Angus Ferraro

A tiny soapbox for a climate researcher.


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EUMETSAT Conference 2014: Challenges and advances in satellite measurement

Atmospheric measurement is an extraordinarily difficult problem. It’s a fluid capable of remarkable feats of contortion, and it contains a number of important constituents, including one – water – which flits easily between solid, liquid and gaseous forms. Satellite instruments offer a unique way to measure the state of the atmosphere, viewing broad swaths of the planet from space.

I’m at the EUMETSAT Meteorological Satellites Conference in Geneva, which is as good a place as any to understand what a remarkable achievement this is. These are my highlights from the first two days, and reflect my particular interests, so I have probably missed a host of other interesting scientific advances.

A major theme of the ‘climate’ session at the conference was the problem of generating long-term climate records from satellite data that is often very choppy. Satellites and their instruments can have very short lifetimes, usually just a few years, though some (like the rather venerable 17-year-old TRMM) buck the trend. Satellites can only carry so much fuel to keep them in orbit, and their instrumentation gradually degrades over time in the harsh environment of space. To maintain a long-term record, you would want to send up identical instruments into identical orbits – but in reality this is not possible. The instruments themselves are made with extraordinary levels of precision, but their complex and delicate nature means it’s not actually possible to make them identical. They will usually have slightly different sensitivies. The satellites carrying them will have different orbits, which means they might measure different parts of the Earth at different times.

Changes like this can cause major stability problems for satellite records. Each time a new instrument goes up on a new satellite the record tends to ‘jump’. Common reasons for this include slight differences in the sensor’s sensitivity, and sampling changes due to the different orbit. As an example, rainfall in the Tropics usually peaks in the afternoon. If you send up a new instrument which passes over the Equator in the morning, it will look like rainfall has abruptly decreased compared to one that passes in the afternoon, but all that’s happened is that you’re measuring it at a different time. These so-called ‘inhomogeneities’ need correction if we are to stand a chance of using these records for studies of climate (which is the statistics of the atmosphere and oceans over decades – many satellite lifetimes).

The ‘climate’ session at EUMETSAT highlighted many approaches to such problems. There was also discussion of the potential for improving the physical consistency between datasets, so common ‘budgets’ can be closed. However, the fact that our observations sometimes don’t ‘add up’ is an important piece of information. It means we’re getting something wrong – but exactly what is of course a rather difficult question.

On Tuesday afternoon a session on precipitation measurement included some very impressive results from the new Global Precipitation Measurement (GPM) mission. A number of technological advances, combined with a unique approach of using two reference satellites to calibrate the measurements from a ‘constellation’ of 11 others, now provide unprecedented detail on Earth’s rain and snowfall. High-frequency microwave measurements combined with radar allow us to look at the icy parts of clouds and to see areas where even very light rain is falling. This allows us to look at, for example, tropical storms in a whole new light – and most importantly, because it’s based on such a huge array of measurement platforms, we won’t miss a single one.

Another impressive aspect of the GPM mission is the speed with which things have moved. Since its launch in February 2014 GPM has been providing huge streams of data, which an international team has worked on to convert to precipitation measurements. Within a short time the data were available to the public. The data were available to the world’s major weather forecasting centres within 2 weeks, allowing them to get a much better picture of the current state of the atmosphere (this is important because small errors in the initial state of the atmosphere can lead to large errors in a weather forecast). In short, GPM looks like a thoroughly modern measurement misson: an international collaboration, operating openly and with detailed documentation, providing timely and freely-available data. Plus it produces some cool graphics (see below).

One of the first storms observed by the NASA/JAXA GPM Core Observatory on March 17, 2014, in the eastern United States revealed a full range of precipitation, from rain to snow. Image Credit: NASA/JAXA

The day closed with a visit to the headquarters of the World Meteorological Organisation for presentations and discussions on the socioeconomic value of satellite data – that’s covered in another post.

EUMETSAT Post 2: Socioeconomic benefits of meteorological satellites. 

EUMETSAT Post 3: Final highlights.


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My thesis: friend or foe?

Bound and ready to submit!

Bound and ready to submit!

Last Monday I submitted my PhD thesis. I walked over to the Examinations Office in the centre of campus, up a few flights of stairs, handed a big old pile of paper over to the secretary there, signed a form, and that was it. I started my PhD in October 2010, and according to my notebook I wrote the first few tentative words of my thesis in June 2012.

