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It seems that every post I write begins with an apology for not writing more. I’ve spent the past few months writing another set of exams (only one more year to go), building and documenting two simple climate models for term projects (much more on that later), and moving to Australia!

This (Northern Hemisphere) summer I have a job at the Climate Change Research Centre at the University of New South Wales in Sydney, which has a close partnership with the UVic Climate Lab (where I worked last summer). I am working with Dr. Katrin Meissner, who primarily studies ocean, carbon cycle, and paleoclimate modelling. We have lots of plans for exciting projects to work on over the next four months.

Australia is an interesting place. Given that it’s nearly 20 hours away by plane, it has a remarkably similar culture to Canada. The weather is much warmer, though (yesterday it dropped down to 15 C and everyone was complaining about the cold) and the food is fantastic. The birds are more colourful (Rainbow Lorikeets are so common that some consider them pests) and the bats are as big as ravens. Best of all, there is an ocean. I think I am going to like it here.

The back gardens of Mayflower, Arkansas aren’t looking too good:

spill

Yes, that’s oil. Canadian oil, no less. You’re welcome.

I’ve heard surprisingly little about this event, which occurred when an Exxon Mobil pipeline ruptured on Friday. It appears that the press have limited access while the cleanup crews are at work. National Geographic had a good piece, though.

Call me cynical, but I think the Canadian media are purposely keeping quiet on this one. It’s a very inconvenient time for a pipeline to burst, given that all levels of government and industry are pushing for Keystone, Northern Gateway, Energy East, etc., etc.

News of this event is largely relying on Mayflower citizens leveraging social media. There’s no way to verify their photos and videos, but they’re striking nonetheless. Here’s a video of the situation on a residential street – note the lack of cleanup crews.

The oil is going straight into the storm drain, the man in the video says, which makes me shudder. I don’t know anything about Mayflower’s stormwater system, but where I live those storm drains are about three steps removed from the Red River. Once oil got in there, I can’t imagine it ever getting out.

I find it puzzling that the negative impacts of pipelines are so often catalogued as “environmentalists’ problems” in the Canadian media – here’s a typical example. In reality, they’re everyone’s problems. Environmentalists (as much as I detest that label) are just the people who realize it. We are not a special interest group; we represent everyone. When it comes to disasters, from short-term spills like the one in Mayflower to millennial-scale impacts like climate change, Canadian oil will affect everyone indiscriminately.

Side note: Sorry I have been so absurdly quiet recently. I am busy building two climate models – just small ones for term projects, but so enjoyable that everything else is getting neglected. I’ll be posting much more on that in about a month.

A Visit to NCAR

Last week I was lucky enough to attend the Second Workshop on Coupling Technologies for Earth System Models, held at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado, USA. I was excited just to visit NCAR, which is one of the top climate research facilities in the world. Not only is it packed full of interesting scientists and great museum displays, but it’s nestled in the Rocky Mountains and so the view from the conference room looks like this:

2013-02-21 13.46.43

Many of the visitors would spend large portions of the coffee breaks just staring out the window…

The conference was focused on couplers – the part of a climate model that ties all the other components (atmosphere, ocean, land, etc.) together. However, the presentations covered (as Rob Jacob put it) “everything that physical scientists don’t care about unless it stops working”. Since I consider myself a physical scientist, this included a lot of concepts I hadn’t thought about before:

  • Parallel processing: Since climate models are so big, it makes sense to multitask by splitting the work over many computer processors. You have to allocate the right number of processors to each component, though: if the atmosphere has too many processors, it will finish its timestep too quickly and sit there waiting until the ocean is done, and vice versa. This is called load balancing, and it gets very tricky as soon as the number of components exceeds two.
  • Scalability: The more processors you use, the faster the model runs, but the speed has diminishing returns. If you double the number of processors, you won’t quite double the speed, particularly if the number of processors exceeds 104 (a setup which is becoming increasingly affordable for large research groups). Historically, the coupler has not been a code bottleneck (limiting factor for model speed), but as the number of processors gets very large, that scenario is changing. We have to figure out the most efficient way to couple many small components together, so that climate model speed can continue to keep up with advances in computer hardware.
  • Standardization: Modelling groups across the world are communicating with each other more and more, and using each other’s code. Currently this requires a lot of modifications, because every climate model has a different structure. Everyone seems to agree that it would be great to have a standard interface that allowed you to plug any combination of components together, but of course everyone has a different idea of what that standard should be.
  • Fortran is still the best language for climate models, believe it or not, because it is the fastest language for the kinds of operations required. If a modern, accessible language like Python could compete based on speed, you can bet that new climate models like MPAS would use it.

