My journey to Reading: Going from application to newly minted SCENARIO PhD student

George Gunn – g.f.gunn@pgr.reading.ac.uk 

Have you been thinking ‘I’ll never be good enough for a PhD’? Or perhaps you’ve been set on the idea of joining those who push the bounds of knowledge for quite some time, but are feeling daunted by the process? Well, keep reading. 

I started university with the hopes of stretching myself academically and gaining an undergraduate degree. As the degree progressed, I found myself increasingly improving in my marks and abilities. I enjoyed the coursework – researching a topic and the sense of discovery brought about by it. I became deeply interested in climate change and the impact humans have on the environment and was able to begin my dissertation research a year early because I was so motivated within my subject. 

In my final year of undergraduate studies, much of my time was pre-occupied with my role as Student President. Attending social events, board meetings, and lots of other things that didn’t involve a darkened room and a pile of books. I was very much a student who turned up, put the effort in, and then spent the rest of my time as I wished.  

Giving a speech at the Global Youth Strike for Climate, Inverness, as Student President. Extracurricular activities are a worthwhile addition to your application and were considered a lot during the interview! 

I began to look for opportunities for research degrees online, as well as asking almost anyone and everyone I knew academically if they had any ideas. Nothing came to fruition. That was until I received a Twitter notification from my lecturer drawing my attention to what looked to be an ideal PhD studentship. The snag? Applications were due to close within 3 hours of me checking the notification. 

By the time I had read the project particulars, accessed the cited literature and paced around my living room more than a few times, I had around 2 hours to submit an application. Due to my prior unsuccessful searches, I hadn’t previously submitted a PhD application and so had nothing to refer to – but proceed I did.  

Thankfully, the application was relatively straightforward. Standard job application information, details of the grades I had achieved and was predicted to achieve, and two academic references (for me, my personal academic tutor and climate change lecturer). What took time (I would advise anyone considering an application to prepare these earlier than I did!) was the statement of research interest and academic CV. My university careers service had excellent advice and resources to assist in that regard. 

Within minutes of the deadline, my application was in. I had almost forgotten about it by the time a week-or-so later I received an e-mail inviting me to Reading for an interview day. Shocked and excited were the emotions – little old me from the Highlands of Scotland, who hadn’t yet finished his undergraduate degree, was somehow being invited to one of the best Meteorology departments in the world to interview for a PhD studentship.  

No time to spare, my travel to and from Reading was booked. For the next couple of weeks, all I now had to worry about was how to do a PhD interview – though as will become clear, I need not have worried. I sought the advice of academic friends and colleagues (a calming influence for sure) and countless websites and forums (generally a source of unnecessary worry). 

Given the level of conflicting advice on PhD interviews, on arrival at Reading I wasn’t sure what to expect. At the front door I was provided with all the information that I needed for the day. I then made my way to a room with all the other candidates for a welcome talk and the opportunity to learn more about other projects on offer over lunch. 

The interview itself was very relaxed. No ‘stock’ PhD interview questions here – it was very much an opportunity to discuss my previous work and abilities, and how that might fit with the project. Importantly, it was an opportunity to meet my potential supervisors and ‘interview’ them too. If you’re going to spend 3-4 years working together, the connection needs to work well both ways. So, whilst the 30-minute interview slot seemed daunting on paper, the time flew by and it was soon time to leave. 

Fast forward a week or so and I was very surprised to receive an e-mail offering me the studentship that I had applied for: Developing an urban canopy model for improved weather forecasts in cities. And the rest, as they say, is history. 

At my desk in the Department of Meteorology, University of Reading. 

I hope that this blog post has helped you to feel less daunted to begin your PhD journey. Please feel free to get in touch with me by e-mail if you would like to chat further about beginning a PhD, or indeed to let me know how your own interview goes. Good luck! 

Tips for working from home as a PhD student

As PhD students, working from home is an option for many of us on a “normal” day – as indeed is increasingly the case with jobs which primarily need just an Internet connection. But, thanks to COVID-19, working from home (WFH) is our new collective reality. So how can we make this work well, when for many, our offices may only now be a few steps away from our beds? We asked around for advice on this matter from current PhD students.

Remember to take a break every half an hour or so. Go away from the desk!

It can be easy to forget to take a break when you’re “at home”, even if you’re also “at work”, and especially when you’re likely closer to the kettle/food/toilet than you would be otherwise. Get up, move around!

Stick to a regular schedule: when you wake up, go to sleep, work, relax, etc.

This is great advice for doing a PhD in general, but even more pertinent now that our routines have been turned upside down.

Pretend that you “go to and from work”, i.e take a morning and afternoon walk/cycle to mark the start and end of your work day.

A commute can be a great time to wake up in the morning and wind down in the evening. Get creative with what you can (safely, and in accordance with government guidance) do to replace your commute during this time.

