Wednesday, September 16, 2015

Dr. Lisa Borland on Her Journey from the Purity of the Study of Natural Systems to Fascination with Financial Markets

Dr. Lisa Borland is an econophysicist working at a private company, publishing in academic journals, and lecturing at Stanford University. She gave a wonderfully engaging telling of her personal journey in our Alumni Seminar Series this spring, a journey that covers Jamaica, Stockholm, Berlin, Stuttgart, Berkeley, and Rio de Janeiro, and a similar amount of intellectual territory as well.

Title: Having Your Cake and Eating it Too

Abstract: Physics opens up the doors to many other fields, but sometimes we are afraid to leave academia. We love doing research and we feel that moving away from pure physics will be like giving up our dreams. I’d like to share a bit of my personal journey, and hopefully give useful tips and inspiration about how to make the best of both worlds (finance and academia) and find a balance that can be extremely fulfilling.

We pick up the transcript here immediately after her introduction by Professor Jim Crutchfield.

So it's a great pleasure to be here, and I'm really excited, except I'm used to giving academic talks. So this is kind of different. But to segue off of something Jim said, we met at this conference in Corsica. It was I think 20 years ago. Or maybe 22 years ago, actually. And the title of the conference was called "From Statistical Physics to Statistical Inference, and Back Again."

And now, when I was just remembering the title of that conference; it kind of sums up my career. And it sums up the commonalities of physics to finance, which has a lot of inference and prediction involved. It has different aspects, but that's one aspect. And it also shows you the interdisciplinary areas to which a physics education can take you. 

The title of my talk is "From Physics to Finance: Having Your Cake and Eating It Too." And the reason I'm calling it that is because I've had to make many choices. Choices because of life situations, having kids, or also graduating at a time where it was hard to get a job in pure physics, trying to find alternatives. So I am trying to show you that it is actually possible to make choices and find a balance in your life, where you can have the best of two worlds, in this case an industry job -- a job at a real company, making maybe better money, and dealing with real world problems; but also having an academic career, where you can still publish papers. I mean, I'm lecturing at Stanford; I'm teaching, and I'm at a company.

So I'm going to take you along the path of how I got there and give you some practical tips. And also make you excited a little bit about using your physics background to do something outside of physics. And not consider that the end of the world, but rather as an inspiration to become interdisciplinary. So when I write down my CV here in bullets it looks, you know, straightforward: bachelor in physics in Stockholm. I was actually born in Jamaica, but we had to kind of flee at some point and I ended up in Stockholm because my mother is Swedish, but that's another long story. Not going to go into that part of it, and instead we're going to pretend that it's fine and that I'm doing my Bachelor's in Physics in Stockholm.

And then I moved to Berlin and continued my education there, and then my PhD. Then I did postdocs in Berkeley with Jim and in Rio de Janeiro with Professor Constantino Tsallis who works a lot on non-extensive thermodynamics. And then suddenly I'm at a hedge fund in San Francisco and suddenly my whole path has changed. But I want to point out to you that even moving from the first step to the second step to the third step and so forth: when you're an undergrad -- and I saw in the room that many of you are undergrads in physics -- it's not clear to you how this is actually going to happen. You know, "Where am I going to do my next thing and how is that going to work?" And sometimes there is a conception that there is a boilerplate way of doing this, like "My CV has to be perfect; I have to have the best grades competing with a whole bunch of people." But I'm going to show you that there are alternative ways of getting to where you want to be. And the only common part, or what you need to have, is a real passion. The main thing I can advise you right now at this stage is to know that you really want to do this. And if you just follow that, there are different ways to take you to where you want to go.

"...Sometimes there is a conception that there is a boilerplate way of doing this, like "My CV has to be perfect; I have to have the best grades competing with a whole bunch of people." But I'm going to show you that there are alternative ways of getting to where you want to be."

The first part is going to be about my own path. So when I was doing my bachelor's in physics -- and why I got interested in physics is I was always interested in math and physics. I loved looking at nature, observing the interactions and dynamics of things I saw around me. I felt very strongly about doing something that would lead to some kind of profound understanding of what's around me, of nature, of creation, of life, of interactions. I scoffed at, for example, my sister, who went into economics and law. That to me was man-made and nothing of interest; it had to be this pure philosophical mathematical thing. So I felt that passion but I had no clue: "Is this ever going to feed me? Where is this going to go?" I really had very little guidance. But I felt that inside me.

But Stockholm’s university became a little too small. It's a small university; after you've done a few years of courses there weren't that many exciting ones to choose from, and I happened upon Berlin on a vacation one year. It was the Cold War; the Wall was right there, and it felt very, very real. So I was mainly attracted to the city, but then I also realized that there's a great history of physics in Berlin. Einstein was there, and many, many famous physicists from the early days of quantum mechanics all studied in Berlin.

