Climate change and the jet stream













A New Kind of Science

Cross-posted from NextGen Journal

Ask most people to picture a scientist at work, and they’ll probably imagine someone in a lab coat and safety goggles, surrounded by test tubes and Bunsen burners. If they’re fans of The Big Bang Theory, maybe they’ll picture complicated equations being scribbled on whiteboards. Others might think of the Large Hadron Collider, or people wading through a swamp taking water samples.

All of these images are pretty accurate – real scientists, in one field or another, do these things as part of their job. But a large and growing approach to science, which is present in nearly every field, replaces the lab bench or swamp with a computer. Mathematical modelling, which essentially means programming the complicated equations from the whiteboard into a computer and solving them many times, is the science of today.

Computer models are used for all sorts of research questions. Epidemiologists build models of an avian flu outbreak, to see how the virus might spread through the population. Paleontologists build biomechanical models of different dinosaurs, to figure out how fast they could run or how high they could stretch their necks. I’m a research student in climate science, where we build models of the entire planet, to study the possible effects of global warming.

All of these models simulate systems which aren’t available in the real world. Avian flu hasn’t taken hold yet, and no sane scientist would deliberately start an outbreak just so they could study it! Dinosaurs are extinct, and playing around with their fossilized bones to see how they might move would be heavy and expensive. Finally, there’s only one Earth, and it’s currently in use. So models don’t replace lab and field work – rather, they add to it. Mathematical models let us perform controlled experiments that would otherwise be impossible.

If you’re interested in scientific modelling, spend your college years learning a lot of math, particularly calculus, differential equations, and numerical methods. The actual application of the modelling, like paleontology or climatology, is less important for now – you can pick that up later, or read about it on your own time. It might seem counter-intuitive to neglect the very system you’re planning to spend your life studying, but it’s far easier this way. A few weeks ago I was writing some computer code for our lab’s climate model, and I needed to calculate a double integral of baroclinic velocity in the Atlantic Ocean. I didn’t know what baroclinic velocity was, but it only took a few minutes to dig up a paper that defined it. My work would have been a lot harder if, instead, I hadn’t known what a double integral was.

It’s also important to become comfortable with computer programming. You might think it’s just the domain of software developers at Google or Apple, but it’s also the main tool of scientists all over the world. Two or three courses in computer science, where you’ll learn a multi-purpose language like C or Java, are all you need. Any other languages you need in the future will take you days, rather than months, to master. If you own a Mac or run Linux on a PC, spend a few hours learning some basic UNIX commands – it’ll save you a lot of time down the road. (Also, if the science plan falls through, computer science is one of the only majors which will almost definitely get you a high-paying job straight out of college.)

Computer models might seem mysterious, or even untrustworthy, when the news anchor mentions them in passing. In fact, they’re no less scientific than the equations that Sheldon Cooper scrawls on his whiteboard. They’re just packaged together in a different form.

How do climate models work?

Also published at Skeptical Science

This is a climate model:





A pixellated Earth






Cracking the code









Show time





Predicting the past






Answering the big questions



Why Trust Science?

Part 1 of a series of 5 for NextGen Journal.

What’s wrong with these statements?

  • I believe in global warming.
  • I don’t believe in global warming.

Don’t see it? How about these?

  • I believe in photosynthesis.
  • I don’t believe in Newton’s Laws of Motion.












Beautiful Things

This is what the last few days have taught me: even if the code for climate models can seem dense and confusing, the output is absolutely amazing.

Late yesterday I discovered a page of plots and animations from the Canadian Centre for Climate Modelling and Analysis. The most recent coupled global model represented on that page is CGCM3, so I looked at those animations. I noticed something very interesting: the North Atlantic, independent of the emissions scenario, was projected to cool slightly, while the world around it warmed up. Here is an example, from the A1B scenario. Don’t worry if the animation is already at the end, it will loop:

It turns out that this slight cooling is due to the North Atlantic circulation slowing down, as is very likely to happen from large additions of freshwater that change the salinity and density of the ocean (IPCC AR4 WG1, FAQ 10.2). This freshwater could come from either increased precipitation due to climate change, or meltwater from the Arctic ending up in the North Atlantic. Of course, we hear about this all the time – the unlikely prospect of the Gulf Stream completely shutting down and Europe going into an ice age, as displayed in The Day After Tomorrow – but, until now, I hadn’t realized that even a slight slowing of the circulation could cool the North Atlantic, while Europe remained unaffected.

