynamically.

General Circulation Models (for studying earth system interactions)

• EdGCM – an educational version of the NASA GISS general circulation model (well, an older version of it). EdGCM provides a simplified user interface for setting up model runs, but allows for some fairly sophisticated experiments. You typically need to let the model run overnight for a century-long simulation.
• Portable University Model of the Atmosphere (PUMA) – a planet Simulator designed by folks at the University of Hamburg for use in the classroom to help train students interested in becoming climate scientists.

Integrated Assessment Models (for policy analysis)

• C-Learn, a simple policy analysis tool from Climate Interactive. Allows you to specify emissions trajectories for three groups of nations, and explore the impact on global temperature. This is a simplified version of the C-ROADS model, which is used to analyze proposals during international climate treaty negotiations.
• Java Climate Model (JVM) – a detailed desktop assessment model that offers detailed controls over different emissions scenarios and regional responses.

Systems Dynamics Models (to foster systems thinking)

• Bathtub Dynamics and Climate Change from John Sterman at MIT. This simulation is intended to get students thinking about the relationship between emissions and concentrations, using the bathtub metaphor. It’s based on Sterman’s work on mental models of climate change.
• The Climate Challenge: Our Choices, also from Sterman’s team at MIT. This one looks fancier, but gives you less control over the simulation – you can just pick one of three emissions paths: increasing, stabilized or reducing. On the other hand, it’s very effective at demonstrating the point about emissions vs. concentrations.
• Carbon Cycle Model from Shodor, originally developed using Stella by folks at Cornell.
• And while we’re on systems dynamics, I ought to mention toolkits for building your own systems dynamics models, such as Stella from ISEE Systems (here’s an example of it used to teach the global carbon cycle).

Other Related Models

• A Kaya Identity Calculator, from David Archer at U Chicago. The Kaya identity is a way of expressing the interaction between the key drivers of carbon emissions: population growth, economic growth, energy efficiency, and the carbon intensity of our energy supply. Archer’s model allows you to play with these numbers.
• An Orbital Forcing Calculator, also from David Archer. This allows you to calculate what the effect changes in the earth’s orbit and the wobble on its axis have on the solar energy that the earth receives, in any year in the past of future.

Useful readings on the hierarchy of climate models

• Isaac Held on how simple models are like fruit flies in biological research – we can use them to give us a first test of whether an idea makes sense.
• John Baez has been collecting basic introductions to the different types of climate model, and has an entire grad course that walks through the mathematics of climate modelling.

Several people have mentioned to me that I missed an interesting interview on the CBC with the author of a new book on assessing carbon footprints, called How Bad Are Bananas? From the blurb, it sounds like it does a great job crunching the numbers to provide useful advice on where we should focus out actions. Here’s hoping it’s as strong as Mackay’s book on sustainable energy.

Okay, here’s a slightly different modeling challenge. It might be more of a visualization challenge. Whatever. In part 1, I suggested we use requirements analysis techniques to identify stakeholders, and stakeholder goals, and link them to the various suggested “wedges“.

Here, I want to suggest something different. There are several excellent books that attempt to address the “how will we do it?” challenge. They each set out a set of suggested solutions, add up the contribution of each solution to reducing emissions, assess the feasibility of each solution, add up all the numbers, and attempt to make some strategic recommendations. But each book makes different input assumptions, focusses on slightly different kinds of solutions, and ends up with different recommendations (but they also agree on many things).

Here are the four books:

George Monbiot, Heat: How to Stop the Planet from Burning. This is probably the best book I have ever read on global warming. It’s brilliantly researched, passionate, and doesn’t pull it’s punches. Plus it’s furiously upbeat – Monbiot takes on the challenge of how we get to 90% emissions reduction, and shows that it is possible (although you kind of have to imagine a world in which politicians are willing to do the right thing).

Joseph Romm, Hell and High Water: Global Warming–the Solution and the Politics–and What We Should Do. While lacking Monbiot’s compelling writing style, Romm makes up by being an insider – he was an energy policy wonk in the Clinton administration. The other contrast is Monbiot is British, and focusses mainly on British examples, Romm is American and focusses on US example. The cultural contrasts are interesting.

David MacKay, Sustainable Energy – Without the Hot Air. Okay, so I haven’t read this one yet, but it got a glowing write-up on Boing Boing . Oh, and it’s available as a free download.

Lester Brown, Plan B 3.0L Mobilizing to Save Civilization. This one’s been on my reading list for a while, will read it soon. It has a much broader remit than the others: Brown wants to solve world poverty, cure disease, feed the world, and solve the climate crisis. I’m looking forward to this one. And it’s also available as a free download.

Okay, so what’s the challenge? Model the set of solutions in each of these books so that it’s possible to compare and contrast their solutions, compare their assumptions, and easily identify areas of agreement and disagreement. I’ve no idea yet how to do this, but a related challenge would be to come up with compelling visualizations that explain to a much broader audience what these solutions look like, and why it’s perfectly feasible. Something like this (my current favourite graphic):

Graph of cost/benefit of climate mitigation strategies