So I went out to visit the university and the Max Planck Institute, which is a big research institute; they have them in many different cities in Germany, and I was just fascinated by the atmosphere. But I had no clue how to actually move from Stockholm to the Max Planck Institute. So I basically just went there and knocked on the door of the group and said, "Hi, this looks really cool, and I am doing physics and I would love to find a way of getting involved." And they looked at me and said "Well, sure." And they were so taken off guard. But I went back to Stockholm and told people in Stockholm, "I really want to do my last year in Berlin. And I'm setting up this thing with the Max Planck Institute." And they were like, "Whoa, where's that coming from?"

And it actually worked. So I moved to Berlin. And it was really easy -- I didn't really even know German that well; I knew Swedish, but physics is all math, right, so you don't really need language. So I learned German while doing physics and got the scholarship; everything was paid for.

The German physicists you interacted with, I imagine their English was quite good.

Their English was quite good. I was also taking classes. At the Institute, where I was doing research, everyone spoke English. But at the university, I was doing my last year there, everything was in German. I had switched to the German system which was not the same as the Swedish one. The German system is different, in those days especially. You do a bachelor's, then you do two years of what's called a Diplom. It has more research than a master's. You do one to two years of research and you write a thesis, but it's not a PhD. So that thesis work I was doing at the Max Planck institute. But I still was doing classes at the university. But opposed to most of the other German students, I was getting paid by the Max Planck Institute. Simply because I went there and said "I want to do this, and I need this," and they realized I needed a scholarship. And then the people in Stockholm from the physics department came to Berlin to assess the education and equate it because I had to somehow patch together my Swedish degree with the German degree in order to move forward.

I'm really saying, if you really want to do it, just knock on the door; people are people. And it's easier sometimes, I think. People feel they have to send this perfect front, perhaps in an email of a CV. But when we're hiring people, that kind of thing can go in junk mail. In contrast, when somebody really does something just to stand out a little bit or show a real interest, that helps a lot. I'm not saying you should all knock on a door, but you can pick up a phone and call, or try to not get stuck in the human resources part of a bureaucracy if you can help it. That was just my advice then.

"If you really want to do it, just knock on the door; people are people."

So I moved to Berlin and finished my diploma and all went really well. And while I was there I got interested more and more in the dynamics of complex systems and self-organization; the field that Prof. Hermann Haken in Stuttgart had founded. So again, I actually went to a professor in Berlin at the university who had given a seminar on that topic. And I had an idea for a PhD thesis. I went to him and I said "I really want to do my thesis on this." And I had kind of a sketch. And he said, "Oh that's not a good idea; I'm not going to support that." And I believed that it was a good idea; I wasn't going to take "no" for an answer. And this is part of the naivety of being young, right? You believe; I believed in it. So I took a train to Stuttgart, which is where Professor Haken was, having called his secretary and made an appointment for office hours. And this is in Germany; he's this bearded gentleman, very bureaucratic. And I knocked on the door and he opens and says, "Oh what can I do for you?" And then I started getting a little nervous, but he sat there; he was very nice, and I explained for him what I wanted to do for my thesis. And he didn't say a word. I was feeling, you know, "Oh my God!" And then he said, "You know what?" And he opened his drawer and pulled out a pre-print, and he said, "I've just done that. Do you want to come here and work with me over the summer?" And I thought, "Okay!"

So I went to Berlin all excited, packed my bags, went to Stuttgart for the summer, worked with some of his students. It was really fun. But then I really wanted him to take me on as a PhD student. And he was very, very hesitant and it turned out he had never had a female student. And in Germany, when you're a PhD student, you share offices with somebody, so it was males, and he didn't want to put me with another male. He wanted me in my own office. So he couldn't take me until he got a free office. And that was what the problem was. [Laughs]. I'm like, "Okay..." and I'm back to Berlin and did some more research there. This is all very patchwork; I'm working on different topics now. I've done my diploma, I'm working on something in Berlin; I've been to Stuttgart, I'm really just wanting to return there. And then one day he picks up the phone a few months later and says, "Office is free, you can come."

So then I moved to Stuttgart and had a really great time. It was lots of fun.

Your own office?

My own office. Actually, another professor in the physics department got a female student, so she and I eventually shared. But I had a great office. It was really big, and I had a hibiscus flower in the window; it was nice.

I worked a lot. Now Professor Haken works on the theory of complex systems and nonlinear thermodynamics, etc., and I worked a lot on stochastic equations and dynamics, trying to explore certain areas of physics using that kind of framework. And this is when I met Jim at that conference about statistical inference in physics. And so the next step, I take -- you see here on my C.V. -- was to do a  postdoc in Berkeley for three years, and then I actually met my ex-husband there at the physics department and had a daughter.