I was at the conference with Steve Easterbrook and his new M.Sc. student Daniel Levy, presenting our bubble diagrams of model architecture. (If you haven’t already, read my AGU poster schpiel first, or none of this will make sense!) As interesting and useful as these diagrams are, there were some flaws in our original analysis:

  1. We didn’t use preprocessed code, meaning that each “model” is actually the code base for many different model configurations. So our estimate of model complexity based on line count is biased towards models which are very configurable, but might not actually be very complex. We can fix this by choosing specific configurations of each model (for consistency, the configuration used in CMIP5 or the equivalent EMIC AR5 intercomparison project) and obtaining preprocessed code from the corresponding institutions.
  2. We sorted the code into components (eg atmosphere) and sub-components (eg atmospheric aerosols) based on folder structure, which might not reflect the hierarchy of routines formed at runtime. Some modelling groups keep their files very organized, but often code from different parts of the model was mixed together, and separating it out was very much a judgement call. To fix this, we can sort based on the dependency structure (a massive tree graph showing which routines call which): all the descendants of the atmosphere driver are part of the atmosphere component, and so on.
  3. We made our diagrams in Microsoft PowerPoint, which is quite limited, and didn’t allow us to size the bubbles so their area was perfectly proportional to line count. Instead, we just had to eyeball it. We can fix this by using Adobe Illustrator, which is much more advanced and has this capability.

So far, we’ve repeated the analysis for the UK Met Office Model, version HadGEM2-ES. I created the dependency structure by going manually through every file and making good use of grep, which took hours and hours (although it was a nice, menial way to avoid studying for my courses!). Daniel is going to write a Fortran parser to make the job easier next time around. In the meantime, our HadGEM2-ES diagram is absolutely gorgeous and wonderfully accurate:
HadGEM2-ES
I will post future diagrams as they become available. We think the main use of these diagrams will be as communication tools between scientists, so they are free to use with attribution.

Just a few more weeks of classes, then I can enjoy some full-time research. Now that I’ve had a taste of being a proper scientist, it’s hard to go back!

A Phone Conversation

Me: Hello?
Caller: Hello?
Me: Yes, hello?
Caller: Hi, I’m from the local paper.
Me: Okay. (We get these calls several times a week. It’s getting kind of tiresome.)
Caller: Do you currently receive the paper?
Me: No.
Caller: Would you like to become a subscriber?
Me: No, thank you.
Caller: Well, have you ever read it?
Me: Yes, and that’s why I don’t want to buy it.
Caller: Say again?
Me: I’m not happy with your science coverage.
Caller: Science?
Me: Yes. I’m a scientist and I’m not happy with the quality of science journalism in the paper.
Caller: Well, I didn’t write it.
Me: I know. I’m just telling you why I don’t want to buy it.
Caller: Is it anything in particular? I mean, you say “science”…
Me: Climate science, in particular.
Caller: Climate science.
Me: Yes.
Caller: Was it a specific article?
Me: No, it was a pattern of articles over several years, relating to climate change. I’m a climate scientist and your coverage of this issue was so far off base that I could no longer support the paper.
Caller: Oh.
Me: Thanks for your interest. Please don’t call again.
Caller: My…interest?
End of call

Then and Now

Sometimes I look back to 2010 and wonder how we all got through it. I remember the stomachache I’d get every time I opened a newspaper, wondering what awful lies had been printed about climate science that day. I remember the disdain with which people treated the science I love and the scientists I look up to. 2010 was the year when climate change conspiracy theories went mainstream, and the year when the whole issue was a lump of dread I carried around in my pocket.

Things are easier now. The climate system is in really bad shape (and it can only get worse from here), but somehow I find this fact easier to deal with than the judgement of well-meaning, but highly misinformed and misled, people. Maybe this is because I find human conflict scary but graphs and numbers comforting. Or maybe I am just too good at thinking of model simulations as hypothetical.

In my own way I am in denial, because when I think about my future I always picture a world without climate change.

Regardless, the attacks on our integrity have largely abated, and everything feels so peaceful in comparison. Part of this, of course, has to do with policy: the misinformation campaign “ClimateGate” was clearly timed to derail the Copenhagen talks, the likes of which won’t happen again for another few years. I think there is another factor, though, which will protect us the next time around: the scientists are now officially pissed off.

As scientists, we are shy creatures by nature (remember what I said about human conflict and graphs?) but even we can be provoked. Recall that we have discovered important information that could be vital to the future of our civilization, and yet there are many who seek to discredit us and make sure this information is not taken seriously. When those people go so far as to slander and harass individual researchers, nearly to the point of suicide, they have stepped on all of our toes. We are mad scientists, but not in the cartoon sense.

Now, when deniers attempt to construct a scandal, it doesn’t get off the ground. Scientists are there immediately to set the record straight, and the media realizes it is a non-story. When shady politicians try to press charges against researchers, those researchers hire accomplished lawyers because there is a fund for that now. Geoscience conferences  feature so many communications workshops that you could attend nothing else if you chose to. Scientific societies are publishing handbooks on how to respond if your research is publicly attacked, you face charges of fraud, or you fear for your safety.

I like this new attitude of climate scientists. Forget the old paradigm that scientists should steer clear of political speech and stick to pure research. We didn’t give up our rights as citizens when we decided to be scientists. Maybe 2010 was a necessary evil, because it made us realize that we have a responsibility to fight for truth.

Counting my Blessings

This is the coldest time of year in the Prairies. Below -20 °C it all feels about the same, but the fuel lines in cars freeze more easily, and outdoor sports are no longer safe. We all become grouchy creatures of the indoors for a few months each year. But as much as I hate the extreme cold, I would rather be here than in Australia right now.