Pretend that you go to work by dressing accordingly, it makes the brain active and makes you stronger against the ‘do something else’  or ‘ relax’ mode activated by the comfy at home clothes.

It’s tempting to work wearing pyjamas, but will this help your productivity and mindset? Getting dressed for work can also help to maintain your work-life balance.

Look after your posture. If possible, sit at a desk with a screen at the right height. 

Try to follow standard health and safety advice when it comes to working long hours at a desk. If possible, invest time and money in making your home working environment a comfortable and non-straining place to be.

If you can at all help it, don’t work in the room where you sleep. It can cause difficulties sleeping.

This also helps add some breaks and changes in your day, which can help to maintain focus and motivation.

Enjoy the benefits of working from home: take a break to actually cook lunch, get things done around the house. Let yourself appreciate the things that are handy about it as well as the negatives. 

Being able to get away from your work and do something like ironing, cooking, baking or cleaning might actually help your productivity and concentration by providing a better break than you might otherwise get in an office. Embrace it!

Schedule social e-contact. Don’t let yourself go more than a day without at least hearing someone’s voice on the phone. Use the opportunity to reconnect with old friends. 

In Reading, we’re making extensive use of Microsoft Teams to remain in contact with each other and try to mimic our vibrant work atmosphere.

Do (as long as it’s safe to do so) go for walks, head outside, make sure you do some exercise twice a week. 

Luckily, we’ve got some very nice weather this week in most of the UK. But do please adhere to social distancing guidelines when you do go outside.

It can be easy for the lines between work and life outside of work to be blurred during a PhD at the best of times, and WFH can make this more problematic. Set your hours, and stick to it.

If you work 8-4, work 8-4! At 4pm, switch your computer off and do something different. Without an evening commute, it can be trickier to bring an end to your working day, but this is probably one of the most important things to maintain.

Most operating systems, including Windows 10, support multiple virtual desktops. Try using one of those for your virtual “work” PC, and another as your virtual “home” PC. Then you can keep the two segregated. 

At the end of the day you can switch to your “home” desktop, and then return to “work” the following day.

This Twitter thread has some great advice: https://twitter.com/ProfAishaAhmad/status/1240284544667996163?s=19

Twitter is of course full of great (and not so great) advice. It can keep people connected but also increase anxiety. Be cautious with it, along with all social media during this time.

Allow yourself ample time to adjust, get the important things in order first (friends/family/food/fitness), and build a regular schedule.

This is a huge change. It’s not just a huge change to work, it’s a huge change to our entire lives. Go easy on yourself as you get into the swing of things.

Fill the space around you with plants – it’ll make you feel like you’re outside if you don’t have that luxury – and open your windows every morning (you’ll appreciate the fresh air!) 

Nature is very calming. Open the window, listen to the birds (you might hear them more than you used to nowadays).

Extending our best wishes to all from everyone in Reading Meteorology during this challenging time.

Wisdom from experience: advice for new PhD students

The new academic year is now underway, and a new bunch of eager first year PhD students are dipping their toes into a three-to-four year journey to their doctorate. So, we’ve collated some advice from the more experienced among us! The idea behind the following tidbits of advice is that they are things we would tell our younger selves if we could go back to day 1…

Work

“Make sure you and your supervisor set out expectations and at least a vague timeline at the start, that way you will know you’re on track.”

“Write code as if you’re giving it to someone else – one day you might have to.”

Even if you don’t give your code to another use, in a year’s time you’ll have forgotten what it does! Related to this, it’s useful to keep good “readme” documents to note where all your code is, how to run things, etcetera. Also, if you think you’re going to present a plot at some point – in a talk, paper, or even your thesis, make a final version at the time (using appropriately accessible colour maps and big enough labels), plus note down where you’ve stored the code you used to make it.

“Learn and use git/github (or at least get familiar with the 3 basic commands of: git add, commit, push) ASAP! This means that if you take a wrong turn in your code (you will), you can painlessly ‘revert’ to a stage before you made a mess.”

“Read papers with your literature review in mind. If you can’t see where the paper will fit in your literature review, either reconsider your literature review… or find a more relevant paper.”

“Write down everything you learn, or facts you are told – you never know when you’ll need a piece of information again.”

But also be prepared to have not really followed any of this advice properly until you regurgitate it to new students in your fourth year and wonder why you haven’t been doing any of it up until now.

“Try to keep up a good routine – it’s much easier to get out of bed when you’re having a slow work week if that’s what your body is used to.”

“You’ll be amazed at how much you’ll learn and master without even realising.”

“Don’t compare yourself to others.”