So now we suddenly had the two-body problem, because remember at this time we were all lucky to have postdocs because it was a time when nobody was hiring and there was very little funding going around in Physics.

What year was this?

I graduated in 1993 with my degree, and this was 93-96. It's kind of just post-Cold War: no jobs, people are doing extended postdocs: postoc after postdoc after postdoc. You remember those days.

Even at UC, there was no hiring.

There was no hiring; it was pretty hard. And we were two people now, with PhDs in physics and a small child. But I had become more and more interested in statistical physics and novel approaches and I was starting to read papers by somebody called Professor Constantino Tsallis. I don't know if people know of him here -- he was at the Santa Fe Institute for a few years after that. But he basically works on statistical systems that have long-range interactions and memory. So you're going beyond Boltzmann statistics which is more suitable to  Markovian problems really. Nonextensive statistics can describe a more extended class of systems. You know, exotic things like levy flights and fat tails, and things that me with my stochastic equation interest I was interested in.

I was very lucky to get a grant from the NSF to go to Rio for two years. So this is now funded by the US -- to go to Rio for two years. And my ex-husband was lucky to get a grant in Brazil from a Brazilian university, so we were able to solve the two-body problem and go there. And that was a very productive time; I mean, I published tons of papers, it was really fun, and I had a son, also. It was very productive. [Laughs].

There we are in Rio. I'm getting my US grant, which wasn't a lot, but it was a lot then and there. And everybody loved us, and so they offered us jobs. The way it works in Brazil is they tailor a competition to your needs. It's called a concurso. So they'll open up a position here at the physics department and the person has to know stochastic calculus, be interested in Levy flights; it's tailored. And then you compete with other candidates. But you have a high chance to win.

So they were setting this all up for us. Everything was great. The only thing is, the salaries were really low. And when I say low, what I mean is suddenly I'm sitting there pregnant, with this family of four. We were paying  $1500 dollars to rent an apartment and the salary that we were going to get was $2000. And then day care was $600. There's nothing left.

That's where I'm sitting. I'm pregnant; I have a two-year-old; I have this great offer. And you get tenure immediately after the concurso; it's for life. But we're going to be starving. What am I going to do? Up until that time I guess I had already been kind of selfish and driven by what I wanted to do in physics, and this is fun, and so forth, and suddenly you start to think, "I have a family to support." So I made a very tough decision, and that was to try to get a job outside of academia. So sitting in Rio now, I did apply for jobs in the US, and it was really hard. That's one thing I would advise you not to do: it's actually hard -- especially for me because I did my PhD in Germany, postdoc in Berkeley then Brazil -- it was hard for me to get an inside connection in the US at a university. I think it's easier if you do your PhD here and there's connections; there's some politics involved. So that wasn't really an option.

Everyone, when I was giving a talk, would say that my equations and what I was working on would fit perfectly to describe the dynamics of stock returns. And you know me, scoffing at it. But quite interestingly while I was in Brazil, at that point -- this is about, again, 15 years ago -- lots of data started being collected of tick-by-tick transaction data from financial markets, which hadn't been available before. And so suddenly one had access to really interesting datasets to look at, and people from physics started being interested in analyzing this data. It's kind of like in physics: you run an experiment and you look at the empirical results, and you analyze it. At that time point people from physics started looking at this data and analyzing it from the point of view of, "I'm running an experiment. What can I uncover about the underlying dynamics or universal properties of these datasets?"

And so I started getting interested in that because I noticed that the distributions and the dynamics seemed to fit very well with the type of stochastic processes I was working on in Brazil. So it wasn't too far-fetched to move in that direction. I was interested in an academic point of view, but the idea of actually leaving academia and going to work at a company -- I thought, "They won't let me do the academic research on this dataset; I'll have to sit there programming business models or some financial application." But because I was pregnant and needed to find some way, I submitted my resume to a hedge fund in San Francisco where I knew a physicist who was already working. And I flew to the interview and actually showed them what I was telling you about before: some of my ideas and others' ideas about how to use physics to understand these datasets. Because people inside the financial world weren't really aware of all these ideas. This was a time point where there was a real separation between the industry finance and what the physicists or academics were doing. But when I presented these ideas in the interview, they were very interested and I got the job.

And I was really lucky because the company I was working with had ex-Berkeley PhDs from different fields: operations research, physics, etc. and even though we actually had to make money and do stuff which turned into a product or a trading application, there was an intellectual curiosity just because of the background of these people. So when I came there and had these ideas, I managed to create a small little group in the company and I was allowed to spend about fifty percent of my time doing academic-type research as long as I also did my other jobs.