A record-breaking, continent-wide heat wave has just wrapped up, and Australia has joined the Arctic in the list of regions where the temperature is so unusually warm that new colours have been added to the map legends. This short-term forecast by the ACCESS model predicts parts of South Australia to reach between 52 and 54 °C on Monday:

For context, the highest temperature ever recorded on Earth was 56.7 °C, in Death Valley during July of 1913. Australia’s coming pretty close.

This heat wave has broken dozens of local records, but the really amazing statistics come from national average daily highs: the highest-ever value at 40.33 °C, on January 7th; and seven days in a row above 39 °C, the most ever, from January 2nd to 8th.

Would this have happened without climate change? It’s a fair question, and (for heat waves at least) one that scientists are starting to tackle – see James Hansen’s methodology that concluded recent heat waves in Texas and Russia were almost certainly the result of climate change.

At any rate, this event suggests that uninformed North Americans who claim “warming is a good thing” haven’t been to Australia.

Here in the northern mid-latitudes (much of Canada and the US, Europe, and the northern half of Asia) our weather is governed by the jet stream. This high-altitude wind current, flowing rapidly from west to east, separates cold Arctic air (to the north) from warmer temperate air (to the south). So on a given day, if you’re north of the jet stream, the weather will probably be cold; if you’re to the south, it will probably be warm; and if the jet stream is passing over you, you’re likely to get rain or snow.

The jet stream isn’t straight, though; it’s rather wavy in the north-south direction, with peaks and troughs. So it’s entirely possible for Calgary to experience a cold spell (sitting in a trough of the jet stream) while Winnipeg, almost directly to the east, has a heat wave (sitting in a peak). The farther north and south these peaks and troughs extend, the more extreme these temperature anomalies tend to be.

Sometimes a large peak or trough will hang around for weeks on end, held in place by certain air pressure patterns. This phenomenon is known as “blocking”, and is often associated with extreme weather. For example, the 2010 heat wave in Russia coincided with a large, stationary, long-lived peak in the polar jet stream. Wildfires, heat stroke, and crop failure ensued. Not a pretty picture.

As climate change adds more energy to the atmosphere, it would be naive to expect all the wind currents to stay exactly the same. Predicting the changes is a complicated business, but a recent study by Jennifer Francis and Stephen Vavrus made headway on the polar jet stream. Using North American and North Atlantic atmospheric reanalyses (models forced with observations rather than a spin-up) from 1979-2010, they found that Arctic amplification – the faster rate at which the Arctic warms, compared to the rest of the world – makes the jet stream slower and wavier. As a result, blocking events become more likely.

Arctic amplification occurs because of the ice-albedo effect: there is more snow and ice available in the Arctic to melt and decrease the albedo of the region. (Faster-than-average warming is not seen in much of Antarctica, because a great deal of thermal inertia is provided to the continent in the form of strong circumpolar wind and ocean currents.) This amplification is particularly strong in autumn and winter.

Now, remembering that atmospheric pressure is directly related to temperature, and pressure decreases with height, warming a region will increase the height at which pressure falls to 500 hPa. (That is, it will raise the 500 hPa “ceiling”.) Below that, the 1000 hPa ceiling doesn’t rise very much, because surface pressure doesn’t usually go much above 1000 hPa anyway. So in total, the vertical portion of the atmosphere that falls between 1000 and 500 hPa becomes thicker as a result of warming.

Since the Arctic is warming faster than the midlatitudes to the south, the temperature difference between these two regions is smaller. Therefore, the difference in 1000-500 hPa thickness is also smaller. Running through a lot of complicated physics equations, this has two main effects:

  1. Winds in the east-west direction (including the jet stream) travel more slowly.
  2. Peaks of the jet stream are pulled farther north, making the current wavier.

Also, both of these effects reinforce each other: slow jet streams tend to be wavier, and wavy jet streams tend to travel more slowly. The correlation between relative 1000-500 hPa thickness and these two effects is not statistically significant in spring, but it is in the other three seasons. Also, melting sea ice and declining snow cover on land are well correlated to relative 1000-500 hPa thickness, which makes sense because these changes are the drivers of Arctic amplification.

Consequently, there is now data to back up the hypothesis that climate change is causing more extreme fall and winter weather in the mid-latitudes, and in both directions: unusual cold as well as unusual heat. Saying that global warming can cause regional cold spells is not a nefarious move by climate scientists in an attempt to make every possible outcome support their theory, as some paranoid pundits have claimed. Rather, it is another step in our understanding of a complex, non-linear system with high regional variability.

Many recent events, such as record snowfalls in the US during the winters of 2009-10 and 2010-11, are consistent with this mechanism – it’s easy to see that they were caused by blocking in the jet stream when Arctic amplification was particularly high. They may or may not have happened anyway, if climate change wasn’t in the picture. However, if this hypothesis endures, we can expect more extreme weather from all sides – hotter, colder, wetter, drier – as climate change continues. Don’t throw away your snow shovels just yet.

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