How I became a scientist

For the first fourteen years of my life, I thought science was boring. As far as I could tell, science was a process of memorising facts: the order of the planets, the names of clouds, the parts of a cell. Sometimes science meant building contraptions out of paper and tape to allow an egg to survive a two-metre fall, and I was really terrible at that sort of thing. So instead I spent all my spare time reading and writing, and decided to be a novelist when I grew up.

This all changed in my first year of secondary school, when I met the periodic table. I don’t know what it says about me that my first spark of interest in science boiled down to “This chart is very nicely organised”. (As anyone who has seen my home library will attest, I really like organising things.) The periodic table quickly acted as a gateway drug to basic physics and chemistry. Science still meant memorising facts, but suddenly they were much more interesting facts.

In the next year of secondary school, maths also became interesting. Until then, maths had been easy to the point of tedium. Most of my time in maths had been spent triple-checking my answers. But now maths was streamed into three different courses, and I chose the most difficult one, and it was wonderful. There is nothing quite as exhilarating as being challenged for the first time.

So now I had a dilemma. I wasn’t so interested in being a novelist any more, and I really liked maths and science. But at my school, all the best maths and science students went on to be doctors. Whereas I was so squeamish about medical things that I would hide from the television whenever my older sisters watched ER. I was also something of a hypochondriac. These are not qualities which are prized by the medical profession.

It was very important for a teenager in the early 2000s to know exactly what they wanted to be when they grew up, so I worried about this a lot. For a while I tried to convince myself to be a doctor anyway. I had no interest in dentistry or pharmacy, which were the other options presented to me. I seriously considered becoming an optometrist, but the faint possibility that I might have to deal with an eyeball that had popped out of someone’s head was enough to turn me against the idea. Some of the strong maths and science students at my school had gone on to become engineers, but I thought that probably involved the same sorts of skills as building egg-protecting devices.

At the same time as this inner turmoil, something else was going on: I was becoming interested in the environment. This was mostly a result of peer pressure. There was a very cool group of students, most in the year above mine, who had started an environmental club. Once a week, I came to school extra early in the morning to hang out with them at club meetings. And we had long and fascinating discussions, ranging from the best way to save water in the school’s bathrooms to environmental policy in the Canadian government.

I started to wonder if there was a career path which connected the environment with maths and science. I went on my school’s career-matching website to find out, and filled in the questionnaire. The website recommended I become a chemist who tested water samples from industrial plants to make sure they weren’t polluting the local environment. I wasn’t particularly inspired by this idea. I remember reading over all the other careers on the website, but I don’t remember seeing anything about academia or scientific research. And, I mean, fair enough. Given the massive oversupply of PhDs in the modern world, I understand why schools wouldn’t want to funnel students in that direction.

Meanwhile, back in the environmental club, names were being drawn out of a hat. One of the local universities was holding a climate change conference for secondary school students, and my school had been allocated three places. I was one of the lucky ones, and a few weeks later I rode the bus to the city centre for the conference.

The first presentation was called “The Science of Climate Change” and it was delivered by Danny Blair, a climatologist at the university. He talked about many different things and all of them were fascinating and I scrawled tiny notes in a tiny notebook as quickly as I could. But I particularly remember him explaining how scientists can use ice cores to figure out the temperature from hundreds of thousands of years ago. In short, oxygen has different isotopes, some of which are heavier than others. When the oxygen atoms join H2O molecules, they form “heavy water” and “light water”. Heavy water needs more energy, and therefore a higher temperature, to evaporate from the ocean and eventually fall as precipitation somewhere else. So by measuring the ratio of heavy water to light water in the ice cores, you can figure out what the global temperature was when each layer of snow fell.

Sitting there with my tiny notebook, I thought this was just the most fascinating thing I’d ever heard. This was the very first time I’d seen a practical application of the periodic table which brought me joy and excitement, rather than despair that I might end up testing water samples for the rest of my life. And it slowly dawned on me that this job called “scientist” basically meant you could study whatever you found interesting, and get paid to do so. “Right then,” I thought, “I’ll be a scientist.”

It’s eleven years later and I still haven’t changed my mind. I didn’t become an ice core scientist, but I did end up studying a different part of the climate system which I found even more interesting. Academia is not perfect, but there is no other way I’d rather spend my working life. Far from memorising an endless stream of facts, it turns out that science is full of creativity and solving mysteries. My work is always changing and growing, and I never get bored.