Every PhD project is unique, as is every student. During a PhD, you’re looking into the unknown. Maybe you’ll get lucky (with some hard work) and have some really interesting results, or it might be a bit of a battle. Some projects are more suited to regular publications, others less so – this doesn’t necessarily reflect your individual abilities. In addition, everyone has different background knowledge and motivation for doing a PhD.

“Not every day has to be maximum productivity, that’s okay!”

“Some days are great, others are rubbish. Like life, really.”

Life

“Make friends with other PhD students. It’s nice to have someone who might make you cake when you feel sad, or happy.”

This is so true. A PhD is quite a unique experience and lots of people don’t really get it, thinking it’s just like another undergrad. Sometimes it’s really useful to have someone who understands the stress of some code just not working, or the dread of a blank page where your monitoring committee report should be. It’s also helpful to get to know people in the years above, or even post-docs, since they’ve probably already gone through what you’re experiencing.

“Make friends and join clubs and societies with people that aren’t doing PhDs.”

Sometimes it’s important to get out of the PhD “bubble” and put things in perspective. Keeping in touch with friends that have “real” jobs (for want of a better word) can be a nice reminder of some of the benefits of PhD life – such as flexible hours (you don’t have to be in before 9 every day) or not having to wear formal business attire.

Wellbeing

“Try to keep your weekends free – it’s great for your sanity!”

“Take holiday! You are expected to.”

“Don’t feel guilty for not cheering up when people tell you everything’s okay. It almost invariably is, but sometimes it all gets a bit much and you’ll feel bad for a while, that’s totally normal!”

Yes, it’s totally okay to have a couple of bad days. Remember, this can often be true of people with ‘real’ jobs, it isn’t just unique to the PhD experience! However, if you’re feeling bad for a long period of time, it’s important to acknowledge that this isn’t okay and you don’t have to feel like that. It might be helpful to let your supervisor know that you’re having a bit of a hard time, for whatever reason, and work might be slow for a while. There are also lots of support systems available. For students at Reading, you can find out more about the Counselling and Wellbeing Service here (http://www.reading.ac.uk/cou/counselling-services-landing.aspx). A PhD is hard work, but it should be a fundamentally enjoyable experience!

Finally:

“No poking your supervisor with a stick. They don’t appreciate it.”

(…no, we don’t get it either)


Co-written by Simon Lee and Sally Woodhouse, with anonymous pieces of advice collected from various PhD students in the Department of Meteorology.

PhD Visiting Scientist 2019: Prof. Cecilia Bitz

r.frew@pgr.reading.ac.uk

With thanks to all my helpers who enabled the week to go smoothly! Adam Bateson, Sally Woodhouse, Kaja Milczewska and Agnieszka Walenkiewicz

Each year PhD students in the Department of Meteorology invite a distinguished scientist to spend a week with us.  This year we invited Prof. Cecilia Bitz, who visited between the 28th-31st May. Cecilia is based at the University of Washington, Seattle. 

Cecilia’s research interests are the role of sea ice in the climate system, and high latitude climate and climate change. She has also done a lot of work on the predictability of Arctic sea ice, and is involved in the Sea Ice Prediction Network.

The week began with a welcome reception in the coffee area, introducing Cecilia to the department, followed by a seminar by Cecilia on ‘Polar Regions as Sentinels of Different Climate Change’. The seminar predominantly focused on Antarctic sea ice, and the possible reasons why Antarctic sea ice behaviour is so different to the Arctic. Whilst Arctic sea ice has steadily declined we have seen Antarctic sea ice expansion over the past four decades, with extreme Antarctic sea ice extent lows since 2016.

Throughout the week Cecilia visited a number of the research groups, including Mesoscale, HHH (dynamics) and Cryosphere, where PhD students from each group presented to her, giving a taste of the range of PhD research within our department. 

Cecilia gave a second seminar later in the week in the Climate and Ocean Dynamics (COD) group meeting, this time focusing on the other pole, ‘Arctic Amplification: Local Versus Remote Causes and Consequences’. Cecilia discussed her work quantifying the role of feedbacks in Arctic Amplification, how they compare with meridional heat transports, and what influence Arctic warming has on the rest of the globe.

cuteness_on_ice
Photo Credit: Cecilia Bitz

On Wednesday afternoon the normal PhD group slot consisted of a career discussion, with Cecilia. Cecilia shared some of her career highlights with us, including extra opportunities she has taken such as doing some fieldwork in Antarctica and working for the charity, Polar Bears International, her insights and advice from her own experiences, as well as about post-doctoral opportunities in the US. A few of my personal take-aways from this session were to try give yourself space to learn one new thing at a time in your career (e.g. teaching, writing proposals, supervising etc). Try to work on a range of problems, and keep your outlook broad and open to new ideas and approaches. Take opportunities when they appear, such as fieldwork or short projects/collaborations. 