And ironically, my big fear at that point was I had been so driven by physics and understanding the truths and scoffing at all these man-made things, I was crushed in my heart. I felt like, “I'm a failure; I'm doing this because I need to make money to support my family. But I'm a failure to my true goals." That's what I thought. Also because inside the academic world, especially maybe it's the German culture, there's kind of this snobbism about "I'm in academia." And I had that in me. But I must tell you that lasted about five minutes. As soon as I got there I realized that people actually cared more about my work and about related questions; people were much more engaged. Like in physics I published papers which maybe weren't the best but they were okay and they had like five citations, ten? Suddenly here I'm publishing papers and getting hundreds of citations and lots of interest and people are engaged and I don't know if it's because people care about money, so they were engaged that way? But I certainly did not lose -- I rather gained -- by making that step outside of academia into industry, but still keeping an academic type of presence.

"[At the hedge fund]. . . I realized that people actually cared more about my work and about related questions; people were much more engaged."

This is just an example: I submitted a paper to PRL with my company name; you know, it's no Princeton affiliation. And it got accepted because they liked what it was. I had always used to think I have to be at a university in order to submit papers, right? But I just started publishing on my own, or with collaborators from wherever I was; my home address: "Here I am." And that's fine; that actually works.

So that was in this phase of my life which was really quite nice. I applied lots of techniques from physics to long-standing problems in finance and in doing so attracted interesting collaborations with people globally from other fields. People called it "econophysics" -- that's the term that is used. I mentioned to you before the large datasets that were coming in about fifteen years ago when physicists were using their techniques to analyze -- that became coined as econophysics. And there are a few famous people who are known for this. So I was kind of working with people in that field.

Then my third child was born -- she's sitting back there now -- and I haven't really emphasized much about the kids part, but I did put it here, because I see there are a few women in the audience and I had to also make some of these choices -- as I said before, it was because of family, and because I had kids. I think it's true for men and women: when you have family your priorities change, and so you have to sometimes make some tough choices. But again, you can always find a way to make it work, I think. For example, I couldn't leave her anywhere today and I brought her here; that's fine. It's not like you don't have to do stuff because you have a child, if you can work around it. I mean it's not always easy, but she's been with me to Brazil, South Africa, Germany, New York about ten times, and I've always just had babysitters, or friends, or organizers of conferences to help watch her. It's hard, but it's not impossible.

"I think it's true for men and women: when you have family your priorities change, and so you have to sometimes make some tough choices. But again, you can always find a way to make it work. . ."

Anyway, for various reasons, this company, which was about 12 years of my life, a great period, ended and I went to work with a couple of startups, in Silicon Valley also doing things related to finance and trading: high-frequency foreign exchange trading and designing software that can connect an over-the-counter market for trading in foreign exchange markets, which was fun. And also throughout this whole time I had established relationships with Stanford because already here I was invited to give talks at Stanford and invited to collaborate with a professor there helping to teach the students and do projects courses with them. And as time went on they offered me my own lectureship, which I have now. So in spring semester I teach there. And when I was down in Silicon Valley I fostered those relationships. And they like that. Stanford loves having industry partners. Because then their students have a place to get hired and they're good connections, money can come in, etc. So I was in that sweet spot where I had a hand in both places.

And then right now I'm also working at another company where I'm the co-Portfolio Manager - -- down in Los Angeles -- where we invest in quantitative strategies. I'm not going to go too much into that. I'm also teaching at Stanford and still doing research and giving talks and so forth. So that's the personal story. And in general, I really feel that a physics undergrad, but especially a PhD, prepares you for anything, for so many things. Because any quantitative field, but also just the process of completing a PhD, of going through the times where your idea doesn't work and that long, dark tunnel of writing the thesis, of actually having the self-motivation to finish something which you are passionate about with all its ups and downs -- I think that that creates a skill which can be applied in any kind of senior or independent position anywhere. And it gives you a confidence that you can actually do something.

Friday, July 24, 2015

A Physicist and an Engineer Go Looking for Data Scientists

In early April we had a visit from two data scientists at Engage3, who came to speak in our Alumni Seminar Series. Toward the end we had some particularly interesting discussion about the value of a physicist as data scientist. I include that part of the conversation here, addressing the question: you need a lot of machine learning, probability and statistics, subjects never taught in physics departments, so why do you hire physicists?

Anup Doshi, Director of Data Science at Engage3
As background, in late March we had a physics department colloquium by the founder of Engage3, Ken Ouimet. According to the Engage3 website, "Ken earned a BS in Chemical Engineering from UC Davis and went on to UC Santa Barbara to pursue his PhD work in Chemical Engineering and Theoretical Physics. While studying Statistical Physics he realized he could utilize these same principles to model retail markets and optimize retail pricing decisions."