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Climate change and compassion fatigue

I’m a climate scientist, and I don’t worry about climate change very much. I think about it every day, but I don’t let it in. To me climate change is a fascinating math problem, a symphony unfolding both slowly and quickly before our very eyes. The consequences of this math problem, for myself and my family and our future, I keep locked in a tiny box in my brain. The box rarely gets opened.

The latest IPCC special report tells the world what I and all of my colleagues have known for years: we’re seriously running out of time. In order to keep climate change in the category of “expensive inconvenience” rather than “civilisation destroyer”, we’re going to have to decarbonise the global economy in less time than many of the people reading this have been alive. But given the priorities of most of the world’s governments, it seems uncomfortably plausible that we’ll be facing the sort of post-apocalyptic wasteland I’ve only ever seen in movies. Will the rich and privileged countries be able to buy their way out of this crisis? Maybe. But maybe not.

I know all this. I’ve known it for years and it’s why I chose the career that I did. It’s the backdrop to my every working day. But I can’t seem to imagine my future intersecting with this future. I can’t picture myself or my family as part of the movie, only as part of the audience. It feels deeply intangible, like my own death.

Instead I surround myself with the comforting minutia of academic life. I worry about small things, like how I’m going to fix the latest problem with my model, and slightly larger things, like what I’m going to do when my contract runs out and whether I will ever get a permanent job. But mostly I just really enjoy studying the disaster. An ice sheet which is falling apart is far more interesting than a stable ice sheet, and I feel privileged to have access to such a good math problem. So I work until my brain feels like it might turn into liquid and slide out of my ears, then I cycle home in the mist and eat Cornish pasties on the couch with my husband while watching the BBC. In so many ways, I love this life. And I don’t worry about climate change, I don’t open that box, for months at a time.

“Compassion fatigue” is a term used to describe healthcare professionals who become desensitised to tragedy and suffering, and lose the ability to empathise with their patients. It begins as a coping strategy, because fully absorbing the emotional impact of such harrowing work would eventually make it impossible to get up in the morning. I think I have compassion fatigue with climate change. The more I study it, the less I actually think about it. The scarier it gets, the less I seem to care.

And maybe this is okay. Maybe compartmentalisation is the healthiest response for those of us close to the issue. Accept the problem, fully let it in, and decide what you’re going to do to help. Then lock up that box in your brain and get on with your piece of the fight. Find joy in this wherever you can. Open up the box once in a while, to remind yourself of your motivation. But for the most part ignore the big picture and keep yourself healthy and happy so that you can keep going. Even if this, in and of itself, is a form of denial.

The silver lining of fake news

What exciting times we live in! The UK is stockpiling food and medicine as it charges willingly into a catastrophe of its own choosing. The next Australian prime minister is likely to be a man who has committed crimes against humanity. And America has descended so far into dystopia that it can’t even be summed up in one pithy sentence.

I spend a lot of time wondering how future generations will look back upon this period in history. Will there be memorial museums on Nauru and at the US-Mexican border, pledging Never Again? Will the UK’s years in the European Union be heralded as a golden age for the country? And what will the history books say about Donald Trump?

When I imagine these future historians, giving their seminars and writing their books and assigning their students essays, there is one overarching theme I’m sure they will focus on. One puzzling phenomenon is at the root of so much of the madness we face today. Our future historian might title such a seminar “Widespread public rejection of facts in the early 21st century”. Or, if you wish to be so crass, “Fake News”. A distrust of experts, and of the very idea of facts, now permeates almost every part of public life – from science to economics to medicine to politics.

Climate change used to be the sole target of this. I’ve been wrestling with fake news on climate change for more than ten years now. And I used to get so frustrated, because my friends and family would read dodgy articles in respectable newspapers written by fossil fuel executives and believe them. Or at least, consider them. Reasonable people heard debate on this issue and assumed there must be some merit to it. “Both sides of the climate change debate have good points to make,” they would reasonably say.