A small group of PhDs also met with her on the Friday to have an informal discussion about climate policy. In particular about her experiences speaking to the US senate, being a part of the IPCC reports and about the role of scientists in speaking about climate change, and whether we have a responsibility to do so.

Thursday evening the PhDs took Cecilia to Zero Degrees (a very apt choice for a polar researcher!), and enjoyed a lovely evening chatting over pizza and beer. 

The week ended with a farewell coffee morning on Friday, where we gave Cecilia some gifts to thank her for giving us her time this week including some tea, chocolates, a climate stripes mug and a framed picture of us… 

All the PhDs had a great week. We hope Cecilia enjoyed her visit as much as we did!

GroupPhoto
PhD students with Cecilia Bitz before the Careers Discussion.

My tips, strategies and hacks as a PhD student

Email: m.prosser@pgr.reading.ac.uk

Having been a PhD student for a little over 3 months I am perhaps ill-qualified to write such a ‘PhD tips’ type of blog post, but write one I appear to be doing! It’s probably actually more accurately titled ‘study tips in general but ones which are highly relevant to science PhDs.’

The following are just my tips on what have helped me over the course of my studies and may be obvious or not suitable for others, but I write them on the off-chance that something here is useful to someone out there. No doubt I will have many more such strategies by the end of my time here in Reading!

Papers and articles
As a science student you may have encountered these from time to time. The better ones are clearly written and succinct, the worse ones are verbose and obscurantist. If you’re not the quickest reader in the world, getting through papers can end up consuming a great deal of your time.

I’m going to advocate speed reading in a bit but when you start learning speed reading, one of the things they ask you to think about first is “Do I really need to read this?”. If the answer is yes, then the next question is “Do I really need to read all of it?”. Perhaps you only need to glance at just the abstract, figures and conclusion? After all, time spent reading this is time not spent doing something else, something more profitable perhaps, so do check that it really is worth your time before diving in.

So once I’ve ascertained that the article is indeed worth my time, I sit down with a pencil (or the equivalent for a PDF) and read through the sections I’ve decided on. Anything that makes my neurons spike (“oh that’s interesting….”), I underline or highlight. Any thoughts or questions that occur to me, I write in the margin. If I feel the need to criticise the paper for being insufficiently clear then I write down these remarks, too.

Once I get to the end, I put the article away out of sight and sit down with a blank piece of paper (or on a computer) and try and write something very informally about what I’ve just read. Quite often my mind will go helpfully blank at this point, so I try and finish the following sentence: “The biggest thing (if anything) I learned from this article was….”. Completing this one sentence then tends to lead to other stuff tumbling out and in no particular order I jot these all down. Only once the majority of it is down on paper do I take a peek at the annotated piece to see what I missed (For heaven’s sake avoid painting the article yellow with a highlighter!)

Please, please, please, don’t.

This personal blurb that you have produced is then a good way to quickly remind yourself of the contents of that article in the future without having to reread it from scratch. This post-reading exercise need not take more than 15 minutes but if you’re worried about spending this extra time, don’t be. You’ll save yourself a heap of time in future by not having to reread the damn thing.

Random piece of advice – if you are unaware of the Encyclopedia of Atmospheric Sciences, then check it out. Whatever your PhD topic I guarantee there’ll be 10 or so shortish entries which are all highly relevant to your particular PhD topic and consequently worth knowing about!

Speed reading
Really still on the previous paragraph but as is often the way, between the valuable articles that you really should be reading and the stuff for which life’s really too short there’s a grey area.
For such grey areas I am an advocate of speed reading.
For any electronic texts check out this free website:

Just copy, paste and go! https://accelareader.com/

The pace the words flash up doesn’t have to be particularly fast (I suggest trying 300 wpm to start with) but the golden rule is to never press pause once you’ve started. No going back to read stuff you’ve missed (well not until you’ve reached the end first at least!). This method of reading is especially useful for any articles that feel like quagmires into which you are slowly drowning. Paradoxically reading faster in such instances often increases one’s comprehension.

A good way to develop the skill of speed reading is to start on articles you see posted on social media, articles that you are not too fussed about getting every single detail. Just let it wash over you!

Talks and lectures
I have found it useful to make audio recordings of these. I don’t usually tend to listen back, but if there is something that was particularly interesting or dense that might be worth revisiting then it can be very worthwhile. I make a note of the time this something was said at the time it was said and can thus track it down in the recording fairly painlessly afterwards.

One tip about note taking that has stayed with me since I first heard it several years back was the following: after writing down the title, only make notes on what is surprising or interesting to you, just that! This may result in many lines of notes or no lines at all, but whatever you do, don’t just make notes of everything that was said. This advice has been very useful for me.

Organising
Ask me in person if you would like to know my thoughts on this.