The colloquium title was "The Physics of Shopping and Algorithmic Trading in Consumer Marketplaces." The visit by Ouimet led to our meeting with the Engage3 data scientists. They were James Holliday (PhD in physics from UC Davis in 2007) and Anup Doshi (PhD in EE).

We pick up the discussion toward the very end of Holliday's presentation.

Holliday: We’re trying to hire people. I tend to look for physicists or people who have gone through a physics education. And the reason I do that is I believe that physicists have a way of solving problems and approaching problems that’s unique. I love the way that we’re taught to take a problem, a complex problem that we’ve never seen before, and break it down into fundamental blocks: things that we have seen before or things that we understand very well. And it can be a really complicated thing and maybe we have to make some approximations, but the ability to look at something that we have not seen before and come up with a way to solve it – it’s just wonderful and I think it’s unique to physics. 

LK: I’m curious for an engineer’s perspective. We can tell ourselves stuff like this all the time but I’m a physicist. You [Doshi] have physicists working for you, and you’re in the market for hiring talent. So I’m also really interested in your perspective on what’s valuable about a physicist.

I think the key qualities that physicists bring to problem solving are the ability to approach a problem from first principles, mathematically model a problem from first principles, and then follow in some sense a scientific method to get all the way through the problem.

Doshi: Sure. Just to preface that question: my background – I did a PhD in Electrical Engineering and since then I’ve been working in this field of data science for a number of years now. I’ve had bosses that are physicists, colleagues that are physicists, and folks that are working for me as physicists, and I always enjoyed working with all of them. I think the key qualities that physicists bring to problem solving are the ability to approach a problem from first principles, mathematically model a problem from first principles, and then follow in some sense a scientific method to get all the way through the problem. That's formulating the problem, doing background research, modeling, generating a hypothesis, doing experiments, doing tests, skills from high energy physics like Monte Carlo simulations, for example, solving great, tough optimizations, going to the whiteboard and actually writing out the optimization problem; working out better ways to solve this. And then beyond that just getting the results and interpreting the results and then communicating those back. Those skills are unique to I think the mathematically-oriented, scientific person, like physicists. You don’t get that necessarily in any other discipline, that I've seen.

Holliday: Exactly. I like to look for the physicists when I'm hiring data scientists. One thing that I do when I’m interviewing people is I’ll throw a problem – I’ll throw it very quickly – I’ll throw a very difficult problem that I don’t expect people to necessarily be able to solve; I don’t give them all the information they need to solve that because I want to see if they can ask the right questions to understand the problem to make progress on it. And I want to see how they think about it as they’re pushing forward; to see if they can’t work in those situations.  The ones we wind up hiring tend to be ones from the mathematical, the scientific-oriented fields, that can think through the problem. So I would encourage everyone as you’re pursuing science or whatever,  make a habit out of asking for clarifying information if you don’t understand something. That is the real world: sometimes you’re not given all the information you need; you need to get that information to make progress.

Questioner: Why don’t you guys hire from mathematicians rather than physicists?

Holliday: We have talked to a few statisticians, and we hired somebody recently with a statistics background; a statistician. 

Questioner: I think you’re thinking biased because for data analysis you need a lot of statistics and machine learning and probability, which are the courses that are never taught in physics departments. You have to spend a lot of time investing in some people to teach them those courses.

Somebody else: I think if you’re a physicist you’re assumed to know probability and statistics; that is the basic –

Original questioner: A little, but not as much as mathematicians need statistics. I am working on complexity, but in all interviews I say that I have a statistics background with probability and machine learning.

Holliday: Yeah, that’s very fair, and I appreciate the question. I suppose it is coming off like I’m saying I’m putting up a filter: only physicists apply. One nice thing, what I get when I assume that a physicist or data scientist is coming in, like we said, there’s the assumption that they have some of that mathematical foundation. If someone were to come with just a mathematical degree, I would be happy to interview. I would obviously be impressed with the math; there’s probably a lot that could be said about the problem solving, and we’d just have to see. 

Doshi: So if I could follow up on that: we see a lot of candidates come across our desk who have X, Y, Z background, and then they’ve got a Master’s in Data Science. And there’s lots of programs now. Data science itself is a big, growing field, and a lot of universities are offering the “Master’s in Data Science.” And they’ll teach you skills like basic statistics, basic machine learning, computational skills – learn python, whatever you need to learn – they’ll teach you that for a year or two, then pump you out with a degree in Data Science. You see a lot of those candidates coming across our desk. They’ll come across, and we’ll pose them one of the simplest problems, a Bayesian problem, and they won’t know how to approach it properly because it doesn’t fit into the things that they’ve learned.

Math questioner: I didn’t mean those. Because those are programs that you pay for them; you don’t get admitted to university for data science; it’s like an MBA.

the key missing qualities there are that inquisitiveness and the ability to approach a problem from a first principles kind of concept.