It’s different now. Denialism has spread into so many topics, and received so much attention, that reasonable people are now well aware of its existence. “You guys, did you know that there are people who don’t believe in facts?!” is the gist of so many dinner conversations around the world these days. And the exhausted climate scientists sit back, twirl their spaghetti around their fork, and say “Yes, yes we know. So you’ve finally caught on.”

This is the weird silver lining of fake news: reasonable people now take climate change more seriously. When they read bogus stories about global cooling and natural cycles and scientific conspiracies, they just say “Aha! These are the people who don’t believe in facts.” It’s like the dystopia of 2018 has inoculated many of us against denialism. More and more people now understand and accept the science of climate change, even while those who don’t grow louder and more desperate. Climate change deniers still exist, but it seems that their audience is shrinking.

(Of course, this doesn’t mean we’re actually doing anything about climate change.)

***

PS I am now Twittering, for those of you who are so inclined.

Future projections of Antarctic ice shelf melting

Climate change will increase ice shelf melt rates around Antarctica. That’s the not-very-surprising conclusion of my latest modelling study, done in collaboration with both Australian and German researchers, which was just published in Journal of Climate. Here’s the less intuitive result: much of the projected increase in melt rates is actually linked to a decrease in sea ice formation.

That’s a lot of different kinds of ice, so let’s back up a bit. Sea ice is just frozen seawater. But ice shelves (as well as ice sheets and icebergs) are originally formed of snow. Snow falls on the Antarctic continent, and over many years compacts into a system of interconnected glaciers that we call an ice sheet. These glaciers flow downhill towards the coast. If they hit the coast and keep going, floating on the ocean surface, the floating bits are called ice shelves. Sometimes the edges of ice shelves will break off and form icebergs, but they don’t really come into this story.

Climate models don’t typically include ice sheets, or ice shelves, or icebergs. This is one reason why projections of sea level rise are so uncertain. But some standalone ocean models do include ice shelves. At least, they include the little pockets of ocean beneath the ice shelves – we call them ice shelf cavities – and can simulate the melting and refreezing that happens on the ice shelf base.

We took one of these ocean/ice-shelf models and forced it with the atmospheric output of regular climate models, which periodically make projections of climate change from now until the end of the century. We completed four different simulations, consisting of two different greenhouse gas emissions scenarios (“Representative Concentration Pathways” or RCPs) and two different choices of climate model (“ACCESS 1.0”, or “MMM” for the multi-model mean). Each simulation required 896 processors on the supercomputer in Canberra. By comparison, your laptop or desktop computer probably has about 4 processors. These are pretty sizable models!

In every simulation, and in every region of Antarctica, ice shelf melting increased over the 21st century. The total increase ranged from 41% to 129% depending on the scenario. The largest increases occurred in the Amundsen Sea region, marked with red circles in the maps below, which happens to be the region exhibiting the most severe melting in recent observations. In the most extreme scenario, ice shelf melting in this region nearly quadrupled.

Percent change in ice shelf melting, caused by the ocean, during the four future projections. The values are shown for all of Antarctica (written on the centre of the continent) as well as split up into eight sectors (colour-coded, written inside the circles). Figure 3 of Naughten et al., 2018, © American Meteorological Society.

So what processes were causing this melting? This is where the sea ice comes in. When sea ice forms, it spits out most of the salt from the seawater (brine rejection), leaving the remaining water saltier than before. Salty water is denser than fresh water, so it sinks. This drives a lot of vertical mixing, and the heat from warmer, deeper water is lost to the atmosphere. The ocean surrounding Antarctica is unusual in that the deep water is generally warmer than the surface water. We call this warm, deep water Circumpolar Deep Water, and it’s currently the biggest threat to the Antarctic Ice Sheet. (I say “warm” – it’s only about 1°C, so you wouldn’t want to go swimming in it, but it’s plenty warm enough to melt ice.)

In our simulations, warming winters caused a decrease in sea ice formation. So there was less brine rejection, causing fresher surface waters, causing less vertical mixing, and the warmth of Circumpolar Deep Water was no longer lost to the atmosphere. As a result, ocean temperatures near the bottom of the Amundsen Sea increased. This better-preserved Circumpolar Deep Water found its way into ice shelf cavities, causing large increases in melting.