Then, in chapter 8 of the IPCC, I read something that surprised me: climate models generate their own El Ninos and La Ninas. Scientists don’t understand quite what triggers the circulation patterns leading to these phenomena, so how can they be in the models? It turns out that the modellers don’t have to parameterize the ENSO cycles at all: they have done such a good job of reproducing global circulation from first principles that ENSO arises by itself, even though we don’t know why. How cool is that? (Thanks to Jim Prall and Things Break for their help with this puzzle.)

Jim Prall also pointed me to an HD animation of output from the UK-Japan Climate Collaboration. I can’t seem to embed the QuickTime movie (WordPress strips out some of the necessary HTML tags) so you will have to click on the link to watch it. It’s pretty long – almost 17 minutes – as it represents an entire year of the world’s climate system, in one-hour time steps. It shows 1978-79, starting from observational data, but from there it simulates its own circulation.

I am struck by the beauty of this output – the swirling cyclonic precipitation, the steady prevailing westerlies and trade winds, the subtropical high pressure belt clear from the relative absence of cloud cover in these regions. You can see storms sprinkling across the Amazon Basin, monsoons pounding South Asia, and sea ice at both poles advancing and retreating with the seasons. Scientists didn’t explicitly tell their models to do any of this. It all appeared from first principles.

Take 17 minutes out of your day to watch it – it’s an amazing stress reliever, sort of like meditation. Or maybe that’s just me…

One more quick observation: most of you are probably familiar with the naming conventions of IPCC reports. The First Assessment Report was FAR, the second was SAR, and so on, until the acronyms started to repeat themselves, so the Fourth Assessment Report was AR4. They’ll have to follow this alternate convention until the Eighth Annual Report, which will be EAR. Maybe they’ll stick with AR8, but that would be substantially less entertaining.

Learning Experiences











Last time, we talked about the energy budget – the process of radiation coming in from the sun, being absorbed by the Earth, and then emitted as infrared radiation, which we perceive as heat when it hits us. Remember that this outgoing emission of energy is what determines the temperature of the Earth.

So how can the temperature of the Earth be changed? Naturally, there is a lot of year-to-year variation. For example, when the oceans absorb radiation from the sun, they don’t always emit it right away. They will store energy for a long time, and sometimes release lots at once, during El Nino. This kind of internal variability makes the average global temperature very zig-zaggy.

We need to revise the question, then. The question is not about the average global surface temperature – it’s about the amount of energy on the planet. That’s generally how the climate is changed, by increasing or decreasing the amount of energy the Earth emits as infrared radiation, and consequently, the temperature.

There are two ways to do this. The simplest method is to change the amount of incoming energy. By increasing or decreasing the amount of solar radiation that hits the Earth – either directly, by changing the sun’s output, or indirectly, by increasing the albedo or reflectivity of the Earth – the amount of infrared radiation emitted by the surface will also increase or decrease, because incoming has to be equal to outgoing. The change in outgoing radiation will often take a bit of time to catch up to the change in incoming radiation. Until the two reach a new equilibrium, the Earth will warm or cool.

Another way to change the Earth’s temperature is by artificially changing the amount of incoming energy. The same amount of solar radiation reaches the Earth, but when it is absorbed and emitted, some of the emitted infrared energy gets bounced back so the Earth has to absorb and emit it again. By processing the same energy multiple times, the temperature is a lot warmer that it would be without any bouncing. We refer to this bouncing as the “greenhouse effect”, even though greenhouses work in a completely different way, and we will be discussing it a lot more later. By increasing or decreasing the greenhouse effect, the temperature of the Earth will change too.

A change in incoming energy is referred to as a radiative forcing, because it “forces” the Earth’s temperature in a certain way, by a certain amount. It is measured in watts per square meter (W/m2), and it doesn’t take very many watts per square meter to make a big difference in the Earth’s temperature. The resulting change in temperature is called a response.

My favourite analogy to explain forcing and response uses one of the most basic physics equations – F=ma. Mass (m) is constant, so force (F) is proportional to acceleration (a). Applying a forcing to the Earth is just like pushing on a box. If the force is big enough to overcome friction, you get an acceleration – a response.

It’s also very important to use net force, not just any force. If there are two people pushing on the box in different directions with different amounts of force, the acceleration you observe will be equal to the result of those forces combined. Similarly, there are often multiple forcings acting on the climate at once. The sun might be getting slightly dimmer, the albedo might be decreasing, the greenhouse effect might be on the rise. The response of the climate will not match up to any one of those, but the sum of them all together.

Here is a video I made last year, in collaboration with Climate Change Connection, about this very analogy:

In future posts, I will be discussing different forcings in more detail. Stay tuned!