Programming to help physical intuition.
This is probably more relevant to students like me who didn’t come from a maths or physics undergrad and consequently aren’t quite as fluent in the old maths….or perhaps undergrads for that matter…
….but in my undergrad (environmental science) I spent quite a lot of the time spent studying maths (and to a lesser extent) physics involved memorising complicated procedures. The best example of this was a lecture on Fourier Series where the professor took the whole hour to work through the process of getting from an input (x^2) to the output (first n terms of the Fourier series). Because it took so much space/effort for me to remember this lengthy process, it ended up crowding out the arguably more important conceptual stuff, such as what a Fourier series actually does and why it is it so useful. When all is said and done and the final exam is handed in, these concepts are what should (ideally) stick with you even if the details of how, don’t.
So here’s where I think programming can come in. Firstly, there’s nothing like coding up some process to check whether you understand the nuts and bolts of it, but more importantly once it has been coded up properly you can then play about with the inputs to see how these affect the graphed outputs. Being able to ‘play’ about like this gives you a more intuitive feel for the model/process that wouldn’t be possible if you had to manually redo the laborious calculations each time you wanted to change the input parameters. 3 examples of where I have done this myself are the following:
1. Getting my head around the thermal inertia of the oceans by varying the depth of the surface and deep layer of the ocean in a simple model.
2. Playing around graphically with dispersion.
3. Convincing myself that it really is true that in the middle of the Northern Hemisphere summer the north pole receives more energy per day than the equator.

And you?
So do you have any hard won study/research tips? If so do email me as I would be interested in hearing about them!
Which study hack do you think I (or others) are most lacking?

Reflecting on starting a PhD

Now that Christmas is just around the corner, and us first year students have settled in to the swing of things, I thought it would be nice to write a short piece on what it’s like starting a PhD.

green-chameleon-21532-unsplash

Reflecting on my experience so far, my first thought was to remark at how I’d only been a PhD student for a little over two months. Frankly, I don’t think I’ve ever learnt so much in quite so short a time before. This was an encouraging thought, because often in the moment progress can seem very slow indeed. However, when you put it all together and zoom out a little, you realise how far you’ve come. If you feel like you’ve wasted a day lost in code, or just generally lost, it’s never wasted; it’s your PhD and is a constant learning process. I’ve found it really rewarding sometimes to simply explore what I find interesting, or practice different ways of making figures. I would recommend that if something, anything, sparks your interest, investigate it, and read up about it. If it comes to nothing, or if you’re not ready to write a journal paper at the end of the day, well, the skills and familiarities you picked up may eventually go towards doing so! Don’t be afraid of not doing the perfect job first time or making a mistake.

The day-to-day life of doing a PhD is also very dynamic. Perhaps I thought I would only spend long hours sitting at my desk in front of a monitor, but every day is different. Research groups, seminars, and social activities really add variety and inspiration to each and every day, even if it means pulling myself away from my data for a small amount of time! I’d recommend to any first year to get involved as much as possible. It is the best way to get to know people in your department and beyond and how they do science! I will admit it took me a little while at first to treat all these different aspects of a typical day as “PhD work”, but that’s the right mindset to be in.

Finally, getting to know other PhD students and researchers has been one of the best and most eye-opening elements so far. In fact, I would say it is almost a crucial part of the process. I am always grateful to those higher up the academic chain, who, despite being busy, are continually happy to offer advice from the small to the big things. At first, I felt like I would be some sort of annoyance asking other people for help on something, or that I should be able to work it out for myself. However, one comes to realise everyone is delighted to help and share their expertise with you. That’s what being a scientist is about, right? As Google Scholar reminds us on each visit: “Stand on the shoulders of giants.” Those older PhDs may scoff at being referred to as giants, but to someone starting a PhD, daunted at how far there is to go and how much there is to do, well… they’ve done a large part of it!

photo-1515524738708-327f6b0037a7

It’s not possible to always see the positives all the time, especially with research. However, one thing is for sure: you not only grow huge amounts as a scientist, but generally as a person, and I think if you keep that in mind, it all makes that little bit more sense.

Email: a.j.doyle@pgr.reading.ac.uk

Faster analysis of large datasets in Python

Have you ever run into a memory error or thought your function is taking too long to run? Here are a few tips on how to tackle these issues.