Doshi: Maybe, but there’s also courses – you can go out and learn by yourself whatever machine learning you want to learn, and so the key missing qualities there are that inquisitiveness and the ability to approach a problem from a first principles kind of concept. Even if you don’t know how to solve the problem the way it’s supposed to be solved, can you think about a solid approach, and can you formulate it in a way that, given your background, that will get you to a reasonable answer – a reasonable hypothesis even – a reasonable answer relatively quickly? And then can you follow through that logic? That kind of inquisitiveness and the ability to approach a problem correctly is much more valuable than actually having those skills because then if we grab the people that have that ability, then we can go out and say hey, here, read this book and come back. 

Other questioner: What are some of the things that you thought you needed to learn as you entered industry, that have helped you succeed in industry?

Holliday: So here’s the academic world versus the real world: in academia you spend a lot of time making sure that the calculations are correct, the foundations are right, the assumptions are correct; in industry there’s a whole lot of “I need something right now.” And that’s a little bit hard for me. And I could see how somebody who has definitely gone through the path of academia would not want to maybe compromise the ethics of the math in order to get a very sloppy calculation out now that we can give to the investor because we’re on the hook for something that needs to be delivered.

Sunday, March 29, 2015

Kate Marvel: Physicist, Climate Scientist Part II

The California drought: does the climate change 'signal' stand out above the 
weather 'noise'? [Figure credit: Jeff Master's Wunderblog]
In the second half of this interview with Dr. Kate Marvel of the NASA Goddard Institute for Space Studies, we discuss her field of climate science. We cover uncertainty, the hunt for signal in noisy data, and the joy of seeing physics work. In her case that joy is a mixed blessing because her data are backing up models that can, at times, make somewhat depressing predictions. All views expressed here are her own.

LK: You’ve been in the thick of comparing different climate models, and seeing how well these models agree with each other, seeing how they’re doing in various tests. What would you want to say about the state of the art here, and the description of our uncertainty? 

KM: There is an incredible amount of uncertainty, and for me that is the scariest thing. It’s not true, but I think you could make an argument that wasn't that wrong if you were to say We don’t know that much more than we did back in the 1800s. We know that there’s a greenhouse effect; we know that carbon dioxide is a greenhouse gas. And just from looking at that we know that if you put a bunch of carbon dioxide in the atmosphere, the Earth is probably going to warm.

And then you see it empirically, in the historical record?

I do a lot of what’s called detection and attribution -- basically trying to figure out what climate change looks like. You might say this is easy: “Duh, it’s global warming.” But what does climate change look like in terms of changes to rainfall patterns or cloud cover, for example? And so we try to understand from basic physics what would happen, what is supposed to happen under climate change. And then looking at observational records; looking at the satellites or ground-based gauges or whatever and saying, “Okay, this thing that we expect to be happening; is it happening?” It’s this weird cognitive dissonance, because you get really excited when you can show when it’s happening, because it’s very elegant. You’re like, “This is what physics tells me to expect; this is what the models are saying; ooh look it’s happening!” Then you kind of realize, “Oh my god, it’s happening!” And that’s a little depressing.

The earth is super complicated, and there are a lot of things that could happen to either speed up or slow down the warming. For example, you melt the ice caps, and that’s a positive feedback – it speeds up the warming. Because you used to have things that were reflecting incident short-wave radiation and now it’s absorbing and re-radiating long wave. So that’s a positive feedback. Warmer air holds more water vapor, and water vapor’s a greenhouse gas, so you make the earth warmer, you get more water vapor, and that accelerates the warming.

But then there are possible negative feedbacks. So if you increase cloud cover down low, then that can kind of reflect more incoming solar radiation and slow down the warming. And it turns out we just don’t understand clouds. We’re making progress, but if you think about how to model cloud formation, that is something that’s really affected by very small scales. Like you put bits of dust up in the atmosphere and you can seed clouds. And that’s really hard to incorporate in a global climate model, because global climate models happen on really big scales, and these processes happen on really small scales. You can’t explicitly resolve them; you have to parameterize them. And it turns out that as a result, we just don’t understand the net effect of cloud changes in the future. And you know, I think we’re making some progress on narrowing that down, but it’s kind of the biggest source of uncertainty right now.

Well people must also be thinking then of seeding clouds; intentionally creating clouds.

Yeah. I mean, there’s a lot of work being done on what’s called Solar Radiation Management, which is either like “Let’s try to increase cloud cover,” or just like “Let’s put a bunch of junk up in the stratosphere so that we decrease the amount of solar radiation coming to the lower atmosphere and hitting the Earth.” People have done a lot of modeling studies, but I think there’s kind of a general consensus that nobody wants to do this. There are so many uncertainties and it would be so much better if we didn’t have to do this. But it doesn’t benefit anybody to be completely clueless about it.