I have heard others tell tales of the looming monstrosity their thesis became in their life, constantly bearing down on them. The folk wisdom of the PhD student is that your thesis is your enemy, and that every day you have to do battle with it, to subjugate it and wrestle it into some kind of coherent shape. To be honest, it never felt that way to me. I followed the standard routine chapter by chapter: outline, concept map, make figures, write text, proofread and edit, send to supervisors, revise. When I started blogging I had planned to use it to describe the process of writing a thesis as it happened: a ‘stop-motion’ thesis, as I called it then. It turns out that the process is a largely uneventful one, churning through the routine described above.

Occasionally this process broke down. There were times when I felt mentally and physically sluggish, so I took a short break – an afternoon off, perhaps – to refocus. It helped that I was still doing little bits of analysis quite late into my PhD. I had done enough to be content, but had a few extra things that were worth doing since I had some spare time. These tasks were pleasant distractions and allowed me to keep my mind active without stressing it out with major pieces of work with real and imminent deadlines. My thesis was never my friend, but it wasn’t my enemy either.

So, for me at least, writing a thesis hasn’t been an epic climactic undertaking. It’s been built up bit by bit, and I’ve worked without putting myself under crippling pressure. I think the academic environment here at the Department of Meteorology really helped: my supervisors provided encouragement, advice and calming words when they were needed, while the rich programme of seminars and group meetings reminded me that I was also there to learn, not just to write a big book and plonk it on someone’s desk.

As I walked back to my office after submitting my thesis I did feel noticeably ‘lighter’. Although it hadn’t been a stressful experience, getting rid of it still felt good. I am now free to do things for their own sake, rather than the artificial goal of a document for examination.

On the subject of examination, I still have my viva (or thesis defence) ahead. In the UK this takes the form of an oral examination by two examiners: the main one from another institution and the other from one’s own (who also takes the role of a moderator). The candidate is quizzed on the details of their thesis in order to check whether it really is their own work and whether they have the depth of knowledge befitting a PhD. It doesn’t sound like a pleasant experience but at the same time I’m looking forward to discussing my work with others. Much like the process of writing is pleasurable if one puts aside the fact it’s for a thesis, I hope the process of discussion my work will be pleasurable if I put aside the fact it determines whether or not I get a PhD!


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(Why) I’m a scientist

If we cut down all the trees, how long would it take us to die?
What qualities do you need to become a great scientist?
When is the zombie apocalypse going to happen?

These are some of the questions I have been pondering over the past two weeks as part of the online event ‘I’m a scientist, get me out of here’. The event puts scientists (grouped into themed ‘zones’) in touch with groups of school children around the country. Children can send questions to the scientists at any time, but what’s even better is they can interact with them in scheduled live chats.

Children vote for their favourite scientist, and at the end of the two weeks one in each zone gets £500 to spend on a science engagement project of their choice.

‘I’m a scientist’ is structured as a competition, but I don’t really think that’s the point. I signed up because I thought it would be fun. I signed up because I can imagine getting a lot out of the event as a schoolchild (which wasn’t particularly long ago – I finished secondary school in 2007). When I was at school I hoovered up facts and such quite diligently. I didn’t really need to be enthused in order to learn. Looking back, though, I think I missed the point of it all.

When I was a boy…

To me, school science practicals felt a bit staged. Recording the resistance of a length of copper wire as it heats up is a useful experiment: it teaches important principles of electricity and it demonstrates the scientific method: question, hypothesis, prediction, test, analyse. But it’s not that exciting.

We also spent a long time on a practical about the cooling of test-tubes of warm water. Which cools slower – a single test tube of water or a test tube surrounded by others? The one with the others around it, of course. This experiment was designed to explain why penguins huddle together and was a perfectly reasonable demonstration. But it felt a little ‘play-school’ at the time. I had also been told by my teacher to put a line of best fit through by data points, but that ‘data points don’t go on the line of best fit’ (thus I even added measurement error to my fictional observations). In fact, I confess, in that experiment I made up some data because I knew what the relationship should be between the temperature after a certain time and the number of surrounding test tubes. I was in a hurry and didn’t want to bother repeating the experiment with more and more surrounding tubes.

I took away the wrong message from the practical. I was fixated on matching my results with the information I had already absorbed – that insulating with additional tubes reduces cooling – rather than carrying out a correct, valuable experiment. The scientific process seemed like a rigid set of arbitrary rules back then. I didn’t appreciate that an experiment done incorrectly is valueless (I should stress that I do not make up data now, of course).