In meteorology we often have to analyse large datasets, which can be time consuming and/or lead to memory errors. While the netCDF4, numpy and pandas packages in Python provide great tools for our data analysis, there are other packages we can use, that parallelize our code: joblib, xarray and dask (view links for documentation and references for further reading). This means that the input data is split between the different cores of the computer and our analysis of different bits of data runs in parallel, rather than one after the other, speeding up the process. At the end the data is collected and returned to us in the same form as before, but now it was done faster. One of the basic ideas behind the parallelization is the ‘divide and conquer’ algorithm [Fig. 1] (see, e.g., Cormen et al. 2009, or Wikipedia for brief introduction), which finds the best possible (fastest) route for calculating the data and return it.

divide_and_conquer
Figure 1: A simple example of the ‘divide and conquer’ algorithm for sorting a list of numbers. First the list is split into simpler subproblems, that are then solved (sorted) and merged to a final sorted array. Source

The simplest module we can use is joblib. This module can be easily implemented for for-loops (see an example here): e.g. the operation that needs to be executed 1000 times, can be split between 40 cores that your computer has, making the calculation that much faster. Note that often Python modules include optimized routines, and we can avoid for-loops entirely, which is usually a faster option.

The xarray module provides tools for opening and saving multiple netCDF-type (though not limited to this) datasets, which can then be analysed either as numpy arrays or dask arrays. If we choose to use the dask arrays (also available via dask module), any command we use on the array will be calculated in parallel automatically via a type of ‘divide and conquer’ algorithm. Note that this on its own does not help us avoid a memory error as the data eventually has to be loaded in the memory (potentially using a for-loop on these xarray/dask arrays can speed-up the calculation). There are often also options to run your data on high-memory nodes, and the larger the dataset the more time we save through parallelization.

In the end it really depends on how much time you are willing to spend on learning about these arrays and whether it is worth the extra effort – I had to use them as they resolved my memory issues and sped up the code. It is certainly worth keeping this option in mind!

Getting started with xarray/dask

In the terminal window:

  • Use a system with conda installed (e.g. anaconda)
  • To start a bash shell type: bash
  • Create a new python environment (e.g. ‘my_env’) locally, so you can install custom packages. Give it a list of packages:
    • conda create -n my_env xarray
  • Then activate the new python environment (Make sure that you are in ‘my_env’ when using xarray):
    • source activate my_env
  • If you need to install any other packages that you need, you can add them later (via conda install), or you could list them with xarray when you create the environment:
    • conda install scipy pandas numpy dask matplotlib joblib #etc.
  • If the following paths are not ‘unset’ then you need to unset them (check this with command: conda info -a):
    • unset PYTHONPATH PYTHONHOME LD_LIBRARY_PATH
  • In python you can then simply import xarray, numpy or dask modules:
    • import xarray as xr; import dask.array as da; import numpy as np; from joblib import Parallel, delayed; # etc.
  • Now you can easily import datasets [e.g.: dataset = xr.open_dataset() from one file or dataset = xr.open_mfdataset() from multiple files; similarly dataset.to_netcdf() to save to one netcdf file or xr.save_mfdataset() to save to multiple netcdf files] and manipulate them using dask and xarray modules – documentation for these can be found in the links above and references below.
  • Once you open a dataset, you can access data either by loading it into memory (xarray data array: dataset.varname.values) and further analyzing it as before using numpy package (which will not run in parallel); or you can access data through the dask array (xarray dask array: dataset.varname.data), which will not load the data in the memory (it will create the best possible path to executing the operation) until you wish to save the data to a file or plot it. The latter can be analysed in a similar way as the well-known numpy arrays, but instead using the dask module [e.g. numpy.mean (array,axis=0) in dask becomes dask.array.mean (dask_array,axis=0)]. Many functions exist in xarray module as well, meaning you can run them on the dataset itself rather than the array [e.g. dataset.mean(dim=’time’) is equivalent to the mean in dask or numpy].
  • Caution: If you try to do too many operations on the array the ‘divide and conquer’ algorithm will become so complex that the programme will not be able to manage it. Therefore, it is best to calculate everything step-by-step, by using dask_array.compute() or dask_array.persist(). Another issue I find with these new array-modulesis that they are slow when it comes to saving the data on disk (i.e. not any faster than other modules).

I would like to thank Shannon Mason and Peter Gabrovšek for their helpful advice and suggestions.

References

Cormen, T.H., C.E. Leiserson, R.L. Rivest, C. Stein, 2009: An introduction to algorithms. MIT press, third edition, 1312 pp.

Dask Development Team, 2016: Dask: Library for dynamic task scheduling. URL: http://dask.pydata.org

Hoyer, S. & Hamman, J., 2017. xarray: N-D labeled Arrays and Datasets in Python. Journal of Open Research Software. 5, p.10. DOI: http://doi.org/10.5334/jors.148

Hoyer, S., C. Fitzgerald, J. Hamman and others, 2016: xarray: v0.8.0. DOI: http://dx.doi.org/10.5281/zenodo.59499

Rocklin, M., 2016: Dask: Parallel Computation with Blocked algorithms and Task Scheduling. Proceedings of the 14th Python in Science Conference (K. Huff and J. Bergstra, eds.), 130 – 136.