I did a carbon audit on myself a few months ago; just on one of these sites where you can enter some simple information. And not surprisingly, my footprint is dominated by flying. And it’s something I’ve wrestled with: what do I do about that? And I’m wondering, so certainly you’re doing science; you benefit greatly from being able to talk to other people and there’s benefits to actually being there in person. How do you think about your own carbon footprint, your own contribution to this problem given the work you’re doing, what you’re focused on?

I try to draw a very firm line between what I do scientifically and what I do personally. Because I do know that there is a science of communication, like “What is the best way to talk to people about these things?” And telling people to stop having fun is not ever going to work. And so I would be thrilled if we had a conversation about what’s the best way to mitigate climate change. And I don’t know, I feel like there are a lot of really smart people thinking about this, people who have training in economics and sociology, etc. It’s not that I feel that it’s not my place, because I have my personal beliefs, but I don’t think we’re there yet. We’re still arguing about whether climate change is a thing and I would just be so thrilled if we stopped having that argument.

We’re still arguing about whether climate change is a thing? What do you mean by that?

I feel like a lot of the political discourse is talking about “Is this happening?” And I find that so frustrating because what should be arguing about it is “What should we do?” And to even be having the discussion would make me so happy. So I’m kind of trying to work on trying to shift the conversation from “Is climate change happening?” And my answer is yes. And “Are we responsible?” And the answer is almost definitely yes. And then trying to move that to “What should we do?”

“I’m kind of trying to work on trying to shift the conversation from “Is climate change happening?” And my answer is yes. And “Are we responsible?” And the answer is almost definitely yes. And then trying to move that to “What should we do?”

So how do you go about that? That sounds to me a) fundamentally important and b) really difficult, and fundamentally ripe with the possibility of tremendous frustration.

I think it is. I mean, there are some really smart people thinking about the best ways to communicate this. And I think that so far there is a consensus: the consensus is “You can’t just tell people more facts.” Like there’s this thing called the Deficit Model, which says “Well, people don’t believe science because they don’t understand it. So if you just tell them more facts, they’ll accept it.” And I think the consensus is that this approach is just not going to work. And part of it is, you have to restrain yourself. So when somebody says something like “There is no climate change,” or “Vaccines don’t work,” or “Evolution is clearly not happening,” then your first impulse as a scientist is to be like, “Well you’re wrong. You’re wrong and I’m going to tell you why you’re wrong.” And I think that’s just a human impulse – we don’t like it when other people are wrong. But you have to kind of suppress that impulse. It’s kind of like eating Krispy Kreme doughnuts: it’s going to make you feel really good in the short term, but you’re really going to regret it in the long term and it’s probably not worth that short term pleasure.

And a lot of it is tribal. A lot of it is, “I want to be the kind of person who believes in and does something about climate change, because it’s bound up with all of these other things that I accept politically.” Or “I don’t want to be the kind of person that does something about climate change because then I’ll have to accept all these things that I just don’t.” And I think it’s trying to come up with ways to say to people who don’t accept a lot of things which they associate with left-wing political ideologies, and to say, “No, there is room for you here. It is possible to create a narrative that includes you.” And I think that is more productive.

There’s a woman called Katharine Hayhoe who’s at Texas Tech. She’s an amazing climate scientist, but she’s also an evangelical Christian. So she is very good at bridging that gap and telling people that it’s okay; there’s room for people like us here. And I think a lot of what she does can then be undermined by a shouty atheist coming along and saying “No, accepting science immediately means that you have to give up all of your beliefs.” There’s nothing wrong with being an atheist; I don’t think there’s anything wrong with being a believer. And I think that there is room for everybody here, but that means that those of us who are scientists kind of have to suppress that urge to tell people that they’re being stupid when we think they’re being stupid.

I choose not to eat meat, because honestly I don't care for it, and I don't drive because I live in a dense city with decent subway service.  But I don't think my personal choices should necessarily be universal, and I don't think it helps to tell other people to give up things that make them happy.

“. . . When somebody says something like “There is no climate change,” or “Vaccines don’t work,” or “Evolution is clearly not happening,” then your first impulse as a scientist is to be like, “Well you’re wrong. You’re wrong and I’m going to tell you why you’re wrong.” And I think that’s just a human impulse – we don’t like it when other people are wrong. But you have to kind of suppress that impulse.”

There’s a book by Naomi Klein in which she argues that conservatives are scared of this for the right reasons, because meeting this challenge means we have to rethink fundamental things about the free market system. Do you care to comment?