Why was I a rubbish scientist?

But why did I miss the point back then? I think it’s because I couldn’t quite see the purpose of it all. It was quite obvious to me that additional test tubes would stop the cooling rate. I just wanted more information to absorb, not to waste my time confirming what I already knew. Essentially, I completely misunderstood the point of learning and the point of science. That is no reflection on my teachers. It just reflects how children often greatly misunderstand why they are at school, and consequently don’t get as much out of it as they should.

What’s the point then?

Which brings me back, after a very lengthy aside, to why I signed up to ‘I’m a scientist’. I am now coming to the end of my PhD and I think I know a little about the scientific method (at least, I know enough to understand why it’s unacceptable to make up results!). I ‘get’ it now. I find it thrilling to be doing science when no one knows the answer and the results are new and puzzling. That’s what it’s about, and that’s what I tried to get across to the kids when presented with their common question ‘what do you like about science?’.

I came second in my zone, behind the excellent Simon Holyoake. To tell the truth, all the scientists in my zone – Hannah Bentham, Laura Roberts Artal and Christian Maerz – were excellent and gave engaging, exciting and thoughtful answers to the kids’ questions. I think we all had a lot of fun chatting to the kids, and deciphering some left-field questions. Some of the questions made me think quite a bit, and explaining things simply really helped me work out how well I understand some basic scientific principles.

So, to any scientists out there, I highly recommend applying to participate in the next ‘I’m a scientist events’. To any teachers out there, I highly recommend getting your class involved. I think events like this are a very effective way of allowing young people to understand why they are learning all these equations, why they care about the difference between igneous and sedimentary rock, why it’s important to put error bars on graphs, and why they’re in this damn classroom on a nice sunny day. Because science is important.

There are plenty of questions science cannot answer, and there are plenty of other valuable forms of knowledge. But science is a great way of learning useful things about the world, and is pretty special because of the quality of predictions it makes and the level of detailed understanding it gives us. That’s why I’m a scientist.


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Getting the balance right: talks, posters and more at #EGU2013

This post is a collection of thoughts about learning how to ‘operate’ huge conferences like EGU. It’s my first time doing this and I’m now starting to learn how to get the most out of it.

First I’d like to talk about the bread-and-butter of the conference, oral presentations (talks). I like going to talks. A well-designed 12-minute talk can give a great overview of the research, communicating novel methods and approaches as well as key results. However, a full day of 12-minute talks is quite draining. My EGU personal programme for the first two days was completely filled with talks and by the end of the first day I was craving a poster session. I enjoy chatting to people over their poster more than I do sitting down and listening to a talk. Going to a talk is a more passive experience. For me, posters are a little more ‘human’. There is time for detailed conversation on topics of your choosing, or you can take a less tiring approach and just wander down the aisles of the poster halls and skim the posters of interest.

Days at the EGU meeting are structured such that most talks happen in the morning and posters in the afternoon. I like this. It recognises that talks are more taxing and puts them early on, allowing people to relax later in the day. However, on Monday and Tuesday I spent the 1730-2000 slot in two excellent short courses on tipping points and predictability. I will write a separate post about them later because they really were superb, but the long and short of it is that I found them a very valuable use of my time. I didn’t miss the posters at all during these sessions because the lecturers were so engaging.

Talks and short courses: that’s been my EGU so far. This evening I will get the chance to go to some poster sessions, which I am really looking forward to.

And yet I’m still missing out on huge chunks of the EGU experience! My calendar is full of sessions running in parallel, all of which I would love to go to. I’ve missed out on some excellent Medal Lectures, which I have heard from friends are really nice (a break from the short, functional oral presentations). When I put together my programme (using the excellent smartphone app) I quickly realised I was going to have to get used to this feeling that I was missing out. Yesterday I tried to flit between sessions, aiming to attend specific presentations. This can be done, but it gets complicated quite quickly, and sometimes it can take a while to get to the new room.

Today I have taken a more laid-back approach. If a talk comes up that isn’t particularly relevant to me I will use that opportunity to ‘zone out’ and rest my brain. As the conference goes on I am finding downtime to be quite important! There is a park close to the conference centre which offers a chance to get some fresh air and relax. I find a relaxing lunch really helps me come back refreshed and ready to engage in the afternoon sessions.