Slices through the Amundsen Sea – you’re looking at the ocean sideways, like a slice of birthday cake, so you can see the vertical structure. Temperature is shown on the top row (blue is cold, red is warm); salinity is shown on the bottom row (blue is fresh, red is salty). Conditions at the beginning of the simulation are shown in the left 2 panels, and conditions at the end of the simulation are shown in the right 2 panels. At the beginning of the simulation, notice how the warm, salty Circumpolar Deep Water rises onto the continental shelf from the north (right side of each panel), but it gets cooler and fresher as it travels south (towards the left) due to vertical mixing. At the end of the simulation, the surface water has freshened and the vertical mixing has weakened, so the warmth of the Circumpolar Deep Water is preserved. Figure 8 of Naughten et al., 2018, © American Meteorological Society.

This link between weakened sea ice formation and increased ice shelf melting has troubling implications for sea level rise. The next step is to simulate the sea level rise itself, which requires some model development. Ocean models like the one we used for this study have to assume that ice shelf geometry stays constant, so no matter how much ice shelf melting the model simulates, the ice shelves aren’t allowed to thin or collapse. Basically, this design assumes that any ocean-driven melting is exactly compensated by the flow of the upstream glacier such that ice shelf geometry remains constant.

Of course this is not a good assumption, because we’re observing ice shelves thinning all over the place, and a few have even collapsed. But removing this assumption would necessitate coupling with an ice sheet model, which presents major engineering challenges. We’re working on it – at least ten different research groups around the world – and over the next few years, fully coupled ice-sheet/ocean models should be ready to use for the most reliable sea level rise projections yet.

A modified version of this post appeared on the EGU Cryospheric Sciences Blog.

Interview at Forecast

I’ve just given an interview at the Forecast podcast, hosted by Nature’s climate change editor, Michael White. Head over to the Forecast website to check it out.

What I love about Forecast is that it interviews climate scientists as fully-rounded human beings, rather than fact-generating robots. The humanisation of scientists is so important for science communication. If the audience feels like they can relate to a scientist, they’re more likely to trust them and take an interest in what they say. Michael does an exemplary job of this, because his interviews aren’t just limited to reporting the results of recent studies. He also asks his guests how that research was done, how they became a scientist in the first place, and what life is like as an academic. These are the sorts of conversations scientists actually have with each other, and it’s refreshing and fascinating to see them captured in online media.

I approached Forecast with an idea for a podcast I’d had rattling around in my brain for months. I am a person who stutters. I don’t think I’ve ever mentioned it on this blog before, but there you have it. When I’m talking my throat likes to close up and block the words from coming out. This is frustrating.

In academia these days there’s quite a lot of discussion about equity and diversity. Usually this is around gender, sometimes ethnicity, sometimes sexual orientation. But I’ve yet to hear any discussion about disabilities. Here I am with this very obvious disability (at least, it’s obvious every time I open my mouth) and I’m sure my colleagues have questions about it, but everyone is too polite to ask.

Those who do say anything – usually my closest friends, and only after I bring it up – generally say something along the lines of “you’re so brave to be a scientist anyway and not let this stop you”. I was really taken aback the first time I heard this, because I’d never even thought about it that way. My disability has never factored into my career choices for a second. There are very few jobs that don’t require some amount of speaking, and I like science and am good at science, so why would I do anything else?

But this got me thinking. About 1% of the population stutters (mostly men, I’m the unlucky exception) and surely there are some aspiring scientists in there. Maybe they’re not all as stubborn as I am. Maybe it would help them to hear from someone who has made it work.

So, there you have it. Hopefully this podcast helps somebody. You also get to hear about ice-sheet/ocean interactions, model development, my new postdoc, and all the different Commonwealth countries I have lived in.

On model development, and sanity

When I was a brand-new PhD student, full of innocence and optimism, I loved solving bugs. I loved the challenge of it and the rush I felt when I succeeded. I knew that if I threw all of my energy at a bug, I could solve it in two days, three days tops. I was full of confidence and hope. I had absolutely no idea what I was in for.

Now I am in the final days of my PhD, slightly jaded and a bit cynical, and I still love solving bugs. I love slowly untangling the long chain of cause and effect that is making my model do something weird. I love methodically ruling out possible sources of the problem until I eventually have a breakthrough. I am still full of confidence and hope. But it’s been a long road for me to come around full circle like this.