Why become a Royal Meteorological Society Student member?

This week the Royal Meteorological Society (RMetS) published their strategic plan for the period of 2018 to 2020, and here at Social Metwork HQ we thought it would be a splendid idea to reflect on the benefits of being a student member of the Royal Meteorological Society.

An important benefit in my opinion is that when becoming a member of RMetS you join a well-established community who hold enthusiasm about the weather and climate at its core. Members come from all corners of the world and at different stages of their career spanning the entire range: from the amateur weather enthusiasts to professionals.  nicole-kuhn-450747As a student, being an RMetS member can lead to conversations that could develop your career and bring unexpected opportunities. This has been greatly enhanced with the RMetS mentoring scheme.

RMetS host many different types of meetings, including annual conferences, meetings hosted by regional centres, and national meetings. Additional gatherings are held by special interest groups, ranging from Weather Arts & Music to Dynamical Problems. Meetings on a regional and national scale provide a platform for discussion and learning amongst those in the field. DEhXj9AXkAARyMM.jpg largeFor a student, the highlight in the RMetS calendar is the annual student conference. Every year, sixty to eighty students come together to present their work and develop professional relationships that continue for years to come. This year’s conference is hosted at the University of York on the 5th and 6th July 2018 (more information). After two student conferences under my belt (see previous blog post), I would highly recommend any early career research scientist attending this event. It serves as a platform to share their own work in a friendly atmosphere and be inspired by the wider student community.

nasa-63030Other benefits to becoming an RMetS student member include eligibility to the Legacies Fund, grants and fellowships, and receiving a monthly copy of Weather magazine. Most importantly though, through becoming a RMetS member you support a professional society who are committed to increasing awareness of the importance of weather and climate in policy and decision-making. Alongside this week’s publication of RMetS’ strategic plan, both the Met Office and NASA have published press releases stating that 2017 was the warmest year on record without El Niño. The atmosphere and oceans of our planet are changing at unprecedented rates: rising sea levels, reductions in Arctic sea-ice, and an increased frequency of extreme weather events to name but a few climate change impacts. Becoming an RMetS student member does not only benefit your career and knowledge, but also supports a society that is committed to promoting and raising awareness of weather and climate science.

Surviving the Viva

Email: d.l.a.flack@reading.ac.uk

Recently in the department we have had a fair number of students submitting their PhD theses and awaiting or completing their viva.

For many students at the start of the PhD the viva seems a long way off and can often be thought of as a terrifying experience. So why then do many PhD students come out of their viva saying that they enjoyed it? and is it really as XKCD portray it?

MY RESULTS ARE A SIGNIFICANT IMPROVEMENT ON THE STATE OF THE AAAAAAAAAAAART
Thesis defense according to XKCD

With the help of some former PhD students (Hannah Bloomfield, Sammie Buzzard, Hannah Gough and Leo Saffin) we’ve come up with a summary of our own experiences and some advice for people just about to go in.

But before I get into that I’ll briefly explain a little bit about the viva. The viva is (alongside writing the thesis) the examination for the PhD. Its essentially an oral exam where you sit and talk about your thesis and the area surrounding your field. The viva can last anywhere between 90 minutes and 5 hours, depending on how much you have to talk about (and how much you or your examiners talk). The result from the viva is as follows: Fail; Major Corrections requiring another viva; Pass: Major corrections; Pass: Minor corrections (the most common) and Pass: No corrections (very rare), and at the end of the day it’s the pass or fail that matters.

So what can you expect from a viva? Well, as with each PhD each viva is different (hence why this post is a collaborative effort). Even people’s nerves are different, some go in feeling confident, whilst others are still fairly nervous about it (which of course is very understandable). I certainly was in the nervous camp, but I would have been disappointed if I wasn’t because I always feel I perform better if I am nervous beforehand. Indeed, many of us who are initially nervous become relaxed as soon as we get into the swing of things and the questions start flowing. Furthermore, many examiners (not all) will know and understand that you will be nervous so will immediately put you at ease by saying something along the lines of “I really enjoyed reading your thesis and you don’t need to be worried about the result.” This last statement is probably key for anyone going into the viva – by the time it gets to the viva your examiners have already decided the result, the viva is mainly to check that you did the work.

Looking at the recent experiences of the PhD students I have broadly classified the viva into three types, Presentation,Traditional” and Thesis covering described below.

Presentation (Hannah Gough):

Hannah was asked to produce a presentation for her viva. She did find this useful as it was a good way to settle into the viva and bring across the aims and key conclusions of her thesis, at the same time highlight what she felt was the most important figures in her thesis. After the presentation, the examiners asked questions on her entire thesis. These ranged from points of clarification, to the wider implications of her work.