My plan for this afternoon includes the remainder of the session on clouds, aerosols and radiation, the debate on fracking, and a whole host of posters on a remainder of topics. That’s the kind of mix I love: some talks relevant to my own work, something rather different with potential for great discussion, all rounded off by a walk around the poster hall. This evening I’ll be heading to the EGU Tweetup, a meeting for scientists interested in using Twitter and similar tools for science communication. See the #egutweetup hashtag for more details.


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First impressions of #EGU2013

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Arriving at the Vienna International Centre is a very exciting experience. I went to the conference centre yesterday to pick up a programme and to get my bearings, together with some other PhD students from Reading.

We wandered amongst the half-prepared stalls and peeked into the rooms in which our presentations would be held. It was exciting to imagine the place jam-packed with scientists and bursting with new research ideas.

After a late lunch in the Innerstadt we headed back to the hotel to relax before going back to the conference centre for the opening reception. People flooded into the conference centre to meet old friends and make new ones. I was in bed quite early though, given I was presenting at 9:30 the following morning!

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I presented my work at the Open Climate session. The audience was bigger than I had expected, but I think it went OK. It’s very easy to think of all the things one should have said once the talk is done. It wasn’t a disaster though, which means it counts as a success. This was my first time presenting at such a big conference and I am sure future presentations will be much improved by the experience.

I got some good feedback and comments after the talk, which was much appreciated. Now I can fully.enjoy the delectable menu of scientific delights EGU 2013 has to offer.

It’s going to be a great week. The Sun has even come out!


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New chapters and foreign lands

By January of this year a major chunk of my PhD work was winding to an end. I had spent a long while looking at the effect of stratospheric aerosol geoengineering on the circulation of the stratosphere, which will form the second (and probably biggest) of the three results chapters in my PhD thesis. At the start of my project I had spent a lot of time reading about stratospheric dynamics and it’s now a somewhat familiar area to me. Well, almost. I still find some chunks counter-intuitive, and sometimes downright baffling. But at least it’s baffling in a familiar way.

We are always reluctant to move away from the familiar. But the work for my final results chapter required that I take the plunge into material and theory that was very much unfamiliar. I was going to look at the impacts of geoengineering on the tropospheric circulation. I eased myself into it by thinking about the tropospheric jet streams first. I at least have some grounding in this area. The dynamics of the midlatitude jet streams is somewhat similar to the dynamics of the stratosphere, and my undergraduate degree in Meteorology has quite a heavy emphasis on the theoretical underpinning of it all. The work on the jet was a nice transition.

Recently (over the past month or so) I have been thinking about precipitation. Especially tropical precipitation. Now, the Earth’s Tropics are meteorologically very different from the midlatitudes. In the midlatitudes the Coriolis Force is a significant effect and weather is determined by large scale wavelike motions producing depressions and anticyclones. Rainfall is mostly frontal in nature. In the Tropics the Coriolis Force is negligible. As a consequence we don’t usually see very large horizontal temperature gradients. This means we don’t see large, rotating weather systems. Rain comes from convective storms, on a much smaller scale than midlatitude frontal depressions. There is so much moisture in the air in the Tropics that the vertical temperature profile pretty much everywhere shows evidence of the release of heat when water vapour condenses to form rain. This forms a characteristic moist adiabatic temperature profile (see image below). Without a strong Coriolis Force this temperature profile is spread over the Tropical belt, so we see it even outside the rain-producing regions.

In order to interpret my model results I had to learn to think differently. Intuitions learned from midlatitude dynamics don’t apply this close to the Equator.

Learning new theory can be pretty intimidating. It’s difficult to know which paper to read first. Sometimes I find myself feeling paralysed. I have a pile of things to read but keep having to refer to different sources to understand terminology, or to get to the bottom of some ‘obvious’ physical understanding not fully explained in one piece of research. Then I took a different tack. I went to see one of the hundreds of other people working in the Department of Meteorology.

This department has experts on any conceivable area, and now, when I’m learning new theory, this is becoming invaluable. In a single hour with a researcher in tropical meteorology I ‘got’ it. I understood the fundamental differences between tropical and midlatitude thinking. Now I can read those papers with confidence. Now I understand the terminology, and a little of the intuition as well. Self-teaching works well (and is entirely necessary for a PhD student) but spending a little time with an expert can help one learn how to teach oneself. This is much the same as, how, when learning a foreign language, you must first learn enough to communicate on a basic level. Once you have that, you can begin to immerse yourself, to learn from conversation with native speakers. The amount of learning that goes on increases exponentially with time. You learn far more from native speakers. But you need to do that initial bit of work to access this higher plane of learning.