As part of my PhD, I took a long journey into the world of model coupling. This basically consisted of taking an ocean model and a sea ice model and bashing them together until they got along. The coupling code had already been written by the Norwegian Meteorological Institute for Arctic domains, but it was my job to adapt the model for an Antarctic domain with ice shelf cavities, and to help the master development team find and fix any problems in their beta code. The goal was to develop a model configuration that was sufficiently realistic for published simulations, to help us understand processes on the Antarctic continental shelf and in ice shelf cavities. Spoiler alert, I succeeded. (Paper #1! Paper #2!) But this outcome was far from obvious for most of my PhD. I spent about two and a half years gripped by the fear that my model would never be good enough, that I would never have any publishable results, that my entire PhD would be a failure, etc., etc. My wonderful supervisor insisted that she had absolute confidence in my success at every step along the way. I was afraid to believe her.

Model coupling is a shitfight, and anyone who tells you otherwise has never tried it. There is a big difference between a model that compiles and runs with no errors, and a model that produces results in the same galaxy as reality. For quite a while my model output did seem to be from another galaxy. Transport through Drake Passage – how we measure the strongest ocean current in the world – was going backwards. In a few model cells near the Antarctic coast, sea ice grew and grew and grew until it was more than a kilometre thick. Full-depth convection, from the ocean surface to the seafloor, was active through most of the Southern Ocean. Sea ice refused to export from the continental shelf, where it got thicker and thicker and older and older, while completely disappearing offshore.

How did I fix these bugs? Slowly. Carefully. Methodically. And once in a while, frantically trying everything I could think of at the same time, flailing in all directions. (Sometimes this works! But not usually.) My colleagues (who seem to regard me as The Fixer of Bugs) sometimes ask what my strategy is, if there is a fixed framework they can follow to solve bugs of their own. But I don’t really have a strategy. It’s different every time.

It’s very hard to switch off from model development, as the bugs sit in the back of your brain and follow you around day and night. Sometimes this constant, low-level mulling-over is helpful – the solutions to several bugs have come to me while in the shower, or walking to the shops, or sitting in a lecture theatre waiting for a seminar to start. But usually bug-brain just gets in the way and prevents you from fully relaxing. I remember one night when I didn’t sleep a wink because every time I closed my eyes all I could see were contour plots of sea ice concentration. Another day, at the pub with my colleagues to celebrate a friend’s PhD submission, I stirred my mojito with a straw and thought about stratification of Southern Ocean water masses.

***

When you spend all your time working towards a goal, you start to glorify the way you will feel when that goal is reached. The Day When This Bug Is Fixed. Or even better, The Day When All The Bugs Are Fixed. The clouds will part, and the angels will sing, and the happiness you feel will far outweigh all the strife and struggle it took to get there.

I’m going to spoil it for you: that’s not how it feels. That is just a fiction we tell ourselves to get through the difficult days. When my model was finally “good enough”, I didn’t really feel anything. It’s like when your paper is finally accepted after many rounds of peer review and you’re so tired of the whole thing that you’re just happy to see the back of it. Another item checked off the list. Time to move on to the next project. And the nihilism descends.

But here’s the most important thing. I regret nothing. Model development has been painful and difficult and all-consuming, but it’s also one of the most worthwhile and strangely joyful experiences I’ve had in my life. (What is it that mothers say about childbirth?) It’s been fantastic for my career, despite the initial dry spell in publications, because it turns out that employers love to hire model developers. And I think I’ve come out of it tough as nails because the stress of assembling a PhD thesis has been downright relaxing in comparison. Most importantly, model development is fun. I can’t say that enough times. Model development is FUN.

***

A few months ago I visited one of our partner labs for the last time. I felt like a celebrity. Now that I had results, everyone wanted to talk to me. “If you would like to arrange a meeting with Kaitlin, please contact her directly,” the group email said, just like if I were a visiting professor.

I had a meeting with a PhD student who was in the second year of a model development project. “How are you doing?” I asked, with a knowing gaze like a war-weary soldier.

“I’m doing okay,” he said bravely. “I’ve started meditating.” So he had reached the meditation stage. That was a bad sign.

“Try not to worry,” I said. “It gets better, and it will all work out somehow in the end. Would you like to hear about the kinds of bugs I was dealing with when I was in my second year?”

I like to think I gave him hope.