Traditional” (Hannah Bloomfield, Sammie Buzzard and Leo Saffin):

The more “traditional” viva asks you to summarise your thesis for the first 3-5 minutes and then goes through the thesis asking about wider implications and where your work fits in, basic theory, parts of the thesis they are unsure about and implications of your work (amongst other things).

Thesis covering (myself):

Essentially, all we did was go through my thesis cover-to-cover discussing bits specifically related to my project (some minor wider implications/knowledge) and comments that they had on my work.

So why do people enjoy the viva then? Well, there is a fairly simple answer to this question. You’ve been doing work for between three and four years and now you get to discuss it in detail and the examiner can see that you know what you are talking about and will often ask some interesting and thought provoking questions that you either haven’t considered or didn’t necessarily view as important.

Other things that are worth mentioning about the viva, before going on to our collective advice, is that most of the time (unless you spend a while talking about basics of your area) the viva doesn’t feel it is taking as long as it actually is (2 hours feels like 15 minutes – I’m not just saying that, it really does!) – it’s essentially the old saying “time flies when you are having fun”.

So, that’s a brief overview of the viva and our experiences, so how do you actually survive it? Our collective advice would be as follows:

  1. You are the expert in your thesis – so don’t panic – your examiners don’t know as much about what you did as you do.
  2. The examiners are not there to trick you, they are just checking that you did your work – they’ve already made the pass/fail decision.
  3. Don’t be afraid to ask for breaks from time to time (your examiners may want a break too).
  4. Don’t look at the clock (if there is one in the room). All you will then do is think about how long you have been in the viva.
  5. Bring food (biscuits, etc) and enough to share with your examiners.
  6. Prepare a simple 3-5 minute overview of your thesis and know it well – generally you will be asked to summarise your thesis.
  7. It can be useful to read a couple of your external examiners papers – just to find out a little bit about them at the very least.
  8. Don’t be afraid to ask questions to be explained in more detail so you know exactly what they want.
  9. Eat something before you go in no matter how bad you feel.
  10. Try and get a good night’s sleep beforehand.
  11. Don’t be afraid to say how you would do things differently, after having had time to look back at it.
  12. You are the expert in your thesis – so don’t panic – your examiners don’t know as much about what you did as you do.

With that all I can say if you are facing a viva soon is good luck.

A special thanks to all the former PhD students that helped provide information for this blog: Hannah Gough, Hannah Bloomfield, Samantha Buzzard and Leo Saffin.

Managing your supervisor

Written by: h.l.gough@pgr.reading.ac.uk

You’re going to be working with them for a while. Supervisors, like projects, are all unique and have their own ways of working. Lots of us have banded together to give tips and advice on how to ‘manage your supervisor’ and by that we mean make the road towards a PhD a little bit easier.

For those of you looking to start a PhD, getting the right match between you and a supervisor is key. PhDs are already stressful enough without a strained supervisor-student relationship.

Know how they work

Supervisors all work differently. Some will leave you to wander for a bit before drawing you back to the point, and others will provide a map of where you’re going. There’s no right or wrong but sometimes their methods can get frustrating when you start comparing supervisors.

Find out the best way to contact them. Some never reply to email and others are never in the office or dislike being disturbed. Figure out between you and your supervisor the best way of getting in contact.

Personal and work balance

Some supervisors are happy to talk about personal problems. Others aren’t. Again, neither option is right or wrong, but it’s something you have to be aware of.

Ask for things

A PhD is intended as a personal development training programme and not just for writing a thesis and publishing papers. Don’t be afraid to ask to do something different, such as environment-Yes, internships, field work and summer schools to name a few.

If you don’t ask, you don’t get.

Manage expectations

Saying yes to all the work they give you is only going to lead to disappointment for them and you. Be honest with the amount of work you can do, and say when you’re having a bad week. They’ll understand. Say when you’ve got enough on your plate already.

Know how long they take to read things, otherwise you’ll end up disappointed when the feedback you expected on a certain day doesn’t arrive.

Don’t expect them to be on email 24/7. Likewise, let them know that you’re not going to be checking emails at 3am either.

Know their style and expertise

Some come across more critical than others, some highlight the good as well as the bad. Their subject may make them biased on certain topics. Knowing their expertise allows you to tailor questions for them.

This is a lot more relevant to people with multiple supervisors, as often you can get two conflicting opinions and have no idea which one to accept. This happens, and it does teach you some diplomacy skills, but don’t go picking sides.

Get advice from other students

Chances are, other students will be supervised by your supervisor. Ask them for hints and tips of how they work. Ask about pitfalls to avoid and helpful tips. They might even have a manual on how to deal with them! There is a camaraderie between people who share the same supervisor!

If you’re still stuck and doing a PhD at Reading University, there’s an RRDP course by the graduate school called managing your supervisor. Definitely worth going to.