Talking of foreign lands, I will soon be off to the 2013 EGU (European Geosciences Union) General Meeting in Vienna. It’s a colossal conference (nearly 12,000 people attended last year) and I’m sure the experience will be educational, entertaining, confusing and exhausting. I’m sure I could list adjectives forever on that one. I will try to write some blog posts and Tweets during the conference, reflecting on what it’s like for a naive young PhD student to be launched into one of the world’s biggest academic conferences.


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The working day of a PhD student

The results are in! Over the past month I have been logging my work patterns. I explained my motivation in a post before I started. I wanted to know how long I spent working, and what I was doing during working hours. The question was: can a PhD student get away with just working 9-5?

The answer is, broadly, yes.

How long do I spend working?


On an average working day I spent 8.57 hours ‘at work’. This is rather loosely defined, but essentially it means I am either at my desk on somewhere else on the university campus. I am not actually doing anything PhD-related for 2.17 of those hours. That brings my daily work time down to 6.4 hours.

Before I began, I estimated that I would spend 6 hours a day working. I may have overestimated my actual work time because I tended to round my working half-hours up (see the Methods section below).

The graph above shows the number of hours worked per day. The 8-hour line represents the standard length of a 9-5 working day. Some days were rather unproductive with large amounts of time ‘greyed out’ where no work was done. You can see at the start of the month, coming back from Christmas, I was very keen. I even did some reading on the weekend. Later on my working time waned slightly. You can also see that the second Friday was a very short working day. It snowed that day and I was finding it difficult to concentrate so I took the afternoon off!

What was I doing?

I spent the biggest chunk of my time coding. This applies to making plots as well as analysing data. Since climate modelling is necessarily computer-based, it’s no surprise coding comes out on top. Next comes my ‘nowork’ category, which I discussed above. I had just over two hours off per day. I rarely take clearly-defined lunch and tea breaks, but I suppose these two hours can represent them. In reality those hours were spent procrastinating on the Internet or doing other things not related to my PhD. This includes organisational tasks like booking transport to meetings and conferences, maintaining websites, and so on.

‘Understanding’ covered research I did with a specific purpose, like finding out how to do a particular type of analysis, or comparing my results with others. This explains why the time I spent ‘reading’ was comparatively small. My purposeful research obviously involved plenty of reading. The ‘reading’ category was specifically for reading new and interesting papers to develop my background knowledge, rather than to find a specific piece of information.

I was surprised how much time I spent in meetings. I think the proportion is artificially large because the Department held a Research Day in early January, when representatives of research groups give summaries of their work to the rest of the Department. Then again, I only went to an afternoon’s worth of talks. I value meetings. Obviously those with my supervisors are very important, but seminars are an excellent way to broaden my education. Recently I have also been thinking about acquiring new skills for analysis, and one of the best ways to learn about these is through seminars.

Finally, the ‘writing’ part: it’s very small, but that is because I haven’t really started my thesis in earnest yet. If I was at a loose end I would do a short stint adding some material or reorganising what I already had.

There is enough time

These results have shown that I haven’t been overly efficient during working hours. I don’t work very hard (in terms of work out versus time in), and yet my output is reasonable, as is the quality of my work. I worked slightly over the standard 8-hour day, but if I really wanted to I could trim this down without sacrificing quantity or quality. In fact, I might gain productivity by constraining my working day, because I’m likely to become less lazy and less easily distracted.

Methods

I used a Google Doc spreadsheet to record the time spent at work. I recorded my predominant activity in half-hour blocks. Work doesn’t fall neatly into blocks like this so I had to do some subjective re-jigging. For example, if I start work at 9:15, so I write in the 9:00 – 9:30 slot that I did some work? I went by the rule of thumb that, if I worked for more than half the time in the slot, I would record it. I categorised my time as follows:

  • understanding – active research, including reading, to find out specific things
  • coding – making plots or running models
  • meeting – talking to other scientists
  • writing – thesis or other smaller piece of writing; blog posts
  • reading – reading papers and other articles without a clearly-defined purpose
  • nowork – breaks, organisational stuff, admin

I think there is more information to be pulled out here. I actually find it quite interesting to just look at the colour-coded allocation of time in my spreadsheet rather than the graphs above. One can pick out, by eye, that I tend to do coding in long, uninterrupted blocks. I find it easier when I have got into the ‘flow’; plus it is simply time-consuming. Please do take a look at the spreadsheet. I would be interested in hearing comments on the results or the method, since I may be trying this again in the future!