I have no idea if that narrative is correct because I’m not an economist. I know that some people are saying, “Okay, we have to completely overhaul capitalism,” and some people are saying, “No, we just need to price externalities right and there’s a free market way to do that.” And I know which position I’m sympathetic to because of my own personal politics, but I think me talking about that would be like me talking about criminal justice or reproductive rights in the sense that I have my beliefs about this, but I don’t claim expertise on that, you know what I mean?

Yes, and I respect your reticence very much. 

Is there anything from the science you’re working on now that you want to tell me about? Questions that you’re digging into that are really fascinating you? You said you’re working on basically figuring out what the predictions are for things like rain patterns and then going and trying to verify those in the historical record, or see what you learned from what we know. Anything that was surprising in this process or really cool?

I just think it’s great. I think one of the great things about climate is that there are so many Big Questions to answer. So you can do these things like, “Okay, how much wind power can we extract from the atmosphere?” Or “What is happening to rainfall patterns?” You can ask these very big questions and I really like that. I’ve gotten really obsessed with clouds, which is ironic because I hate bad weather and I’m only happy when it’s sunny outside, but know your enemy, right? So I’ve been doing a lot of work on clouds. Because I think this is a really interesting question, and we’ve been able to show that you can actually see things happening in the observations in clouds. At least in a couple data sets, you can see clouds rising, which is what’s predicted under global warming conditions.

What do you mean, you can see them rising?

So we’ve got cloud satellites dating back to the early 80’s, and in the satellite data, you can basically see the fingerprint of human-caused climate change in the cloud records, which is really surprising, because they’re so noisy, and so difficult to get anything out of. But you can really start to see all of these patterns emerging and it’s amazing how coherent everything is.

So you mean the typical height of the clouds above the land is changing?

Yeah. So I mean the height of high clouds is changing. So these big thunderheads that you would see, like convective clouds in the tropics, those are rising, those are going higher in ways that are predicted very robustly by a lot of the climate models and some of the physics underlying them, which is incredible. If you look at what climate change is supposed to do to rainfall, there are two basic underlying physical concepts. One, warmer air holds more water vapor, so all else being equal, wet areas will get wetter and dry areas will get drier. Two, all else is not equal, and we expect changes to atmospheric dynamics, which means the locations of those wet and dry areas are moving. And if you look at the satellite records you can see that the wet areas are getting wetter and the dry areas are getting drier and the entire pattern is moving poleward in basically exactly the way that you think it should. So that’s kind of amazing to see theory go to models, go to observations, in quite such a straightforward way.

I can see why you would get excited.

Yeah, maybe like, “Oh man!” <laughs>

So wet areas getting wetter, dry areas getting drier, and then everything moving around, that final statement – there’s no meaning in it then, unless the predictions are quite specific on how things are moving around. And they are?


So we’re in what looks like the fourth year now of a drought in California. What does this work actually say about particulars like that? Is this likely associated with climate change? Is it just consistent with what we expect? How do I think about this drought in the context of climate change?

The smaller the scales you’re looking at, the more complicated the picture becomes. So if you’re just looking at the California drought: I think the story that’s emerging is that it’s consistent with things that have happened before naturally, so the California drought looks like natural variability. But that doesn’t mean that it’s not influenced by climate change. So I think the tricky thing to try to understand, and the tricky thing to communicate, is that there’s no such thing as weather independent of climate. It’s like personality and mood; weather is mood and climate is personality. But obviously your moods are affected by your personality. And so the California drought – things like that have happened before, things like that would probably happen even if we weren’t doing anything to change the climate, but the California drought is happening in the context of climate change. And so just because it’s consistent with natural variability, that doesn’t rule out a role for climate change. It’s just that the role of climate change is really difficult to disentangle, if that makes sense. There are some things that are more clear-cut; the extreme heat events they're experiencing in Australia are very unlikely to happen without systemic climate change. And so there are things that are more clear-cut than others, and the California drought is kind of in that non-clear-cut category.

“. . . It’s like personality and mood; weather is mood and climate is personality. But obviously your moods are affected by your personality. And so the California drought – things like that have happened before, things like that would probably happen even if we weren’t doing anything to change the climate, but the California drought is happening in the context of climate change.”

Well, it’s like that in cosmology, where there are certain signals we can only dig out of the noise by stacking, so I guess that’s the case here with climate in California: you look at the patterns globally and I guess that’s what you’re saying about dry areas getting drier, wet areas getting wetter. In particular areas you can’t separate out that signal from the weather variability noise. But more globally you’re seeing the signals emerge.

Yeah, exactly. I mean, that’s even how we use that language. We talk about things as a signal to noise problem. Just because there’s a lot of noise and you can’t pick out the signal, it doesn’t mean that the signal doesn't exist. But the signal of climate change is getting louder and louder, and we're starting to pick it up in more places.